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2024
	Zhang, Xinyu; Burattini, Margherita; Duru, Jens; Chala, Nafsika; Wyssen, Nino; Cofiño-Fabres, Carla; Rivera-Arbeláez, José Manuel; Passier, Robert; Poulikakos, Dimos; Aldo Ferrari, Christina Tringides ; Vörös, János; Luciani, Giovanni Battista; Miragoli, Michele; Zambelli, Tomaso Multimodal Mapping of Electrical and Mechanical Latency of Human-Induced Pluripotent Stem Cell-Derived Cardiomyocyte Layers Journal Article ACS Nano, 2024, ISSN: 1936-0851. Abstract \| Links \| BibTeX \| Tags: Cardiomyocytes, HD-MEA, IPSC, MaxOne, MEA Technology @article{Zhang2024, title = {Multimodal Mapping of Electrical and Mechanical Latency of Human-Induced Pluripotent Stem Cell-Derived Cardiomyocyte Layers}, author = {Xinyu Zhang and Margherita Burattini and Jens Duru and Nafsika Chala and Nino Wyssen and Carla Cofiño-Fabres and José Manuel Rivera-Arbeláez and Robert Passier and Dimos Poulikakos and Aldo Ferrari, Christina Tringides and János Vörös and Giovanni Battista Luciani and Michele Miragoli and Tomaso Zambelli}, url = {https://doi.org/10.1021/acsnano.4c03896}, doi = {10.1021/acsnano.4c03896}, issn = {1936-0851}, year = {2024}, date = {2024-08-22}, journal = {ACS Nano}, abstract = {The synchronization of the electrical and mechanical coupling assures the physiological pump function of the heart, but life-threatening pathologies may jeopardize this equilibrium. Recently, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a model for personalized investigation because they can recapitulate human diseased traits, such as compromised electrical capacity or mechanical circuit disruption. This research avails the model of hiPSC-CMs and showcases innovative techniques to study the electrical and mechanical properties as well as their modulation due to inherited cardiomyopathies. In this work, hiPSC-CMs carrying either Brugada syndrome (BRU) or dilated cardiomyopathy (DCM), were organized in a bilayer configuration to first validate the experimental methods and second mimic the physiological environment. High-density CMOS-based microelectrode arrays (HD-MEA) have been employed to study the electrical activity. Furthermore, mechanical function was investigated via quantitative video-based evaluation, upon stimulation with a β-adrenergic agonist. This study introduces two experimental methods. First, high-throughput mechanical measurements in the hiPSC-CM layers (xy-inspection) are obtained using both a recently developed optical tracker (OPT) and confocal reference-free traction force microscopy (cTFM) aimed to quantify cardiac kinematics. Second, atomic force microscopy (AFM) with FluidFM probes, combined with the xy-inspection methods, supplemented a three-dimensional understanding of cell−cell mechanical coupling (xyz-inspection). This particular combination represents amulti-technique approach to detecting electrical and mechanical latency among the cell layers, examining differences and possible implications following inherited cardiomyopathies. It can not only detect disease characteristics in the proposed in vitro model but also quantitatively assess its response to drugs, thereby demonstrating its feasibility as ascalable tool for clinical and pharmacological studies.}, keywords = {Cardiomyocytes, HD-MEA, IPSC, MaxOne, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close The synchronization of the electrical and mechanical coupling assures the physiological pump function of the heart, but life-threatening pathologies may jeopardize this equilibrium. Recently, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a model for personalized investigation because they can recapitulate human diseased traits, such as compromised electrical capacity or mechanical circuit disruption. This research avails the model of hiPSC-CMs and showcases innovative techniques to study the electrical and mechanical properties as well as their modulation due to inherited cardiomyopathies. In this work, hiPSC-CMs carrying either Brugada syndrome (BRU) or dilated cardiomyopathy (DCM), were organized in a bilayer configuration to first validate the experimental methods and second mimic the physiological environment. High-density CMOS-based microelectrode arrays (HD-MEA) have been employed to study the electrical activity. Furthermore, mechanical function was investigated via quantitative video-based evaluation, upon stimulation with a β-adrenergic agonist. This study introduces two experimental methods. First, high-throughput mechanical measurements in the hiPSC-CM layers (xy-inspection) are obtained using both a recently developed optical tracker (OPT) and confocal reference-free traction force microscopy (cTFM) aimed to quantify cardiac kinematics. Second, atomic force microscopy (AFM) with FluidFM probes, combined with the xy-inspection methods, supplemented a three-dimensional understanding of cell−cell mechanical coupling (xyz-inspection). This particular combination represents amulti-technique approach to detecting electrical and mechanical latency among the cell layers, examining differences and possible implications following inherited cardiomyopathies. It can not only detect disease characteristics in the proposed in vitro model but also quantitatively assess its response to drugs, thereby demonstrating its feasibility as ascalable tool for clinical and pharmacological studies. Close https://doi.org/10.1021/acsnano.4c03896 doi:10.1021/acsnano.4c03896 Close
	Cartiglia, Matteo; Costa, Filippo; Narayanan, Shyam; Bui, Cat-Vu H; Ulusan, Hasan; Risia, Nicoletta; Haessig, Germain; Hierlemann, Andreas; Cardes, Fernando; Indiveri, Giacomo A 4096 Channel Event-based Multielectrode Array with Asynchronous Outputs Compatible with Neuromorphic Processors Journal Article Nature Communications, 2024. Abstract \| Links \| BibTeX \| Tags: ETH-CMOS-MEA, MEA Technology @article{Cartiglia2024, title = {A 4096 Channel Event-based Multielectrode Array with Asynchronous Outputs Compatible with Neuromorphic Processors}, author = {Matteo Cartiglia and Filippo Costa and Shyam Narayanan and Cat-Vu H. Bui and Hasan Ulusan and Nicoletta Risia and Germain Haessig and Andreas Hierlemann and Fernando Cardes and Giacomo Indiveri}, url = {https://www.nature.com/articles/s41467-024-50783-2}, doi = {10.1038/s41467-024-50783-2}, year = {2024}, date = {2024-08-21}, journal = {Nature Communications}, abstract = {io-signal sensing is pivotal in medical bioelectronics. Traditional methods focus on high sampling rates, leading to large amounts of irrelevant data and high energy consumption. We introduce a self-clocked microelectrode array (MEA) that digitizes bio-signals at the pixel level by encoding changes as asynchronous digital address-events only when they exceed a threshold, significantly reducing off-chip data transmission. This novel MEA comprises a 64 × 64 electrode array, an asynchronous 2D-arbiter, and an Address-Event Representation (AER) communication block. Each pixel operates autonomously, monitoring voltage fluctuations from cellular activity and producing digital pulses for significant changes. Positive and negative signal changes are encoded as “up” and “down” events and are routed off-chip via the asynchronous arbiter. We present results from chip characterization and experimental measurements using electrogenic cells. Additionally, we interface the MEA to a mixed-signal neuromorphic processor, demonstrating a prototype for end-to-end event-based bio-signal sensing and processing.}, keywords = {ETH-CMOS-MEA, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close io-signal sensing is pivotal in medical bioelectronics. Traditional methods focus on high sampling rates, leading to large amounts of irrelevant data and high energy consumption. We introduce a self-clocked microelectrode array (MEA) that digitizes bio-signals at the pixel level by encoding changes as asynchronous digital address-events only when they exceed a threshold, significantly reducing off-chip data transmission. This novel MEA comprises a 64 × 64 electrode array, an asynchronous 2D-arbiter, and an Address-Event Representation (AER) communication block. Each pixel operates autonomously, monitoring voltage fluctuations from cellular activity and producing digital pulses for significant changes. Positive and negative signal changes are encoded as “up” and “down” events and are routed off-chip via the asynchronous arbiter. We present results from chip characterization and experimental measurements using electrogenic cells. Additionally, we interface the MEA to a mixed-signal neuromorphic processor, demonstrating a prototype for end-to-end event-based bio-signal sensing and processing. Close https://www.nature.com/articles/s41467-024-50783-2 doi:10.1038/s41467-024-50783-2 Close
	Lee, Jihyun; Duperrex, Eliane; El-Battrawy, Ibrahim; Hohn, Alyssa; M., Ardan; Saguner, ; Duru, Firat; Emmenegger, Vishalini; Cyganek, Lukas; Hierlemann, Andreas; Ulusan, Hasan CardioMEA: Comprehensive Data Analysis Platform for Studying Cardiac Diseases and Drug Responses Journal Article bioRxiv, 2024. Abstract \| Links \| BibTeX \| Tags: Cardiomyocytes, IPSC, MEA Technology @article{Lee2024, title = {CardioMEA: Comprehensive Data Analysis Platform for Studying Cardiac Diseases and Drug Responses}, author = {Jihyun Lee and Eliane Duperrex and Ibrahim El-Battrawy and Alyssa Hohn and Ardan M. and Saguner and Firat Duru and Vishalini Emmenegger and Lukas Cyganek and Andreas Hierlemann and Hasan Ulusan}, url = {https://www.biorxiv.org/content/10.1101/2024.07.28.605490v1}, doi = {10.1101/2024.07.28.605490}, year = {2024}, date = {2024-07-29}, journal = {bioRxiv}, abstract = {In recent years, high-density microelectrode arrays (HD-MEAs) have emerged as a 25 valuable tool in preclinical research for characterizing the electrophysiology of human 26 induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). HD-MEAs enable the 27 capturing of both extracellular and intracellular signals on a large scale, while minimizing 28 potential damage to the cell. However, a gap exists between technological advancements 29 of HD-MEAs and the availability of effective data-analysis platforms. To address this 30 need, we introduce CardioMEA, a comprehensive data-analysis platform designed 31 specifically for HD-MEA data that have been obtained from iPSC-CMs. CardioMEA 32 features scalable data processing pipelines and an interactive web-based dashboard for 33 advanced visualization and analysis. In addition to its core functionalities, CardioMEA incorporates modules designed to discern crucial electrophysiological features between diseased and healthy iPSC-CMs. Notably, CardioMEA has the unique capability to analyze both extracellular and intracellular signals, thereby facilitating customized analyses for specific research tasks. We demonstrate the practical application of CardioMEA by analyzing electrophysiological signals from iPSC-CM cultures exposed to seven antiarrhythmic drugs. CardioMEA holds great potential as an intuitive, user-friendly platform for studying cardiac diseases and assessing drug effects.}, keywords = {Cardiomyocytes, IPSC, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close In recent years, high-density microelectrode arrays (HD-MEAs) have emerged as a 25 valuable tool in preclinical research for characterizing the electrophysiology of human 26 induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). HD-MEAs enable the 27 capturing of both extracellular and intracellular signals on a large scale, while minimizing 28 potential damage to the cell. However, a gap exists between technological advancements 29 of HD-MEAs and the availability of effective data-analysis platforms. To address this 30 need, we introduce CardioMEA, a comprehensive data-analysis platform designed 31 specifically for HD-MEA data that have been obtained from iPSC-CMs. CardioMEA 32 features scalable data processing pipelines and an interactive web-based dashboard for 33 advanced visualization and analysis. In addition to its core functionalities, CardioMEA incorporates modules designed to discern crucial electrophysiological features between diseased and healthy iPSC-CMs. Notably, CardioMEA has the unique capability to analyze both extracellular and intracellular signals, thereby facilitating customized analyses for specific research tasks. We demonstrate the practical application of CardioMEA by analyzing electrophysiological signals from iPSC-CM cultures exposed to seven antiarrhythmic drugs. CardioMEA holds great potential as an intuitive, user-friendly platform for studying cardiac diseases and assessing drug effects. Close https://www.biorxiv.org/content/10.1101/2024.07.28.605490v1 doi:10.1101/2024.07.28.605490 Close
	Hoang, Huu; Matsumoto, Nobuyoshi; Miyano, Miyuki; Ikegaya, Yuji; Cortese, Aurelio Dopamine-induced Relaxation of Connectivity Diversifies Burst Patterns in Cultured Hippocampal Networks Journal Article bioRxiv, 2024. Abstract \| Links \| BibTeX \| Tags: Activity Scan Assay, HD-MEA, MaxOne, MEA Technology, Network Assay, Neuronal Networks, Primary Neuronal Cell Culture @article{Hoang2024, title = {Dopamine-induced Relaxation of Connectivity Diversifies Burst Patterns in Cultured Hippocampal Networks}, author = {Huu Hoang and Nobuyoshi Matsumoto and Miyuki Miyano and Yuji Ikegaya and Aurelio Cortese}, url = {https://www.biorxiv.org/content/10.1101/2024.06.26.600923v1}, doi = {10.1101/2024.06.26.600923}, year = {2024}, date = {2024-06-30}, journal = {bioRxiv}, abstract = {The intricate interplay of neurotransmitters orchestrates a symphony of neural activity in the hippocampus, with dopamine emerging as a key conductor in this complex ensemble. Despite numerous studies uncovering the cellular mechanisms of dopamine, its influence on hippocampal neural networks remains elusive. Combining in vitro electrophysiological recordings of rat embryonic hippocampal neurons, pharmacological interventions, and computational analyses of spike trains, we found that dopamine induces a relaxation in network connectivity, characterised by a reduction in spike coherence. This relaxation expands the repertoire of burst dynamics within these hippocampal networks, a phenomenon notably absent under the administration of dopamine antagonists. Our study provides a thorough understanding of the roles of dopamine signalling in shaping functional networks of hippocampal neurons.}, keywords = {Activity Scan Assay, HD-MEA, MaxOne, MEA Technology, Network Assay, Neuronal Networks, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close The intricate interplay of neurotransmitters orchestrates a symphony of neural activity in the hippocampus, with dopamine emerging as a key conductor in this complex ensemble. Despite numerous studies uncovering the cellular mechanisms of dopamine, its influence on hippocampal neural networks remains elusive. Combining in vitro electrophysiological recordings of rat embryonic hippocampal neurons, pharmacological interventions, and computational analyses of spike trains, we found that dopamine induces a relaxation in network connectivity, characterised by a reduction in spike coherence. This relaxation expands the repertoire of burst dynamics within these hippocampal networks, a phenomenon notably absent under the administration of dopamine antagonists. Our study provides a thorough understanding of the roles of dopamine signalling in shaping functional networks of hippocampal neurons. Close https://www.biorxiv.org/content/10.1101/2024.06.26.600923v1 doi:10.1101/2024.06.26.600923 Close
	Beaubois, Romain; Cheslet, Jérémy; Duenki, Tomoya; Venuto, Giuseppe De; Carè, Marta; Khoyratee, Farad; Chiappalone, Michela; Branchereau, Pascal; Ikeuchi, Yoshiho; Levi, Timothée BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network Journal Article Nature Communications, 2024. Abstract \| Links \| BibTeX \| Tags: Activity Scan Assay, closed loop stimulation, HD-MEA, IPSC, MaxOne, MEA Technology, Modeling, Organoids, Stimulation @article{Beaubois2024, title = {BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network}, author = {Romain Beaubois and Jérémy Cheslet and Tomoya Duenki and Giuseppe De Venuto and Marta Carè and Farad Khoyratee and Michela Chiappalone and Pascal Branchereau and Yoshiho Ikeuchi and Timothée Levi }, url = {https://www.nature.com/articles/s41467-024-48905-x}, doi = {10.1038/s41467-024-48905-x}, year = {2024}, date = {2024-06-20}, journal = {Nature Communications}, abstract = {Characterization and modeling of biological neural networks has emerged as a field driving significant advancements in our understanding of brain function and related pathologies. As of today, pharmacological treatments for neurological disorders remain limited, pushing the exploration of promising alternative approaches such as electroceutics. Recent research in bioelectronics and neuromorphic engineering have fostered the development of the new generation of neuroprostheses for brain repair. However, achieving their full potential necessitates a deeper understanding of biohybrid interaction. In this study, we present a novel real-time, biomimetic, cost-effective and user-friendly neural network capable of real-time emulation for biohybrid experiments. Our system facilitates the investigation and replication of biophysically detailed neural network dynamics while prioritizing cost-efficiency, flexibility and ease of use. We showcase the feasibility of conducting biohybrid experiments using standard biophysical interfaces and a variety of biological cells as well as real-time emulation of diverse network configurations. We envision our system as a crucial step towards the development of neuromorphic-based neuroprostheses for bioelectrical therapeutics, enabling seamless communication with biological networks on a comparable timescale. Its embedded real-time functionality enhances practicality and accessibility, amplifying its potential for real-world applications in biohybrid experiments.}, keywords = {Activity Scan Assay, closed loop stimulation, HD-MEA, IPSC, MaxOne, MEA Technology, Modeling, Organoids, Stimulation}, pubstate = {published}, tppubtype = {article} } Close Characterization and modeling of biological neural networks has emerged as a field driving significant advancements in our understanding of brain function and related pathologies. As of today, pharmacological treatments for neurological disorders remain limited, pushing the exploration of promising alternative approaches such as electroceutics. Recent research in bioelectronics and neuromorphic engineering have fostered the development of the new generation of neuroprostheses for brain repair. However, achieving their full potential necessitates a deeper understanding of biohybrid interaction. In this study, we present a novel real-time, biomimetic, cost-effective and user-friendly neural network capable of real-time emulation for biohybrid experiments. Our system facilitates the investigation and replication of biophysically detailed neural network dynamics while prioritizing cost-efficiency, flexibility and ease of use. We showcase the feasibility of conducting biohybrid experiments using standard biophysical interfaces and a variety of biological cells as well as real-time emulation of diverse network configurations. We envision our system as a crucial step towards the development of neuromorphic-based neuroprostheses for bioelectrical therapeutics, enabling seamless communication with biological networks on a comparable timescale. Its embedded real-time functionality enhances practicality and accessibility, amplifying its potential for real-world applications in biohybrid experiments. Close https://www.nature.com/articles/s41467-024-48905-x doi:10.1038/s41467-024-48905-x Close
	Buccino, Alessio Paolo; Damart, Tanguy; Bartram, Julian; Mandge, Darshan; Xue, Xiaohan; Zbili, Mickael; Gänswein, Tobias; Jaquier, Aurélien; Emmenegger, Vishalini; Markram, Henry; Hierlemann, Andreas; Geit, Werner Van A Multimodal Fitting Approach to Construct Single-Neuron Models with Patch Clamp and High-Density Microelectrode Arrays Journal Article Neural Computation (MIT Press), 2024. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, ETH-CMOS-MEA, HD-MEA, MEA Metrics, MEA Technology @article{Buccino2024, title = {A Multimodal Fitting Approach to Construct Single-Neuron Models with Patch Clamp and High-Density Microelectrode Arrays}, author = {Alessio Paolo Buccino and Tanguy Damart and Julian Bartram and Darshan Mandge and Xiaohan Xue and Mickael Zbili and Tobias Gänswein and Aurélien Jaquier and Vishalini Emmenegger and Henry Markram and Andreas Hierlemann and Werner Van Geit}, url = {https://direct.mit.edu/neco/article/doi/10.1162/neco_a_01672/121124/A-Multimodal-Fitting-Approach-to-Construct-Single}, doi = {10.1162/neco_a_01672}, year = {2024}, date = {2024-06-07}, journal = {Neural Computation (MIT Press)}, abstract = {In computational neuroscience, multicompartment models are among the most biophysically realistic representations of single neurons. Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions. The experimental data are then used to fit the many parameters of the model. While patching of the soma is currently the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections. Recording from the soma alone makes it hard to observe and correctly parameterize the activity of nonsomatic compartments. In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density microelectrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at subcellular resolution. In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models. We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone. We also demonstrate our procedure using experimental data by constructing cell models from in vitro cell cultures. The proposed multimodal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and provide the field with neuronal models that are more realistic and can be better validated.}, keywords = {2D Neuronal Culture, ETH-CMOS-MEA, HD-MEA, MEA Metrics, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close In computational neuroscience, multicompartment models are among the most biophysically realistic representations of single neurons. Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions. The experimental data are then used to fit the many parameters of the model. While patching of the soma is currently the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections. Recording from the soma alone makes it hard to observe and correctly parameterize the activity of nonsomatic compartments. In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density microelectrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at subcellular resolution. In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models. We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone. We also demonstrate our procedure using experimental data by constructing cell models from in vitro cell cultures. The proposed multimodal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and provide the field with neuronal models that are more realistic and can be better validated. Close https://direct.mit.edu/neco/article/doi/10.1162/neco_a_01672/121124/A-Multimodal[...] doi:10.1162/neco_a_01672 Close
	Servais, Bram; Mahmoudi, Negar; Gautam, Vini; Tong, Wei; Ibbotson, Michael R; Nisbet, David R; Collins, David Engineering Brain-on-a-Chip Platforms Journal Article Nature Reviews Bioengineering, 2024. Abstract \| Links \| BibTeX \| Tags: 3D Culture, MEA Technology @article{Servais2024, title = {Engineering Brain-on-a-Chip Platforms}, author = {Bram Servais and Negar Mahmoudi and Vini Gautam and Wei Tong and Michael R. Ibbotson and David R. Nisbet and David Collins}, url = {https://www.nature.com/articles/s44222-024-00184-3}, doi = {10.1038/s44222-024-00184-3}, year = {2024}, date = {2024-06-05}, journal = {Nature Reviews Bioengineering}, abstract = {The increasing prevalence of neurological and psychiatric diseases, such as Alzheimer disease and schizophrenia, necessitates the development of new research tools to investigate these diseases and develop effective treatments. Thus, in vitro brain models, such as brain-on-a-chip devices, have been developed to mimic in vivo biochemical and mechanobiological interactions and to monitor their electrochemical activity. In this Review, we discuss the technologies to build complex brain models. We discuss progress in microfluidic and semiconductor-based technologies that facilitate in vitro modelling of the blood–brain barrier and neuronal circuits to study pathophysiological processes. We further discuss advances in 3D tissue engineering, electrode strategies and materials that, when combined, could allow simulation of the native complexity of brain regions and the interrogation of their activity at cellular length scales. Furthermore, we explore the engineering challenges and opportunities for complex physiologically relevant brain-on-a-chip devices and their future progress.}, keywords = {3D Culture, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close The increasing prevalence of neurological and psychiatric diseases, such as Alzheimer disease and schizophrenia, necessitates the development of new research tools to investigate these diseases and develop effective treatments. Thus, in vitro brain models, such as brain-on-a-chip devices, have been developed to mimic in vivo biochemical and mechanobiological interactions and to monitor their electrochemical activity. In this Review, we discuss the technologies to build complex brain models. We discuss progress in microfluidic and semiconductor-based technologies that facilitate in vitro modelling of the blood–brain barrier and neuronal circuits to study pathophysiological processes. We further discuss advances in 3D tissue engineering, electrode strategies and materials that, when combined, could allow simulation of the native complexity of brain regions and the interrogation of their activity at cellular length scales. Furthermore, we explore the engineering challenges and opportunities for complex physiologically relevant brain-on-a-chip devices and their future progress. Close https://www.nature.com/articles/s44222-024-00184-3 doi:10.1038/s44222-024-00184-3 Close
	Sifringer, Léo; Fratzl, Alex; Clément, Blandine F; Chansoria, Parth; Mönkemöller, Leah S; Duru, Jens; Ihle, Stephan J; Steffens, Simon; Beltraminelli, Anna; Ceylan, Eylul; Hengsteler, Julian; Maurer, Benedikt; Weaver, Sean M; Tringides, Christina M; Vulić, Katarina; Madduri, Srinivas; Zenobi-Wong, Marcy; Roska, Botond; Vörös, János; Ruff, Tobias An implantable biohybrid nerve model towards synaptic deep brain stimulation Journal Article bioRxiv, 2024. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, 3D Culture, CMOS, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Retina @article{Sifringer2024, title = {An implantable biohybrid nerve model towards synaptic deep brain stimulation}, author = {Léo Sifringer and Alex Fratzl and Blandine F. Clément and Parth Chansoria and Leah S. Mönkemöller and Jens Duru and Stephan J. Ihle and Simon Steffens and Anna Beltraminelli and Eylul Ceylan and Julian Hengsteler and Benedikt Maurer and Sean M. Weaver and Christina M. Tringides and Katarina Vulić and Srinivas Madduri and Marcy Zenobi-Wong and Botond Roska and János Vörös and Tobias Ruff}, url = {http://biorxiv.org/lookup/doi/10.1101/2024.05.31.596665}, doi = {10.1101/2024.05.31.596665}, year = {2024}, date = {2024-06-03}, journal = {bioRxiv}, abstract = {Restoring functional vision in blind patients lacking a healthy optic nerve requires bypassing retinal circuits, ideally, by directly stimulating the visual thalamus. However, available deep brain stimulation electrodes do not provide the resolution required for vision restoration. We developed an implantable biohybrid nerve model designed for synaptic stimulation of deep brain targets. The interface combines a stretchable stimulation array with an aligned microfluidic axon guidance system seeded with neural spheroids to facilitate the development of a 3 mm long nerve-like structure. A bioresorbable hydrogel nerve conduit was used as a bridge between the tissue and the biohybrid implant. We demonstrated stimulation of spheroids within the biohybrid structure in vitro and used high-density CMOS microelectrode arrays to show faithful activity conduction across the device. Finally, implantation of the biohybrid nerve onto the mouse cortex showed that neural spheroids grow axons in vivo and remain functionally active for more than 22 days post-implantation.}, keywords = {2D Neuronal Culture, 3D Culture, CMOS, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Retina}, pubstate = {published}, tppubtype = {article} } Close Restoring functional vision in blind patients lacking a healthy optic nerve requires bypassing retinal circuits, ideally, by directly stimulating the visual thalamus. However, available deep brain stimulation electrodes do not provide the resolution required for vision restoration. We developed an implantable biohybrid nerve model designed for synaptic stimulation of deep brain targets. The interface combines a stretchable stimulation array with an aligned microfluidic axon guidance system seeded with neural spheroids to facilitate the development of a 3 mm long nerve-like structure. A bioresorbable hydrogel nerve conduit was used as a bridge between the tissue and the biohybrid implant. We demonstrated stimulation of spheroids within the biohybrid structure in vitro and used high-density CMOS microelectrode arrays to show faithful activity conduction across the device. Finally, implantation of the biohybrid nerve onto the mouse cortex showed that neural spheroids grow axons in vivo and remain functionally active for more than 22 days post-implantation. Close http://biorxiv.org/lookup/doi/10.1101/2024.05.31.596665 doi:10.1101/2024.05.31.596665 Close
	Khajehnejad, Moein; Habibollahi, Forough; Paul, Aswin; Razi, Adeel; Kagan, Brett J Biological Neurons Compete with Deep Reinforcement Learning in Sample Efficiency in a Simulated Gameworld Journal Article arXiv , 2024. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, closed loop stimulation, HD-MEA, IPSC, Machine Learning, MaxOne, Modeling, Primary Neuronal Cell Culture @article{Khajehnejad2024, title = {Biological Neurons Compete with Deep Reinforcement Learning in Sample Efficiency in a Simulated Gameworld}, author = {Moein Khajehnejad and Forough Habibollahi and Aswin Paul and Adeel Razi and Brett J. Kagan}, url = {http://arxiv.org/abs/2405.16946}, doi = { https://doi.org/10.48550/arXiv.2405.16946}, year = {2024}, date = {2024-05-27}, journal = {arXiv }, abstract = {How do biological systems and machine learning algorithms compare in the number of samples required to show significant improvements in completing a task? We compared the learning efficiency of in vitro biological neural networks to the state-of-the-art deep reinforcement learning (RL) algorithms in a simplified simulation of the game `Pong'. Using DishBrain, a system that embodies in vitro neural networks with in silico computation using a high-density multi-electrode array, we contrasted the learning rate and the performance of these biological systems against time-matched learning from three state-of-the-art deep RL algorithms (i.e., DQN, A2C, and PPO) in the same game environment. This allowed a meaningful comparison between biological neural systems and deep RL. We find that when samples are limited to a real-world time course, even these very simple biological cultures outperformed deep RL algorithms across various game performance characteristics, implying a higher sample efficiency. Ultimately, even when tested across multiple types of information input to assess the impact of higher dimensional data input, biological neurons showcased faster learning than all deep reinforcement learning agents.}, keywords = {2D Neuronal Culture, closed loop stimulation, HD-MEA, IPSC, Machine Learning, MaxOne, Modeling, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close How do biological systems and machine learning algorithms compare in the number of samples required to show significant improvements in completing a task? We compared the learning efficiency of in vitro biological neural networks to the state-of-the-art deep reinforcement learning (RL) algorithms in a simplified simulation of the game `Pong'. Using DishBrain, a system that embodies in vitro neural networks with in silico computation using a high-density multi-electrode array, we contrasted the learning rate and the performance of these biological systems against time-matched learning from three state-of-the-art deep RL algorithms (i.e., DQN, A2C, and PPO) in the same game environment. This allowed a meaningful comparison between biological neural systems and deep RL. We find that when samples are limited to a real-world time course, even these very simple biological cultures outperformed deep RL algorithms across various game performance characteristics, implying a higher sample efficiency. Ultimately, even when tested across multiple types of information input to assess the impact of higher dimensional data input, biological neurons showcased faster learning than all deep reinforcement learning agents. Close http://arxiv.org/abs/2405.16946 doi: https://doi.org/10.48550/arXiv.2405.16946 Close
	Bucci, Annalisa; Büttner, Marc; Domdei, Niklas; Rosselli, Federica Bianca; Znidaric, Matej; Diggelmann, Roland; Gennaro, Martina De; Cowan, Cameron S; Harmening, Wolf; Hierlemann, Andreas; Roska, Botond; Franke, Felix Action potential propagation speed compensates for traveling distance in the human retina Journal Article bioRxiv , 2024. Abstract \| Links \| BibTeX \| Tags: Activity Assay, Activity Scan Assay, Axon Tracking Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Microfluidics, Modeling, Retina, Slices, Spike Sorting @article{Bucci2024, title = {Action potential propagation speed compensates for traveling distance in the human retina}, author = {Annalisa Bucci and Marc Büttner and Niklas Domdei and Federica Bianca Rosselli and Matej Znidaric and Roland Diggelmann and Martina De Gennaro and Cameron S. Cowan and Wolf Harmening and Andreas Hierlemann and Botond Roska and Felix Franke }, url = {http://biorxiv.org/lookup/doi/10.1101/2024.04.30.591867}, doi = {10.1101/2024.04.30.591867}, year = {2024}, date = {2024-05-01}, journal = {bioRxiv }, abstract = {Neural information processing requires accurately timed action potentials arriving from presynaptic neurons at the postsynaptic neuron. However, axons of ganglion cells in the human retina feature low axonal conduction speeds and vastly different lengths, which poses a challenge to the brain for constructing a temporally coherent image over the visual field. Combining results from microelectrode array recordings, human behavioral measurements, transmission electron microscopy, and mathematical modelling of the retinal nerve fiber layer, we demonstrate that axonal propagation speeds compensate for variations in axonal length across the human retina including the fovea. The human brain synchronizes the arrival times of action potentials at the optic disc by increasing the diameters of longer axons, which increases their propagation speeds.}, keywords = {Activity Assay, Activity Scan Assay, Axon Tracking Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Microfluidics, Modeling, Retina, Slices, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close Neural information processing requires accurately timed action potentials arriving from presynaptic neurons at the postsynaptic neuron. However, axons of ganglion cells in the human retina feature low axonal conduction speeds and vastly different lengths, which poses a challenge to the brain for constructing a temporally coherent image over the visual field. Combining results from microelectrode array recordings, human behavioral measurements, transmission electron microscopy, and mathematical modelling of the retinal nerve fiber layer, we demonstrate that axonal propagation speeds compensate for variations in axonal length across the human retina including the fovea. The human brain synchronizes the arrival times of action potentials at the optic disc by increasing the diameters of longer axons, which increases their propagation speeds. Close http://biorxiv.org/lookup/doi/10.1101/2024.04.30.591867 doi:10.1101/2024.04.30.591867 Close
	Donner, Christian; Bartram, Julian; Hornauer, Philipp; Kim, Taehoon; Roqueiro, Damian; Hierlemann, Andreas; Obozinski, Guillaume; Schröter, Manuel Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains Journal Article PLOS Computational Biology, 2024. Abstract \| Links \| BibTeX \| Tags: ETH-CMOS-MEA, HD-MEA, MaxTwo, MEA Metrics, MEA Technology, Modeling, Primary Neuronal Cell Culture, Spike Sorting, Synapses @article{Donner2024, title = {Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains}, author = {Christian Donner and Julian Bartram and Philipp Hornauer and Taehoon Kim and Damian Roqueiro and Andreas Hierlemann and Guillaume Obozinski and Manuel Schröter }, url = {https://dx.plos.org/10.1371/journal.pcbi.1011964}, doi = {10.1371/journal.pcbi.1011964}, year = {2024}, date = {2024-04-29}, journal = {PLOS Computational Biology}, abstract = {Probing the architecture of neuronal circuits and the principles that underlie their functional organization remains an important challenge of modern neurosciences. This holds true, in particular, for the inference of neuronal connectivity from large-scale extracellular recordings. Despite the popularity of this approach and a number of elaborate methods to reconstruct networks, the degree to which synaptic connections can be reconstructed from spike-train recordings alone remains controversial. Here, we provide a framework to probe and compare connectivity inference algorithms, using a combination of synthetic ground-truth and in vitro data sets, where the connectivity labels were obtained from simultaneous high-density microelectrode array (HD-MEA) and patch-clamp recordings. We find that reconstruction performance critically depends on the regularity of the recorded spontaneous activity, i.e., their dynamical regime, the type of connectivity, and the amount of available spike-train data. We therefore introduce an ensemble artificial neural network (eANN) to improve connectivity inference. We train the eANN on the validated outputs of six established inference algorithms and show how it improves network reconstruction accuracy and robustness. Overall, the eANN demonstrated strong performance across different dynamical regimes, worked well on smaller datasets, and improved the detection of synaptic connectivity, especially inhibitory connections. Results indicated that the eANN also improved the topological characterization of neuronal networks. The presented methodology contributes to advancing the performance of inference algorithms and facilitates our understanding of how neuronal activity relates to synaptic connectivity. Author summary This study introduces an ensemble artificial neural network (eANN) to infer neuronal connectivity from spike times. We benchmark the eANN against existing connectivity inference algorithms and validate it using in silico simulations and in vitro data obtained from parallel high-density microelectrode array (HD-MEA) and patch-clamp recordings. Results demonstrate that the eANN outperforms all other algorithms across different dynamical regimes and provides a more accurate description of the underlying topological organization of the studied networks. Further examinations of the eANN’s output are conducted to identify which input features are most instrumental in achieving this enhanced performance. In sum, the eANN is a promising approach to improve connectivity inference from spike-train data.}, keywords = {ETH-CMOS-MEA, HD-MEA, MaxTwo, MEA Metrics, MEA Technology, Modeling, Primary Neuronal Cell Culture, Spike Sorting, Synapses}, pubstate = {published}, tppubtype = {article} } Close Probing the architecture of neuronal circuits and the principles that underlie their functional organization remains an important challenge of modern neurosciences. This holds true, in particular, for the inference of neuronal connectivity from large-scale extracellular recordings. Despite the popularity of this approach and a number of elaborate methods to reconstruct networks, the degree to which synaptic connections can be reconstructed from spike-train recordings alone remains controversial. Here, we provide a framework to probe and compare connectivity inference algorithms, using a combination of synthetic ground-truth and in vitro data sets, where the connectivity labels were obtained from simultaneous high-density microelectrode array (HD-MEA) and patch-clamp recordings. We find that reconstruction performance critically depends on the regularity of the recorded spontaneous activity, i.e., their dynamical regime, the type of connectivity, and the amount of available spike-train data. We therefore introduce an ensemble artificial neural network (eANN) to improve connectivity inference. We train the eANN on the validated outputs of six established inference algorithms and show how it improves network reconstruction accuracy and robustness. Overall, the eANN demonstrated strong performance across different dynamical regimes, worked well on smaller datasets, and improved the detection of synaptic connectivity, especially inhibitory connections. Results indicated that the eANN also improved the topological characterization of neuronal networks. The presented methodology contributes to advancing the performance of inference algorithms and facilitates our understanding of how neuronal activity relates to synaptic connectivity. Author summary This study introduces an ensemble artificial neural network (eANN) to infer neuronal connectivity from spike times. We benchmark the eANN against existing connectivity inference algorithms and validate it using in silico simulations and in vitro data obtained from parallel high-density microelectrode array (HD-MEA) and patch-clamp recordings. Results demonstrate that the eANN outperforms all other algorithms across different dynamical regimes and provides a more accurate description of the underlying topological organization of the studied networks. Further examinations of the eANN’s output are conducted to identify which input features are most instrumental in achieving this enhanced performance. In sum, the eANN is a promising approach to improve connectivity inference from spike-train data. Close https://dx.plos.org/10.1371/journal.pcbi.1011964 doi:10.1371/journal.pcbi.1011964 Close
	Kesdoğan, Aylin B; Neureiter, Anika; Gaebler, Arnim J; Kalia, Anil K; Körner, Jannis; Lampert, Angelika Analgesic Effect of Botulinum Toxin in Neuropathic Pain is Sodium Channel Independent Journal Article Neuropharmacology, 2024. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, Activity Scan Assay, HD-MEA, IPSC, MaxTwo, MEA Metrics, MEA Technology @article{Kesdoğan2024, title = {Analgesic Effect of Botulinum Toxin in Neuropathic Pain is Sodium Channel Independent}, author = {Aylin B. Kesdoğan and Anika Neureiter and Arnim J. Gaebler and Anil K. Kalia and Jannis Körner and Angelika Lampert }, url = {https://www.sciencedirect.com/science/article/pii/S0028390824001369?via%3Dihub}, doi = {10.1016/j.neuropharm.2024.109967}, year = {2024}, date = {2024-04-23}, journal = {Neuropharmacology}, abstract = {Botulinum neurotoxin type A BoNT/A is used off-label as a third line therapy for neuropathic pain. However, the mechanism of action remains unclear. In recent years, the role of voltage-gated sodium channels (Nav) in neuropathic pain became evident and it was suggested that block of sodium channels by BoNT/A would contribute to its analgesic effect. We assessed sodium channel function in the presence of BoNT/A in heterologously expressed Nav1.7, Nav1.3, and the neuronal cell line ND7/23 by high throughput automated and manual patch-clamp. We used both the full protein and the isolated catalytic light chain LC/A for acute or long-term extracellular or intracellular exposure. To assess the toxin's effect in a human cellular system, we differentiated induced pluripotent stem cells (iPSC) into sensory neurons from a healthy control and a patient suffering from a hereditary neuropathic pain syndrome (inherited erythromelalgia) carrying the Nav1.7/p.Q875E-mutation and carried out multielectrode-array measurements. Both BoNT/A and the isolated catalytic light chain LC/A showed limited effects in heterologous expression systems and the neuronal cell line ND7/23. Spontaneous activity in iPSC derived sensory neurons remained unaltered upon BoNT/A exposure both in neurons from the healthy control and the mutation carrying patient. BoNT/A may not specifically be beneficial in pain syndromes linked to sodium channel variants. The favorable effects of BoNT/A in neuropathic pain are likely based on mechanisms other than sodium channel blockage and new approaches to understand BoNT/A's therapeutic effects are necessary.}, keywords = {2D Neuronal Culture, Activity Scan Assay, HD-MEA, IPSC, MaxTwo, MEA Metrics, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close Botulinum neurotoxin type A BoNT/A is used off-label as a third line therapy for neuropathic pain. However, the mechanism of action remains unclear. In recent years, the role of voltage-gated sodium channels (Nav) in neuropathic pain became evident and it was suggested that block of sodium channels by BoNT/A would contribute to its analgesic effect. We assessed sodium channel function in the presence of BoNT/A in heterologously expressed Nav1.7, Nav1.3, and the neuronal cell line ND7/23 by high throughput automated and manual patch-clamp. We used both the full protein and the isolated catalytic light chain LC/A for acute or long-term extracellular or intracellular exposure. To assess the toxin's effect in a human cellular system, we differentiated induced pluripotent stem cells (iPSC) into sensory neurons from a healthy control and a patient suffering from a hereditary neuropathic pain syndrome (inherited erythromelalgia) carrying the Nav1.7/p.Q875E-mutation and carried out multielectrode-array measurements. Both BoNT/A and the isolated catalytic light chain LC/A showed limited effects in heterologous expression systems and the neuronal cell line ND7/23. Spontaneous activity in iPSC derived sensory neurons remained unaltered upon BoNT/A exposure both in neurons from the healthy control and the mutation carrying patient. BoNT/A may not specifically be beneficial in pain syndromes linked to sodium channel variants. The favorable effects of BoNT/A in neuropathic pain are likely based on mechanisms other than sodium channel blockage and new approaches to understand BoNT/A's therapeutic effects are necessary. Close https://www.sciencedirect.com/science/article/pii/S0028390824001369?via%3Dihub doi:10.1016/j.neuropharm.2024.109967 Close
	van der Molen, Tjitse; Lim, Max; Bartram, Julian; Cheng, Zhuowei; Robbins, Ash; Parks, David F; Petzold, Linda R; Hierlemann, Andreas; Haussler, David; Hansma, Paul K; Tovar, Kenneth R; Kosik, Kenneth S RT-Sort: an action potential propagation-based algorithm for real time spike detection and sorting with millisecond latencies Journal Article bioRxiv, 2024. Abstract \| Links \| BibTeX \| Tags: 3D Culture, Action Potential, closed loop stimulation, HD-MEA, MEA Metrics, MEA Technology, Organoids, Spike Sorting, Stimulation @article{vanderMolen2024, title = {RT-Sort: an action potential propagation-based algorithm for real time spike detection and sorting with millisecond latencies}, author = {Tjitse van der Molen and Max Lim and Julian Bartram and Zhuowei Cheng and Ash Robbins and David F. Parks and Linda R. Petzold and Andreas Hierlemann and David Haussler and Paul K. Hansma and Kenneth R. Tovar and Kenneth S. Kosik}, url = {http://biorxiv.org/lookup/doi/10.1101/2024.04.08.588620}, doi = {10.1101/2024.04.08.588620}, year = {2024}, date = {2024-04-12}, journal = {bioRxiv}, abstract = {With the use of high density multi electrode recording devices, electrophysiological signals resulting from action potentials of individual neurons can now be reliably detected on multiple adjacent recording electrodes both in vivo and in vitro. Spike sorting assigns these signals to putative neural sources. However, until now, spike sorting can only be performed after completion of the recording, preventing true real time usage of spike sorting algorithms. Utilizing the unique propagation patterns of action potentials along axons detected as high fidelity sequential activations on adjacent electrodes, together with a convolutional neural network based spike detection algorithm, we introduce RT-Sort (Real Time Sorting), a spike sorting algorithm that enables the sorted detection of action potentials within 7.5ms±1.5ms (mean±STD) after the waveform trough while the recording remains ongoing. RT-Sort’s true real-time spike sorting capabilities enable closed loop experiments with latencies comparable to synaptic delay times. We show RT-Sort’s performance on both Multi-Electrode Arrays as well as Neuropixels probes to exemplify RT-Sort’s functionality on different types of recording hardware and electrode configurations.}, keywords = {3D Culture, Action Potential, closed loop stimulation, HD-MEA, MEA Metrics, MEA Technology, Organoids, Spike Sorting, Stimulation}, pubstate = {published}, tppubtype = {article} } Close With the use of high density multi electrode recording devices, electrophysiological signals resulting from action potentials of individual neurons can now be reliably detected on multiple adjacent recording electrodes both in vivo and in vitro. Spike sorting assigns these signals to putative neural sources. However, until now, spike sorting can only be performed after completion of the recording, preventing true real time usage of spike sorting algorithms. Utilizing the unique propagation patterns of action potentials along axons detected as high fidelity sequential activations on adjacent electrodes, together with a convolutional neural network based spike detection algorithm, we introduce RT-Sort (Real Time Sorting), a spike sorting algorithm that enables the sorted detection of action potentials within 7.5ms±1.5ms (mean±STD) after the waveform trough while the recording remains ongoing. RT-Sort’s true real-time spike sorting capabilities enable closed loop experiments with latencies comparable to synaptic delay times. We show RT-Sort’s performance on both Multi-Electrode Arrays as well as Neuropixels probes to exemplify RT-Sort’s functionality on different types of recording hardware and electrode configurations. Close http://biorxiv.org/lookup/doi/10.1101/2024.04.08.588620 doi:10.1101/2024.04.08.588620 Close
	Tetzlaff, Svenja K; Reyhan, Ekin; Bengtson, Peter C; Schroers, Julian; Wagner, Julia; Schubert, Marc C; Layer, Nikolas; Puschhof, Maria C; Faymonville, Anton J; Drewa, Nina; Pramatarov, Rangel L; Wissmann, Niklas; Alhalabi, Obada; Heuer, Alina; Sivapalan, Nirosan; Campos, Joaquín; Boztepe, Berin; Scheck, Jonas G; Villa, Giulia; Schröter, Manuel; Sahm, Felix; Forsberg-Nilsson, Karin; Breckwoldt, Michael O; Acuna, Claudio; Suchorska, Bogdana; Heiland, Dieter Henrik; Saez-Rodriguez, Julio; Venkataramani, Varun Characterizing and targeting glioblastoma neuron-tumor networks with retrograde tracing Journal Article bioRxiv, 2024. Abstract \| Links \| BibTeX \| Tags: 3D Culture, HD-MEA, MaxTwo, MEA Metrics, MEA Technology, Organoids, Primary Neuronal Cell Culture @article{Tetzlaff2024, title = {Characterizing and targeting glioblastoma neuron-tumor networks with retrograde tracing}, author = {Svenja K. Tetzlaff and Ekin Reyhan and C. Peter Bengtson and Julian Schroers and Julia Wagner and Marc C. Schubert and Nikolas Layer and Maria C. Puschhof and Anton J. Faymonville and Nina Drewa and Rangel L. Pramatarov and Niklas Wissmann and Obada Alhalabi and Alina Heuer and Nirosan Sivapalan and Joaquín Campos and Berin Boztepe and Jonas G. Scheck and Giulia Villa and Manuel Schröter and Felix Sahm and Karin Forsberg-Nilsson and Michael O. Breckwoldt and Claudio Acuna and Bogdana Suchorska and Dieter Henrik Heiland and Julio Saez-Rodriguez and Varun Venkataramani}, url = {http://biorxiv.org/lookup/doi/10.1101/2024.03.18.585565}, doi = {10.1101/2024.03.18.585565}, year = {2024}, date = {2024-03-22}, journal = {bioRxiv}, abstract = {Glioblastomas are invasive brain tumors with high therapeutic resistance. Neuron-to-glioma synapses have been shown to promote glioblastoma progression. However, a characterization of tumor-connected neurons has been hampered by a lack of technologies. Here, we adapted retrograde tracing using rabies viruses to investigate and manipulate neuron-tumor networks. Glioblastoma rapidly integrated into neural circuits across the brain engaging in widespread functional communication, with acetylcholinergic neurons driving glioblastoma invasion. We uncovered patient-specific and tumor cell state-dependent differences in synaptogenic gene expression associated with neuron-tumor connectivity and subsequent invasivity. Importantly, radiotherapy enhanced neuron-tumor connectivity by increased neuronal activity. In turn, simultaneous neuronal activity inhibition and radiotherapy showed increased therapeutic effects, indicative of a role for neuron-to-glioma synapses in contributing to therapeutic resistance. Lastly, rabies-mediated genetic ablation of tumor-connected neurons halted glioblastoma progression, offering a viral strategy to tackle glioblastoma. Together, this study provides a framework to comprehensively characterize neuron-tumor networks and target glioblastoma.}, keywords = {3D Culture, HD-MEA, MaxTwo, MEA Metrics, MEA Technology, Organoids, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close Glioblastomas are invasive brain tumors with high therapeutic resistance. Neuron-to-glioma synapses have been shown to promote glioblastoma progression. However, a characterization of tumor-connected neurons has been hampered by a lack of technologies. Here, we adapted retrograde tracing using rabies viruses to investigate and manipulate neuron-tumor networks. Glioblastoma rapidly integrated into neural circuits across the brain engaging in widespread functional communication, with acetylcholinergic neurons driving glioblastoma invasion. We uncovered patient-specific and tumor cell state-dependent differences in synaptogenic gene expression associated with neuron-tumor connectivity and subsequent invasivity. Importantly, radiotherapy enhanced neuron-tumor connectivity by increased neuronal activity. In turn, simultaneous neuronal activity inhibition and radiotherapy showed increased therapeutic effects, indicative of a role for neuron-to-glioma synapses in contributing to therapeutic resistance. Lastly, rabies-mediated genetic ablation of tumor-connected neurons halted glioblastoma progression, offering a viral strategy to tackle glioblastoma. Together, this study provides a framework to comprehensively characterize neuron-tumor networks and target glioblastoma. Close http://biorxiv.org/lookup/doi/10.1101/2024.03.18.585565 doi:10.1101/2024.03.18.585565 Close
	Fenton, Timothy A; Haouchine, Olivia Y; Hallam, Elizabeth L; Smith, Emily M; Jackson, Kiya C; Rahbarian, Darlene; Canales, Cesar; Adhikari, Anna; Nord, Alexander S; Ben-Shalom, Roy; Silverman, Jill L Hyperexcitability and translational phenotypes in a preclinical mouse model of SYNGAP1-Related Intellectual Disability Journal Article Research Square, 2024. Abstract \| Links \| BibTeX \| Tags: Activity Scan Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Network Assay, Primary Neuronal Cell Culture, Spike Sorting @article{Fenton2024, title = {Hyperexcitability and translational phenotypes in a preclinical mouse model of SYNGAP1-Related Intellectual Disability}, author = {Timothy A Fenton and Olivia Y Haouchine and Elizabeth L Hallam and Emily M Smith and Kiya C Jackson and Darlene Rahbarian and Cesar Canales and Anna Adhikari and Alexander S Nord and Roy Ben-Shalom and Jill L Silverman}, url = {https://www.researchsquare.com/article/rs-4067746/v1}, doi = {10.21203/rs.3.rs-4067746/v1}, year = {2024}, date = {2024-03-19}, journal = {Research Square}, abstract = {Disruption of SYNGAP1 directly causes a genetically identifiable neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability (SRID). Without functional SynGAP1 protein, individuals are developmentally delayed and have prominent features of intellectual disability, motor impairments, and epilepsy. Over the past two decades, there have been numerous discoveries indicting the critical role of Syngap1. Several rodent models with a loss of Syngap1 have been engineered identifying precise roles in neuronal structure and function, as well as key biochemical pathways key for synapse integrity. Homozygous loss of Syngap1 is lethal. Heterozygous mutations of Syngap1 result in a broad range of behavioral phenotypes. Our in vivo functional data, using the mouse model from the Huganir laboratory, corroborated earlier reported behaviors including robust hyperactivity and deficits in learning and memory in young adults. In extension, we report impairments in slow wave sleep, a critical component of the domain of sleep. We characterized Syngap1+/- mice by using neurophysiology collected with wireless, telemetric electroencephalography (EEG). Syngap1+/- mice also exhibited elevated spiking events and spike trains, in addition to elevated power, most notably in the delta frequency band. For the first time, we illustrated how primary neurons from Syngap1+/- mice function and display increased network firing activity, greater bursts, and shorter inter-burst intervals between peaks by employing high density microelectrode arrays (HD-MEA). Our reported data bridge in-vitro electrophysiological neuronal activity and function with in vivo neurophysiological brain activity and function. These data elucidate quantitative, translational biomarkers in vivo and in vitro that can be utilized for the development of and efficacy assessment of targeted treatments for SRID.}, keywords = {Activity Scan Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Network Assay, Primary Neuronal Cell Culture, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close Disruption of SYNGAP1 directly causes a genetically identifiable neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability (SRID). Without functional SynGAP1 protein, individuals are developmentally delayed and have prominent features of intellectual disability, motor impairments, and epilepsy. Over the past two decades, there have been numerous discoveries indicting the critical role of Syngap1. Several rodent models with a loss of Syngap1 have been engineered identifying precise roles in neuronal structure and function, as well as key biochemical pathways key for synapse integrity. Homozygous loss of Syngap1 is lethal. Heterozygous mutations of Syngap1 result in a broad range of behavioral phenotypes. Our in vivo functional data, using the mouse model from the Huganir laboratory, corroborated earlier reported behaviors including robust hyperactivity and deficits in learning and memory in young adults. In extension, we report impairments in slow wave sleep, a critical component of the domain of sleep. We characterized Syngap1+/- mice by using neurophysiology collected with wireless, telemetric electroencephalography (EEG). Syngap1+/- mice also exhibited elevated spiking events and spike trains, in addition to elevated power, most notably in the delta frequency band. For the first time, we illustrated how primary neurons from Syngap1+/- mice function and display increased network firing activity, greater bursts, and shorter inter-burst intervals between peaks by employing high density microelectrode arrays (HD-MEA). Our reported data bridge in-vitro electrophysiological neuronal activity and function with in vivo neurophysiological brain activity and function. These data elucidate quantitative, translational biomarkers in vivo and in vitro that can be utilized for the development of and efficacy assessment of targeted treatments for SRID. Close https://www.researchsquare.com/article/rs-4067746/v1 doi:10.21203/rs.3.rs-4067746/v1 Close
	Voitiuk, Kateryna; Seiler, Spencer T; de Melo, Mirella Pessoa; Geng, Jinghui; Hernandez, Sebastian; Schweiger, Hunter E; Sevetson, Jess L; Parks, David F; Robbins, Ash; Torres-Montoya, Sebastian; Ehrlich, Drew; Elliott, Matthew A T; Sharf, Tal; Haussler, David; Mostajo-Radji, Mohammed A; Salama, Sofie R; Teodorescu, Mircea A feedback-driven IoT microfluidic, electrophysiology, and imaging platform for brain organoid studies Journal Article bioRxiv, 2024. Abstract \| Links \| BibTeX \| Tags: Activity Scan Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Microfluidics, Organoids @article{Voitiuk2024, title = {A feedback-driven IoT microfluidic, electrophysiology, and imaging platform for brain organoid studies}, author = {Kateryna Voitiuk and Spencer T. Seiler and Mirella Pessoa de Melo and Jinghui Geng and Sebastian Hernandez and Hunter E. Schweiger and Jess L. Sevetson and David F. Parks and Ash Robbins and Sebastian Torres-Montoya and Drew Ehrlich and Matthew A.T. Elliott and Tal Sharf and David Haussler and Mohammed A. Mostajo-Radji and Sofie R. Salama and Mircea Teodorescu}, url = {http://biorxiv.org/lookup/doi/10.1101/2024.03.15.585237}, doi = {10.1101/2024.03.15.585237}, year = {2024}, date = {2024-03-17}, journal = {bioRxiv}, abstract = {The analysis of tissue cultures, particularly brain organoids, takes a high degree of coordination, measurement, and monitoring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Unified by an Internet of Things (IoT) architecture, our approach enables continuous, communicative interactions among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids and monitor their neuronal activity. The organoids are cultured in custom, 3D-printed chambers attached to commercial microelectrode arrays for electrophysiology monitoring. Periodic feeding is achieved using programmable microfluidic pumps. We developed computer vision fluid volume estimations of aspirated media, achieving high accuracy, and used feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a 7-day study of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated experimental samples maintained robust neural activity throughout the experiment, comparable with the control samples. The automated system enabled hourly electrophysiology recordings that revealed dramatic temporal changes in neuron firing rates not observed in once-a-day recordings. One-Sentence Summary: An IoT laboratory robotics system that enables touch-free feeding, imaging, and electrophysiology of brain organoids.}, keywords = {Activity Scan Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Microfluidics, Organoids}, pubstate = {published}, tppubtype = {article} } Close The analysis of tissue cultures, particularly brain organoids, takes a high degree of coordination, measurement, and monitoring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Unified by an Internet of Things (IoT) architecture, our approach enables continuous, communicative interactions among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids and monitor their neuronal activity. The organoids are cultured in custom, 3D-printed chambers attached to commercial microelectrode arrays for electrophysiology monitoring. Periodic feeding is achieved using programmable microfluidic pumps. We developed computer vision fluid volume estimations of aspirated media, achieving high accuracy, and used feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a 7-day study of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated experimental samples maintained robust neural activity throughout the experiment, comparable with the control samples. The automated system enabled hourly electrophysiology recordings that revealed dramatic temporal changes in neuron firing rates not observed in once-a-day recordings. One-Sentence Summary: An IoT laboratory robotics system that enables touch-free feeding, imaging, and electrophysiology of brain organoids. Close http://biorxiv.org/lookup/doi/10.1101/2024.03.15.585237 doi:10.1101/2024.03.15.585237 Close
	Kasuba, Krishna Chaitanya; Buccino, Alessio Paolo; Bartram, Julian; Gaub, Benjamin M; Fauser, Felix J; Ronchi, Silvia; Kumar, Sreedhar Saseendran; Geissler, Sydney; Nava, Michele M; Hierlemann, Andreas; Müller, Daniel J Mechanical stimulation and electrophysiological monitoring at subcellular resolution reveals differential mechanosensation of neurons within networks Journal Article Nature Nanotechnology, 2024. Abstract \| Links \| BibTeX \| Tags: Action Potential, Brain Slice, HD-MEA, MaxOne, Primary Neuronal Cell Culture, Spike Sorting @article{Kasuba2024, title = {Mechanical stimulation and electrophysiological monitoring at subcellular resolution reveals differential mechanosensation of neurons within networks}, author = {Krishna Chaitanya Kasuba and Alessio Paolo Buccino and Julian Bartram and Benjamin M. Gaub and Felix J. Fauser and Silvia Ronchi and Sreedhar Saseendran Kumar and Sydney Geissler and Michele M. Nava and Andreas Hierlemann and Daniel J. Müller }, url = {https://www.nature.com/articles/s41565-024-01609-1}, doi = {10.1038/s41565-024-01609-1}, year = {2024}, date = {2024-02-20}, journal = {Nature Nanotechnology}, abstract = {A growing consensus that the brain is a mechanosensitive organ is driving the need for tools that mechanically stimulate and simultaneously record the electrophysiological response of neurons within neuronal networks. Here we introduce a synchronized combination of atomic force microscopy, high-density microelectrode array and fluorescence microscopy to monitor neuronal networks and to mechanically characterize and stimulate individual neurons at piconewton force sensitivity and nanometre precision while monitoring their electrophysiological activity at subcellular spatial and millisecond temporal resolution. No correlation is found between mechanical stiffness and electrophysiological activity of neuronal compartments. Furthermore, spontaneously active neurons show exceptional functional resilience to static mechanical compression of their soma. However, application of fast transient (∼500 ms) mechanical stimuli to the neuronal soma can evoke action potentials, which depend on the anchoring of neuronal membrane and actin cytoskeleton. Neurons show higher responsivity, including bursts of action potentials, to slower transient mechanical stimuli (∼60 s). Moreover, transient and repetitive application of the same compression modulates the neuronal firing rate. Seemingly, neuronal networks can differentiate and respond to specific characteristics of mechanical stimulation. Ultimately, the developed multiparametric tool opens the door to explore manifold nanomechanobiological responses of neuronal systems and new ways of mechanical control.}, keywords = {Action Potential, Brain Slice, HD-MEA, MaxOne, Primary Neuronal Cell Culture, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close A growing consensus that the brain is a mechanosensitive organ is driving the need for tools that mechanically stimulate and simultaneously record the electrophysiological response of neurons within neuronal networks. Here we introduce a synchronized combination of atomic force microscopy, high-density microelectrode array and fluorescence microscopy to monitor neuronal networks and to mechanically characterize and stimulate individual neurons at piconewton force sensitivity and nanometre precision while monitoring their electrophysiological activity at subcellular spatial and millisecond temporal resolution. No correlation is found between mechanical stiffness and electrophysiological activity of neuronal compartments. Furthermore, spontaneously active neurons show exceptional functional resilience to static mechanical compression of their soma. However, application of fast transient (∼500 ms) mechanical stimuli to the neuronal soma can evoke action potentials, which depend on the anchoring of neuronal membrane and actin cytoskeleton. Neurons show higher responsivity, including bursts of action potentials, to slower transient mechanical stimuli (∼60 s). Moreover, transient and repetitive application of the same compression modulates the neuronal firing rate. Seemingly, neuronal networks can differentiate and respond to specific characteristics of mechanical stimulation. Ultimately, the developed multiparametric tool opens the door to explore manifold nanomechanobiological responses of neuronal systems and new ways of mechanical control. Close https://www.nature.com/articles/s41565-024-01609-1 doi:10.1038/s41565-024-01609-1 Close
	Hruska-Plochan, Marian; Wiersma, Vera I; Betz, Katharina M; Mallona, Izaskun; Ronchi, Silvia; Maniecka, Zuzanna; Hock, Eva-Maria; Tantardini, Elena; Laferriere, Florent; Sahadevan, Sonu; Hoop, Vanessa; Delvendahl, Igor; Pérez-Berlanga, Manuela; Gatta, Beatrice; Panatta, Martina; van der Bourg, Alexander; Bohaciakova, Dasa; Sharma, Puneet; Vos, Laura De; Frontzek, Karl; Aguzzi, Adriano; Lashley, Tammaryn; Robinson, Mark D; Karayannis, Theofanis; Mueller, Martin; Hierlemann, Andreas; Polymenidou, Magdalini A model of human neural networks reveals NPTX2 pathology in ALS and FTLD Journal Article Nature, 2024. Abstract \| Links \| BibTeX \| Tags: Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Network Assay, Primary Neuronal Cell Culture, Spike Sorting @article{Hruska-Plochan2024, title = {A model of human neural networks reveals NPTX2 pathology in ALS and FTLD}, author = {Marian Hruska-Plochan and Vera I. Wiersma and Katharina M. Betz and Izaskun Mallona and Silvia Ronchi and Zuzanna Maniecka and Eva-Maria Hock and Elena Tantardini and Florent Laferriere and Sonu Sahadevan and Vanessa Hoop and Igor Delvendahl and Manuela Pérez-Berlanga and Beatrice Gatta and Martina Panatta and Alexander van der Bourg and Dasa Bohaciakova and Puneet Sharma and Laura De Vos and Karl Frontzek and Adriano Aguzzi and Tammaryn Lashley and Mark D. Robinson and Theofanis Karayannis and Martin Mueller and Andreas Hierlemann and Magdalini Polymenidou }, url = {https://www.nature.com/articles/s41586-024-07042-7}, doi = {10.1038/s41586-024-07042-7}, year = {2024}, date = {2024-02-14}, journal = {Nature}, abstract = {Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1, which involve human-specific mechanisms that cannot be directly studied in animal models. Here, to explore the emergence and consequences of TDP-43 pathologies, we generated induced pluripotent stem cell-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors. Single-cell transcriptomics and comparison to independent neural stem cells showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks (which we designate iNets). Neuronal and glial maturation in iNets was similar to that of cortical organoids. Overexpression of wild-type TDP-43 in a minority of neurons within iNets led to progressive fragmentation and aggregation of the protein, resulting in a partial loss of function and neurotoxicity. Single-cell transcriptomics revealed a novel set of misregulated RNA targets in TDP-43-overexpressing neurons and in patients with TDP-43 proteinopathies exhibiting a loss of nuclear TDP-43. The strongest misregulated target encoded the synaptic protein NPTX2, the levels of which are controlled by TDP-43 binding on its 3′ untranslated region. When NPTX2 was overexpressed in iNets, it exhibited neurotoxicity, whereas correcting NPTX2 misregulation partially rescued neurons from TDP-43-induced neurodegeneration. Notably, NPTX2 was consistently misaccumulated in neurons from patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby revealing a TDP-43-dependent pathway of neurotoxicity.}, keywords = {Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Network Assay, Primary Neuronal Cell Culture, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1, which involve human-specific mechanisms that cannot be directly studied in animal models. Here, to explore the emergence and consequences of TDP-43 pathologies, we generated induced pluripotent stem cell-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors. Single-cell transcriptomics and comparison to independent neural stem cells showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks (which we designate iNets). Neuronal and glial maturation in iNets was similar to that of cortical organoids. Overexpression of wild-type TDP-43 in a minority of neurons within iNets led to progressive fragmentation and aggregation of the protein, resulting in a partial loss of function and neurotoxicity. Single-cell transcriptomics revealed a novel set of misregulated RNA targets in TDP-43-overexpressing neurons and in patients with TDP-43 proteinopathies exhibiting a loss of nuclear TDP-43. The strongest misregulated target encoded the synaptic protein NPTX2, the levels of which are controlled by TDP-43 binding on its 3′ untranslated region. When NPTX2 was overexpressed in iNets, it exhibited neurotoxicity, whereas correcting NPTX2 misregulation partially rescued neurons from TDP-43-induced neurodegeneration. Notably, NPTX2 was consistently misaccumulated in neurons from patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby revealing a TDP-43-dependent pathway of neurotoxicity. Close https://www.nature.com/articles/s41586-024-07042-7 doi:10.1038/s41586-024-07042-7 Close
	Wang, Guodong; Zhang, Dandan; Qin, Liangshan; Liu, Quanhui; Tang, Wenkui; Liu, Mingxing; Xu, Fan; Tang, Fen; Cheng, Leping; Mo, Huiming; Yuan, Xiang; Wang, Zhiqiang; Huang, Ben Forskolin-driven conversion of human somatic cells into induced neurons through regulation of the cAMP-CREB1-JNK signaling Journal Article Theranostics , 2024. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology @article{Wang2024, title = {Forskolin-driven conversion of human somatic cells into induced neurons through regulation of the cAMP-CREB1-JNK signaling}, author = {Guodong Wang and Dandan Zhang and Liangshan Qin and Quanhui Liu and Wenkui Tang and Mingxing Liu and Fan Xu and Fen Tang and Leping Cheng and Huiming Mo and Xiang Yuan and Zhiqiang Wang and Ben Huang}, url = {https://www.thno.org/v14p1701.htm}, doi = {10.7150/thno.92700}, year = {2024}, date = {2024-02-11}, journal = {Theranostics }, abstract = {Human somatic cells can be reprogrammed into neuron cell fate through regulation of a single transcription factor or application of small molecule cocktails. Methods: Here, we report that forskolin efficiently induces the conversion of human somatic cells into induced neurons (FiNs). Results: A large population of neuron-like phenotype cells was observed as early as 24-36 h post-induction. There were >90% TUJ1-, >80% MAP2-, and >80% NEUN-positive neurons at 5 days post-induction. Multiple subtypes of neurons were present among TUJ1-positive cells, including >60% cholinergic, >20% glutamatergic, >10% GABAergic, and >5% dopaminergic neurons. FiNs exhibited typical neural electrophysiological activity in vitro and the ability to survive in vitro and in vivo more than 2 months. Mechanistically, forskolin functions in FiN reprogramming by regulating the cAMP-CREB1-JNK signals, which upregulates cAMP-CREB1 expression and downregulates JNK expression. Conclusion: Overall, our studies identify a safer and efficient single-small-molecule-driven reprogramming approach for induced neuron generation and reveal a novel regulatory mechanism of neuronal cell fate acquisition.}, keywords = {2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close Human somatic cells can be reprogrammed into neuron cell fate through regulation of a single transcription factor or application of small molecule cocktails. Methods: Here, we report that forskolin efficiently induces the conversion of human somatic cells into induced neurons (FiNs). Results: A large population of neuron-like phenotype cells was observed as early as 24-36 h post-induction. There were >90% TUJ1-, >80% MAP2-, and >80% NEUN-positive neurons at 5 days post-induction. Multiple subtypes of neurons were present among TUJ1-positive cells, including >60% cholinergic, >20% glutamatergic, >10% GABAergic, and >5% dopaminergic neurons. FiNs exhibited typical neural electrophysiological activity in vitro and the ability to survive in vitro and in vivo more than 2 months. Mechanistically, forskolin functions in FiN reprogramming by regulating the cAMP-CREB1-JNK signals, which upregulates cAMP-CREB1 expression and downregulates JNK expression. Conclusion: Overall, our studies identify a safer and efficient single-small-molecule-driven reprogramming approach for induced neuron generation and reveal a novel regulatory mechanism of neuronal cell fate acquisition. Close https://www.thno.org/v14p1701.htm doi:10.7150/thno.92700 Close
	Hornauer, Philipp; Prack, Gustavo; Anastasi, Nadia; Ronchi, Silvia; Kim, Taehoon; Donner, Christian; Fiscella, Michele; Borgwardt, Karsten; Taylor, Verdon; Jagasia, Ravi; Roqueiro, Damian; Hierlemann, Andreas; Schröter, Manuel DeePhys: A machine learning–assisted platform for electrophysiological phenotyping of human neuronal networks Journal Article Stem Cell Reports, 2024. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Technology, Spike Sorting @article{Hornauer2024, title = {DeePhys: A machine learning–assisted platform for electrophysiological phenotyping of human neuronal networks}, author = {Philipp Hornauer and Gustavo Prack and Nadia Anastasi and Silvia Ronchi and Taehoon Kim and Christian Donner and Michele Fiscella and Karsten Borgwardt and Verdon Taylor and Ravi Jagasia and Damian Roqueiro and Andreas Hierlemann and Manuel Schröter}, url = {https://www.sciencedirect.com/science/article/pii/S2213671123005015}, doi = {10.1016/j.stemcr.2023.12.008}, year = {2024}, date = {2024-01-25}, journal = {Stem Cell Reports}, abstract = {Reproducible functional assays to study in vitro neuronal networks represent an important cornerstone in the quest to develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven functional phenotyping of in vitro neuronal cultures recorded by high-density microelectrode arrays. DeePhys is a modular workflow that offers a range of techniques to extract features from spike-sorted data, allowing for the examination of functional phenotypes both at the individual cell and network levels, as well as across development. In addition, DeePhys incorporates the capability to integrate novel features and to use machine-learning-assisted approaches, which facilitates a comprehensive evaluation of pharmacological interventions. To illustrate its practical application, we apply DeePhys to human induced pluripotent stem cell–derived dopaminergic neurons obtained from both patients and healthy individuals and showcase how DeePhys enables phenotypic screenings.}, keywords = {2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Technology, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close Reproducible functional assays to study in vitro neuronal networks represent an important cornerstone in the quest to develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven functional phenotyping of in vitro neuronal cultures recorded by high-density microelectrode arrays. DeePhys is a modular workflow that offers a range of techniques to extract features from spike-sorted data, allowing for the examination of functional phenotypes both at the individual cell and network levels, as well as across development. In addition, DeePhys incorporates the capability to integrate novel features and to use machine-learning-assisted approaches, which facilitates a comprehensive evaluation of pharmacological interventions. To illustrate its practical application, we apply DeePhys to human induced pluripotent stem cell–derived dopaminergic neurons obtained from both patients and healthy individuals and showcase how DeePhys enables phenotypic screenings. Close https://www.sciencedirect.com/science/article/pii/S2213671123005015 doi:10.1016/j.stemcr.2023.12.008 Close
2023
	van der Molen, Tjitse; Spaeth, Alex; Chini, Mattia; Bartram, Julian; Dendukuri, Aditya; Zhang, Zongren; Bhaskaran-Nair, Kiran; Blauvelt, Lon J; Petzold, Linda R; Hansma, Paul K; Teodorescu, Mircea; Hierlemann, Andreas; Hengen, Keith B; Hanganu-Opatz, Ileana L; Kosik, Kenneth S; Sharf, Tal Protosequences in human cortical organoids model intrinsic states in the developing cortex Journal Article bioRxiv, 2023. Abstract \| Links \| BibTeX \| Tags: MaxOne, Organoids @article{Molen2023, title = {Protosequences in human cortical organoids model intrinsic states in the developing cortex}, author = {Tjitse van der Molen and Alex Spaeth and Mattia Chini and Julian Bartram and Aditya Dendukuri and Zongren Zhang and Kiran Bhaskaran-Nair and Lon J. Blauvelt and Linda R. Petzold and Paul K. Hansma and Mircea Teodorescu and Andreas Hierlemann and Keith B. Hengen and Ileana L. Hanganu-Opatz and Kenneth S. Kosik and Tal Sharf}, url = {https://www.biorxiv.org/content/10.1101/2023.12.29.573646v1}, doi = {10.1101/2023.12.29.573646}, year = {2023}, date = {2023-12-30}, journal = {bioRxiv}, abstract = {Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development.}, keywords = {MaxOne, Organoids}, pubstate = {published}, tppubtype = {article} } Close Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development. Close https://www.biorxiv.org/content/10.1101/2023.12.29.573646v1 doi:10.1101/2023.12.29.573646 Close
	Cai, Hongwei; Ao, Zheng; Tian, Chunhui; Wu, Zhuhao; Liu, Hongcheng; Tchieu, Jason; Gu, Mingxia; Mackie, Ken; Guo, Feng Brain organoid reservoir computing for artificial intelligence Journal Article Nature Electronics, 2023. Abstract \| Links \| BibTeX \| Tags: 3D Culture, HD-MEA, Machine Learning, MaxOne, MEA Technology, Organoids, Stimulation @article{Cai2023b, title = {Brain organoid reservoir computing for artificial intelligence}, author = {Hongwei Cai and Zheng Ao and Chunhui Tian and Zhuhao Wu and Hongcheng Liu and Jason Tchieu and Mingxia Gu and Ken Mackie and Feng Guo }, url = {https://www.nature.com/articles/s41928-023-01069-w}, doi = {10.1038/s41928-023-01069-w}, year = {2023}, date = {2023-12-11}, journal = {Nature Electronics}, abstract = {Brain-inspired computing hardware aims to emulate the structure and working principles of the brain and could be used to address current limitations in artificial intelligence technologies. However, brain-inspired silicon chips are still limited in their ability to fully mimic brain function as most examples are built on digital electronic principles. Here we report an artificial intelligence hardware approach that uses adaptive reservoir computation of biological neural networks in a brain organoid. In this approach—which is termed Brainoware—computation is performed by sending and receiving information from the brain organoid using a high-density multielectrode array. By applying spatiotemporal electrical stimulation, nonlinear dynamics and fading memory properties are achieved, as well as unsupervised learning from training data by reshaping the organoid functional connectivity. We illustrate the practical potential of this technique by using it for speech recognition and nonlinear equation prediction in a reservoir computing framework.}, keywords = {3D Culture, HD-MEA, Machine Learning, MaxOne, MEA Technology, Organoids, Stimulation}, pubstate = {published}, tppubtype = {article} } Close Brain-inspired computing hardware aims to emulate the structure and working principles of the brain and could be used to address current limitations in artificial intelligence technologies. However, brain-inspired silicon chips are still limited in their ability to fully mimic brain function as most examples are built on digital electronic principles. Here we report an artificial intelligence hardware approach that uses adaptive reservoir computation of biological neural networks in a brain organoid. In this approach—which is termed Brainoware—computation is performed by sending and receiving information from the brain organoid using a high-density multielectrode array. By applying spatiotemporal electrical stimulation, nonlinear dynamics and fading memory properties are achieved, as well as unsupervised learning from training data by reshaping the organoid functional connectivity. We illustrate the practical potential of this technique by using it for speech recognition and nonlinear equation prediction in a reservoir computing framework. Close https://www.nature.com/articles/s41928-023-01069-w doi:10.1038/s41928-023-01069-w Close
	Ryu, Seungmi; Weber, Claire; Chu, Pei-Hsuan; Ernest, Ben; Jovanovic, Vukasin M; Deng, Tao; Slamecka, Jaroslav; Hong, Hyenjong; Jethmalani, Yogita; Baskir, Hannah M; Inman, Jason; Braisted, John; Hirst, Marissa B; Simeonov, Anton; Voss, Ty C; Tristan, Carlos A; Singeç, Ilyas Stress-free cell aggregation by using the CEPT cocktail enhances embryoid body and organoid fitness Journal Article Biofabrication, 2023. Abstract \| Links \| BibTeX \| Tags: 3D Culture, Activity Scan Assay, HD-MEA, MEA Technology, Organoids @article{Ryu2023, title = {Stress-free cell aggregation by using the CEPT cocktail enhances embryoid body and organoid fitness}, author = {Seungmi Ryu and Claire Weber and Pei-Hsuan Chu and Ben Ernest and Vukasin M Jovanovic and Tao Deng and Jaroslav Slamecka and Hyenjong Hong and Yogita Jethmalani and Hannah M Baskir and Jason Inman and John Braisted and Marissa B Hirst and Anton Simeonov and Ty C Voss and Carlos A Tristan and Ilyas Singeç}, url = {https://dx.doi.org/10.1088/1758-5090/ad0d13}, doi = {10.1088/1758-5090/ad0d13}, year = {2023}, date = {2023-12-11}, journal = {Biofabrication}, abstract = {Embryoid bodies (EBs) and self-organizing organoids derived from human pluripotent stem cells (hPSCs) recapitulate tissue development in a dish and hold great promise for disease modeling and drug development. However, current protocols are hampered by cellular stress and apoptosis during cell aggregation, resulting in variability and impaired cell differentiation. Here, we demonstrate that EBs and various organoid models (e.g., brain, gut, kidney) can be optimized by using the small molecule cocktail named CEPT (chroman 1, emricasan, polyamines, trans-ISRIB), a polypharmacological approach that ensures cytoprotection and cell survival. Application of CEPT for just 24 h during cell aggregation has long-lasting consequences affecting morphogenesis, gene expression, cellular differentiation, and organoid function. Various qualification methods confirmed that CEPT treatment enhanced experimental reproducibility and consistently improved EB and organoid fitness as compared to the widely used ROCK inhibitor Y-27632. Collectively, we discovered that stress-free cell aggregation and superior cell survival in the presence of CEPT are critical quality control determinants that establish a robust foundation for bioengineering complex tissue and organ models.}, keywords = {3D Culture, Activity Scan Assay, HD-MEA, MEA Technology, Organoids}, pubstate = {published}, tppubtype = {article} } Close Embryoid bodies (EBs) and self-organizing organoids derived from human pluripotent stem cells (hPSCs) recapitulate tissue development in a dish and hold great promise for disease modeling and drug development. However, current protocols are hampered by cellular stress and apoptosis during cell aggregation, resulting in variability and impaired cell differentiation. Here, we demonstrate that EBs and various organoid models (e.g., brain, gut, kidney) can be optimized by using the small molecule cocktail named CEPT (chroman 1, emricasan, polyamines, trans-ISRIB), a polypharmacological approach that ensures cytoprotection and cell survival. Application of CEPT for just 24 h during cell aggregation has long-lasting consequences affecting morphogenesis, gene expression, cellular differentiation, and organoid function. Various qualification methods confirmed that CEPT treatment enhanced experimental reproducibility and consistently improved EB and organoid fitness as compared to the widely used ROCK inhibitor Y-27632. Collectively, we discovered that stress-free cell aggregation and superior cell survival in the presence of CEPT are critical quality control determinants that establish a robust foundation for bioengineering complex tissue and organ models. Close https://dx.doi.org/10.1088/1758-5090/ad0d13 Close
	Friston, Karl J; Salvatori, Tommaso; Isomura, Takuya; Tschantz, Alexander; Kiefer, Alex; Verbelen, Tim; Koudahl, Magnus; Paul, Aswin; Parr, Thomas; Razi, Adeel; Kagan, Brett; Buckley, Christopher L; and Ramstead, Maxwell J D Active Inference and Intentional Behaviour Journal Article arXiv, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Technology, Stimulation @article{Friston2023, title = {Active Inference and Intentional Behaviour}, author = {Karl J. Friston and Tommaso Salvatori and Takuya Isomura and Alexander Tschantz and Alex Kiefer and Tim Verbelen and Magnus Koudahl and Aswin Paul and Thomas Parr and Adeel Razi and Brett Kagan and Christopher L. Buckley and and Maxwell J. D. Ramstead}, url = {http://arxiv.org/abs/2312.07547}, doi = {10.48550/arXiv.2312.07547}, year = {2023}, date = {2023-12-06}, journal = {arXiv}, abstract = {Recent advances in theoretical biology suggest that basal cognition and sentient behaviour are emergent properties of in vitro cell cultures and neuronal networks, respectively. Such neuronal networks spontaneously learn structured behaviours in the absence of reward or reinforcement. In this paper, we characterise this kind of selforganisation through the lens of the free energy principle, i.e., as self-evidencing. We do this by first discussing the definitions of reactive and sentient behaviour in the setting of active inference, which describes the behaviour of agents that model the consequences of their actions. We then introduce a formal account of intentional behaviour, that describes agents as driven by a preferred endpoint or goal in latent state-spaces. We then investigate these forms of (reactive, sentient, and intentional) behaviour using simulations. First, we simulate the aforementioned in vitro experiments, in which neuronal cultures spontaneously learn to play Pong, by implementing nested, free energy minimising processes. The simulations are then used to deconstruct the ensuing predictive behaviour—leading to the distinction between merely reactive, sentient, and intentional behaviour, with the latter formalised in terms of inductive planning. This distinction is further studied using simple machine learning benchmarks (navigation in a grid world and the Tower of Hanoi problem), that show how quickly and efficiently adaptive behaviour emerges under an inductive form of active inference.}, keywords = {2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Technology, Stimulation}, pubstate = {published}, tppubtype = {article} } Close Recent advances in theoretical biology suggest that basal cognition and sentient behaviour are emergent properties of in vitro cell cultures and neuronal networks, respectively. Such neuronal networks spontaneously learn structured behaviours in the absence of reward or reinforcement. In this paper, we characterise this kind of selforganisation through the lens of the free energy principle, i.e., as self-evidencing. We do this by first discussing the definitions of reactive and sentient behaviour in the setting of active inference, which describes the behaviour of agents that model the consequences of their actions. We then introduce a formal account of intentional behaviour, that describes agents as driven by a preferred endpoint or goal in latent state-spaces. We then investigate these forms of (reactive, sentient, and intentional) behaviour using simulations. First, we simulate the aforementioned in vitro experiments, in which neuronal cultures spontaneously learn to play Pong, by implementing nested, free energy minimising processes. The simulations are then used to deconstruct the ensuing predictive behaviour—leading to the distinction between merely reactive, sentient, and intentional behaviour, with the latter formalised in terms of inductive planning. This distinction is further studied using simple machine learning benchmarks (navigation in a grid world and the Tower of Hanoi problem), that show how quickly and efficiently adaptive behaviour emerges under an inductive form of active inference. Close http://arxiv.org/abs/2312.07547 doi:10.48550/arXiv.2312.07547 Close
	Elliott, Matthew A T; Schweiger, Hunter E; Robbins, Ash; Vera-Choqqueccota, Samira; Ehrlich, Drew; Hernandez, Sebastian; Voitiuk, Kateryna; Geng, Jinghui; Sevetson, Jess L; Core, Cordero; Rosen, Yohei M; Teodorescu, Mircea; Wagner, Nico O; Haussler, David; Mostajo-Radji, Mohammed A Internet-Connected Cortical Organoids for Project-Based Stem Cell and Neuroscience Education Journal Article eNeuro, 2023. Abstract \| Links \| BibTeX \| Tags: 3D Culture, Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Organoids, Spike Sorting, Stimulation @article{Elliott2023, title = {Internet-Connected Cortical Organoids for Project-Based Stem Cell and Neuroscience Education}, author = {Matthew A. T. Elliott and Hunter E. Schweiger and Ash Robbins and Samira Vera-Choqqueccota and Drew Ehrlich and Sebastian Hernandez and Kateryna Voitiuk and Jinghui Geng and Jess L. Sevetson and Cordero Core and Yohei M. Rosen and Mircea Teodorescu and Nico O. Wagner and David Haussler and Mohammed A. Mostajo-Radji}, url = {https://www.eneuro.org/lookup/doi/10.1523/ENEURO.0308-23.2023}, doi = {10.1523/ENEURO.0308-23.2023}, year = {2023}, date = {2023-11-28}, journal = {eNeuro}, abstract = {The introduction of Internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell (PSC)-derived cortical organoids in two different settings: using microscopy to monitor organoid growth in an introductory tissue culture course and using high-density (HD) multielectrode arrays (MEAs) to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training.}, keywords = {3D Culture, Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Organoids, Spike Sorting, Stimulation}, pubstate = {published}, tppubtype = {article} } Close The introduction of Internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell (PSC)-derived cortical organoids in two different settings: using microscopy to monitor organoid growth in an introductory tissue culture course and using high-density (HD) multielectrode arrays (MEAs) to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training. Close https://www.eneuro.org/lookup/doi/10.1523/ENEURO.0308-23.2023 doi:10.1523/ENEURO.0308-23.2023 Close
	Kobayashi, Toki; Shimba, Kenta; Kotani, Kiyoshi; Jimbo, Yasuhiko Measuring and Inducing the Plasticity of Single-Neuron Scale at Multiple Points Conference ISSS Xplore, 2023. Abstract \| Links \| BibTeX \| Tags: HD-MEA, MaxOne, Primary Neuronal Cell Culture, Stimulation @conference{Kobayashi2023, title = {Measuring and Inducing the Plasticity of Single-Neuron Scale at Multiple Points}, author = {Toki Kobayashi and Kenta Shimba and Kiyoshi Kotani and Yasuhiko Jimbo}, url = {https://ieeexplore.ieee.org/abstract/document/10322076}, doi = {10.1109/BMEiCON60347.2023.10322076}, year = {2023}, date = {2023-11-22}, journal = {IEEE Xplore}, publisher = {ISSS Xplore}, abstract = {Information processing in the brain is supported by the plasticity of the connections of neurons in biological neuronal networks. There is a gap between our understanding on plasticity of individual connections and that of the neuronal networks. Here, we aimed to induce and measure plasticity at the connections of individual neurons and at the network level. We achieved inducing plasticity with a combination of single cell stimulation by optogenetics and high-resolution extracellular potentials recording by high-density microelectrode array. Spike timing plasticity in a single neuron was successfully measured. Although we also tried to induce synaptic potentiation by tetanus stimulation, no significant change was observed. In the future, we will investigate how the plasticity of individual connections changes dynamics of entire network.}, keywords = {HD-MEA, MaxOne, Primary Neuronal Cell Culture, Stimulation}, pubstate = {published}, tppubtype = {conference} } Close Information processing in the brain is supported by the plasticity of the connections of neurons in biological neuronal networks. There is a gap between our understanding on plasticity of individual connections and that of the neuronal networks. Here, we aimed to induce and measure plasticity at the connections of individual neurons and at the network level. We achieved inducing plasticity with a combination of single cell stimulation by optogenetics and high-resolution extracellular potentials recording by high-density microelectrode array. Spike timing plasticity in a single neuron was successfully measured. Although we also tried to induce synaptic potentiation by tetanus stimulation, no significant change was observed. In the future, we will investigate how the plasticity of individual connections changes dynamics of entire network. Close https://ieeexplore.ieee.org/abstract/document/10322076 doi:10.1109/BMEiCON60347.2023.10322076 Close
	Tamatani, Chie; Shimba, Kenta; andYasuhiko Jimbo, Kiyoshi Kotani Activity- and Spatial-dependent Variations in Axonal Conduction Recorded from Microtunnel Electrodes Conference IEEE Xplore, 2023. Abstract \| Links \| BibTeX \| Tags: HD-MEA, MaxOne @conference{Tamatani2023, title = {Activity- and Spatial-dependent Variations in Axonal Conduction Recorded from Microtunnel Electrodes}, author = {Chie Tamatani and Kenta Shimba and Kiyoshi Kotani andYasuhiko Jimbo }, url = {https://ieeexplore.ieee.org/abstract/document/10321980}, doi = {10.1109/BMEiCON60347.2023.10321980}, year = {2023}, date = {2023-11-22}, publisher = {IEEE Xplore}, abstract = {Axons are not simple transmission cables in neuronal networks, but they are directly involved in information processing. We developed a novel culture device that aims to assess axonal conduction properties. The microdevice consists of microtunnels directly fabricated on high-density microelectrode array. Neuron growth and axon isolation were confirmed by immunofluorescent staining and neural activity recording. Several dozens of electrodes were detected from each tunnel and signals had enough S/N ratio to handle each spike event. Activity- and spatial-dependent variations in conduction velocity were observed. These results suggest that our microdevice is feasible to study axonal information processing.}, keywords = {HD-MEA, MaxOne}, pubstate = {published}, tppubtype = {conference} } Close Axons are not simple transmission cables in neuronal networks, but they are directly involved in information processing. We developed a novel culture device that aims to assess axonal conduction properties. The microdevice consists of microtunnels directly fabricated on high-density microelectrode array. Neuron growth and axon isolation were confirmed by immunofluorescent staining and neural activity recording. Several dozens of electrodes were detected from each tunnel and signals had enough S/N ratio to handle each spike event. Activity- and spatial-dependent variations in conduction velocity were observed. These results suggest that our microdevice is feasible to study axonal information processing. Close https://ieeexplore.ieee.org/abstract/document/10321980 doi:10.1109/BMEiCON60347.2023.10321980 Close
	Sawada, Tomoyo; Barbosa, André R; Araujo, Bruno; McCord, Alejandra E; D’Ignazio, Laura; Benjamin, Kynon J M; Sheehan, Bonna; Zabolocki, Michael; Feltrin, Arthur; Arora, Ria; Brandtjen, Anna C; Kleinman, Joel E; Hyde, Thomas M; Bardy, Cedric; Weinberger, Daniel R; Paquola, Apuã C M; Erwin, Jennifer A Recapitulation of Perturbed Striatal Gene Expression Dynamics of Donor’s Brains With Ventral Forebrain Organoids Derived From the Same Individuals With Schizophrenia Journal Article American Journal of Psychiatry, 2023, ISSN: 0002-953X. Abstract \| Links \| BibTeX \| Tags: 3D Culture, Activity Scan Assay, HD-MEA, MaxTwo, Network Assay, Organoids @article{Tomoyo2023, title = {Recapitulation of Perturbed Striatal Gene Expression Dynamics of Donor’s Brains With Ventral Forebrain Organoids Derived From the Same Individuals With Schizophrenia}, author = {Tomoyo Sawada and André R. Barbosa and Bruno Araujo and Alejandra E. McCord and Laura D’Ignazio and Kynon J.M. Benjamin and Bonna Sheehan and Michael Zabolocki and Arthur Feltrin and Ria Arora and Anna C. Brandtjen and Joel E. Kleinman and Thomas M. Hyde and Cedric Bardy and Daniel R. Weinberger and Apuã C.M. Paquola and Jennifer A. Erwin}, url = {https://ajp.psychiatryonline.org/doi/10.1176/appi.ajp.20220723}, doi = {10.1176/appi.ajp.20220723}, issn = {0002-953X}, year = {2023}, date = {2023-11-02}, journal = {American Journal of Psychiatry}, abstract = {Objective: Schizophrenia is a brain disorder that originates during neurodevelopment and has complex genetic and environmental etiologies. Despite decades of clinical evidence of altered striatal function in affected patients, studies examining its cellular and molecular mechanisms in humans are limited. To explore neurodevelopmental alterations in the striatum associated with schizophrenia, the authors established a method for the differentiation of induced pluripotent stem cells (iPSCs) into ventral forebrain organoids (VFOs). Methods: VFOs were generated from postmortem dural fibroblast–derived iPSCs of four individuals with schizophrenia and four neurotypical control individuals for whom postmortem caudate genotypes and transcriptomic data were profiled in the BrainSeq neurogenomics consortium. Individuals were selected such that the two groups had nonoverlapping schizophrenia polygenic risk scores (PRSs). Results: Single-cell RNA sequencing analyses of VFOs revealed differences in developmental trajectory between schizophrenia and control individuals in which inhibitory neuronal cells from the patients exhibited accelerated maturation. Furthermore, upregulated genes in inhibitory neurons in schizophrenia VFOs showed a significant overlap with upregulated genes in postmortem caudate tissue of individuals with schizophrenia compared with control individuals, including the donors of the iPSC cohort. Conclusions: The findings suggest that striatal neurons derived from high-PRS individuals with schizophrenia carry abnormalities that originated during early brain development and that the VFO model can recapitulate disease-relevant cell type–specific neurodevelopmental phenotypes in a dish.}, keywords = {3D Culture, Activity Scan Assay, HD-MEA, MaxTwo, Network Assay, Organoids}, pubstate = {published}, tppubtype = {article} } Close Objective: Schizophrenia is a brain disorder that originates during neurodevelopment and has complex genetic and environmental etiologies. Despite decades of clinical evidence of altered striatal function in affected patients, studies examining its cellular and molecular mechanisms in humans are limited. To explore neurodevelopmental alterations in the striatum associated with schizophrenia, the authors established a method for the differentiation of induced pluripotent stem cells (iPSCs) into ventral forebrain organoids (VFOs). Methods: VFOs were generated from postmortem dural fibroblast–derived iPSCs of four individuals with schizophrenia and four neurotypical control individuals for whom postmortem caudate genotypes and transcriptomic data were profiled in the BrainSeq neurogenomics consortium. Individuals were selected such that the two groups had nonoverlapping schizophrenia polygenic risk scores (PRSs). Results: Single-cell RNA sequencing analyses of VFOs revealed differences in developmental trajectory between schizophrenia and control individuals in which inhibitory neuronal cells from the patients exhibited accelerated maturation. Furthermore, upregulated genes in inhibitory neurons in schizophrenia VFOs showed a significant overlap with upregulated genes in postmortem caudate tissue of individuals with schizophrenia compared with control individuals, including the donors of the iPSC cohort. Conclusions: The findings suggest that striatal neurons derived from high-PRS individuals with schizophrenia carry abnormalities that originated during early brain development and that the VFO model can recapitulate disease-relevant cell type–specific neurodevelopmental phenotypes in a dish. Close https://ajp.psychiatryonline.org/doi/10.1176/appi.ajp.20220723 doi:10.1176/appi.ajp.20220723 Close
	Nakajima, Ryota; Shirakami, Arata; Tsumura, Hayato; Matsuda, Kouki; Nakamura, Eita; Shimono, Masanori Mutual generation in neuronal activity across the brain via deep neural approach, and its network interpretation Journal Article Communications Biology, 2023. Abstract \| Links \| BibTeX \| Tags: Brain Slice, HD-MEA, MaxOne, MEA Technology @article{Nakajima2023, title = {Mutual generation in neuronal activity across the brain via deep neural approach, and its network interpretation}, author = {Ryota Nakajima and Arata Shirakami and Hayato Tsumura and Kouki Matsuda and Eita Nakamura and Masanori Shimono}, url = {https://www.nature.com/articles/s42003-023-05453-2}, doi = {10.1038/s42003-023-05453-2}, year = {2023}, date = {2023-10-31}, journal = {Communications Biology}, abstract = {In the brain, many regions work in a network-like association, yet it is not known how durable these associations are in terms of activity and could survive without structural connections. To assess the association or similarity between brain regions with a generating approach, this study evaluated the similarity of activities of neurons within each region after disconnecting between regions. The “generation” approach here refers to using a multi-layer LSTM (Long Short-Term Memory) model to learn the rules of activity generation in one region and then apply that knowledge to generate activity in other regions. Surprisingly, the results revealed that activity generation from one region to disconnected regions was possible with similar accuracy to generation between the same regions in many cases. Notably, firing rates and synchronization of firing between neuron pairs, often used as neuronal representations, could be reproduced with precision. Additionally, accuracies were associated with the relative angle between brain regions and the strength of the structural connections that initially connected them. This outcome enables us to look into trends governing non-uniformity of the cortex based on the potential to generate informative data and reduces the need for animal experiments.}, keywords = {Brain Slice, HD-MEA, MaxOne, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close In the brain, many regions work in a network-like association, yet it is not known how durable these associations are in terms of activity and could survive without structural connections. To assess the association or similarity between brain regions with a generating approach, this study evaluated the similarity of activities of neurons within each region after disconnecting between regions. The “generation” approach here refers to using a multi-layer LSTM (Long Short-Term Memory) model to learn the rules of activity generation in one region and then apply that knowledge to generate activity in other regions. Surprisingly, the results revealed that activity generation from one region to disconnected regions was possible with similar accuracy to generation between the same regions in many cases. Notably, firing rates and synchronization of firing between neuron pairs, often used as neuronal representations, could be reproduced with precision. Additionally, accuracies were associated with the relative angle between brain regions and the strength of the structural connections that initially connected them. This outcome enables us to look into trends governing non-uniformity of the cortex based on the potential to generate informative data and reduces the need for animal experiments. Close https://www.nature.com/articles/s42003-023-05453-2 doi:10.1038/s42003-023-05453-2 Close
	Duru, Jens; Rüfenacht, Arielle; Löhle, Josephine; Pozzi, Marcello; Forró, Csaba; Ledermann, Linus; Bernardi, Aeneas; Matter, Michael; Renia, André; Simona, Benjamin; Tringides, Christina M; Bernhard, Stéphane; Ihle, Stephan J; Hengsteler, Julian; Maurer, Benedikt; Zhanga, Xinyu; Nakatsuka, Nako Driving electrochemical reactions at the microscale using CMOS microelectrode arrays Journal Article Lab on a Chip, 2023, ISSN: 1473-0189. Abstract \| Links \| BibTeX \| Tags: HD-MEA, MaxOne, Primary Neuronal Cell Culture, Stimulation @article{Duru2023c, title = {Driving electrochemical reactions at the microscale using CMOS microelectrode arrays}, author = {Jens Duru and Arielle Rüfenacht and Josephine Löhle and Marcello Pozzi and Csaba Forró and Linus Ledermann and Aeneas Bernardi and Michael Matter and André Renia and Benjamin Simona and Christina M. Tringides and Stéphane Bernhard and Stephan J. Ihle and Julian Hengsteler and Benedikt Maurer and Xinyu Zhanga and Nako Nakatsuka}, url = {https://pubs.rsc.org/en/content/articlelanding/2023/lc/d3lc00630a}, doi = {10.1039/D3LC00630A}, issn = {1473-0189}, year = {2023}, date = {2023-10-30}, journal = {Lab on a Chip}, abstract = {Precise control of pH values at electrode interfaces enables the systematic investigation of pH-dependent processes by electrochemical means. In this work, we employed high-density complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs) as miniaturized systems to induce and confine electrochemical reactions in areas corresponding to the pitch of single electrodes (17.5 μm). First, we present a strategy for generating localized pH patterns on the surface of the CMOS MEA with unprecedented spatial resolution. Leveraging the versatile routing capabilities of the switch matrix beneath the CMOS MEA, we created arbitrary combinations of anodic and cathodic electrodes and hence pH patterns. Moreover, we utilized the system to produce polymeric surface patterns by additive and subtractive methods. For additive patterning, we controlled the in situ formation of polydopamine at the microelectrode surface through oxidation of free dopamine above a threshold pH > 8.5. For subtractive patterning, we removed cell-adhesive poly-L-lysine from the electrode surface and backfilled the voids with antifouling polymers. Such polymers were chosen to provide a proof-of-concept application of controlling neuronal growth via electrochemically-induced patterns on the CMOS MEA surface. Importantly, our platform is compatible with commercially available high-density MEAs and requires no custom equipment, rendering the findings generalizable and accessible.}, keywords = {HD-MEA, MaxOne, Primary Neuronal Cell Culture, Stimulation}, pubstate = {published}, tppubtype = {article} } Close Precise control of pH values at electrode interfaces enables the systematic investigation of pH-dependent processes by electrochemical means. In this work, we employed high-density complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs) as miniaturized systems to induce and confine electrochemical reactions in areas corresponding to the pitch of single electrodes (17.5 μm). First, we present a strategy for generating localized pH patterns on the surface of the CMOS MEA with unprecedented spatial resolution. Leveraging the versatile routing capabilities of the switch matrix beneath the CMOS MEA, we created arbitrary combinations of anodic and cathodic electrodes and hence pH patterns. Moreover, we utilized the system to produce polymeric surface patterns by additive and subtractive methods. For additive patterning, we controlled the in situ formation of polydopamine at the microelectrode surface through oxidation of free dopamine above a threshold pH > 8.5. For subtractive patterning, we removed cell-adhesive poly-L-lysine from the electrode surface and backfilled the voids with antifouling polymers. Such polymers were chosen to provide a proof-of-concept application of controlling neuronal growth via electrochemically-induced patterns on the CMOS MEA surface. Importantly, our platform is compatible with commercially available high-density MEAs and requires no custom equipment, rendering the findings generalizable and accessible. Close https://pubs.rsc.org/en/content/articlelanding/2023/lc/d3lc00630a doi:10.1039/D3LC00630A Close
	hiya Lv,; He, Enhui; Luo, Jinping; Liu, Yaoyao; Liang, Wei; Xu, Shihong; Zhang, Kui; Yang, Yan; Wang, Mixia; Song, Yilin; Wu, Yirong; Cai, Xinxia Using Human-Induced Pluripotent Stem Cell Derived Neurons on Microelectrode Arrays to Model Neurological Disease: A Review Journal Article Advanced Science, 2023. Abstract \| Links \| BibTeX \| Tags: Brain Slice, HD-MEA, IPSC, MEA Technology, Organoids @article{Lv2023, title = {Using Human-Induced Pluripotent Stem Cell Derived Neurons on Microelectrode Arrays to Model Neurological Disease: A Review}, author = {hiya Lv and Enhui He and Jinping Luo and Yaoyao Liu and Wei Liang and Shihong Xu and Kui Zhang and Yan Yang and Mixia Wang and Yilin Song and Yirong Wu and Xinxia Cai}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/advs.202301828}, doi = {10.1002/advs.202301828}, year = {2023}, date = {2023-10-23}, journal = {Advanced Science}, abstract = {In situ physiological signals of in vitro neural disease models are essential for studying pathogenesis and drug screening. Currently, an increasing number of in vitro neural disease models are established using human-induced pluripotent stem cell (hiPSC) derived neurons (hiPSC-DNs) to overcome interspecific gene expression differences. Microelectrode arrays (MEAs) can be readily interfaced with two-dimensional (2D), and more recently, three-dimensional (3D) neural stem cell-derived in vitro models of the human brain to monitor their physiological activity in real time. Therefore, MEAs are emerging and useful tools to model neurological disorders and disease in vitro using human iPSCs. This is enabling a real-time window into neuronal signaling at the network scale from patient derived. This paper provides a comprehensive review of MEA’s role in analyzing neural disease models established by hiPSC-DNs. It covers the significance of MEA fabrication, surface structure and modification schemes for hiPSC-DNs culturing and signal detection. Additionally, this review discusses advances in the development and use of MEA technology to study in vitro neural disease models, including epilepsy, autism spectrum developmental disorder (ASD), and others established using hiPSC-DNs. The paper also highlights the application of MEAs combined with hiPSC-DNs in detecting in vitro neurotoxic substances. Finally, the future development and outlook of multifunctional and integrated devices for in vitro medical diagnostics and treatment are discussed.}, keywords = {Brain Slice, HD-MEA, IPSC, MEA Technology, Organoids}, pubstate = {published}, tppubtype = {article} } Close In situ physiological signals of in vitro neural disease models are essential for studying pathogenesis and drug screening. Currently, an increasing number of in vitro neural disease models are established using human-induced pluripotent stem cell (hiPSC) derived neurons (hiPSC-DNs) to overcome interspecific gene expression differences. Microelectrode arrays (MEAs) can be readily interfaced with two-dimensional (2D), and more recently, three-dimensional (3D) neural stem cell-derived in vitro models of the human brain to monitor their physiological activity in real time. Therefore, MEAs are emerging and useful tools to model neurological disorders and disease in vitro using human iPSCs. This is enabling a real-time window into neuronal signaling at the network scale from patient derived. This paper provides a comprehensive review of MEA’s role in analyzing neural disease models established by hiPSC-DNs. It covers the significance of MEA fabrication, surface structure and modification schemes for hiPSC-DNs culturing and signal detection. Additionally, this review discusses advances in the development and use of MEA technology to study in vitro neural disease models, including epilepsy, autism spectrum developmental disorder (ASD), and others established using hiPSC-DNs. The paper also highlights the application of MEAs combined with hiPSC-DNs in detecting in vitro neurotoxic substances. Finally, the future development and outlook of multifunctional and integrated devices for in vitro medical diagnostics and treatment are discussed. Close https://onlinelibrary.wiley.com/doi/abs/10.1002/advs.202301828 doi:10.1002/advs.202301828 Close
	Kelley, Matt R; Chipman, Laura B; Asano, Shoh; Knott, Matthew; Howard, Samantha T; Berg, Allison P Potentiating NaV1.1 in Dravet syndrome patient iPSC-derived GABAergic neurons increases neuronal firing frequency and decreases network synchrony Journal Article bioRxiv, 2023. Abstract \| Links \| BibTeX \| Tags: Activity Scan Assay, Axon Tracking Assay, HD-MEA, IPSC, MaxTwo, MEA Technology, Network Assay, Spike Sorting @article{Kelley2023, title = {Potentiating NaV1.1 in Dravet syndrome patient iPSC-derived GABAergic neurons increases neuronal firing frequency and decreases network synchrony}, author = {Matt R Kelley and Laura B Chipman and Shoh Asano and Matthew Knott and Samantha T Howard and Allison P Berg}, url = {https://www.biorxiv.org/content/10.1101/2023.09.28.559990v1}, doi = {10.1101/2023.09.28.559990}, year = {2023}, date = {2023-09-29}, journal = {bioRxiv}, abstract = {Dravet syndrome is a developmental and epileptic encephalopathy characterized by seizures, behavioral abnormalities, developmental deficits, and elevated risk of sudden unexpected death in epilepsy (SUDEP). Most patient cases are caused by de novo loss-of-function mutations in the gene SCN1A, causing a haploinsufficiency of the alpha subunit of the voltage-gated sodium channel NaV1.1. Within the brain, NaV1.1 is primarily localized to the axons of inhibitory neurons, and decreased NaV1.1 function is hypothesized to reduce GABAergic inhibitory neurotransmission within the brain, driving neuronal network hyperexcitability and subsequent pathology. We have developed a human in vitro model of Dravet syndrome using differentiated neurons derived from patient iPSC and enriched for GABA expressing neurons. Neurons were plated on high definition multielectrode arrays (HD-MEAs), permitting recordings from the same cultures over the 7-weeks duration of study at the network, single cell, and subcellular resolution. Using this capability, we characterized the features of axonal morphology and physiology. Neurons developed increased spiking activity and synchronous network bursting. Recordings were processed through a spike sorting pipeline for curation of single unit activity and to assess the effects of pharmacological treatments. At 7-weeks, the application of the GABAAR receptor agonist muscimol eliminated network bursting, indicating the presence of GABAergic neurotransmission. To identify the role of NaV1.1 on neuronal and network activity, cultures were treated with a dose-response of the NaV1.1 potentiator δ-theraphotoxin-Hm1a. This resulted in a strong increase in firing rates of putative GABAergic neurons, an increase in the intraburst firing rate, and eliminated network bursting. These results validate that potentiation of NaV1.1 in Dravet patient iPSC-derived neurons results in decreased firing synchrony in neuronal networks through increased GABAergic neuron activity and support the use of human neurons and HD-MEAs as viable high-throughput electrophysiological platform to enable therapeutic discovery.}, keywords = {Activity Scan Assay, Axon Tracking Assay, HD-MEA, IPSC, MaxTwo, MEA Technology, Network Assay, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close Dravet syndrome is a developmental and epileptic encephalopathy characterized by seizures, behavioral abnormalities, developmental deficits, and elevated risk of sudden unexpected death in epilepsy (SUDEP). Most patient cases are caused by de novo loss-of-function mutations in the gene SCN1A, causing a haploinsufficiency of the alpha subunit of the voltage-gated sodium channel NaV1.1. Within the brain, NaV1.1 is primarily localized to the axons of inhibitory neurons, and decreased NaV1.1 function is hypothesized to reduce GABAergic inhibitory neurotransmission within the brain, driving neuronal network hyperexcitability and subsequent pathology. We have developed a human in vitro model of Dravet syndrome using differentiated neurons derived from patient iPSC and enriched for GABA expressing neurons. Neurons were plated on high definition multielectrode arrays (HD-MEAs), permitting recordings from the same cultures over the 7-weeks duration of study at the network, single cell, and subcellular resolution. Using this capability, we characterized the features of axonal morphology and physiology. Neurons developed increased spiking activity and synchronous network bursting. Recordings were processed through a spike sorting pipeline for curation of single unit activity and to assess the effects of pharmacological treatments. At 7-weeks, the application of the GABAAR receptor agonist muscimol eliminated network bursting, indicating the presence of GABAergic neurotransmission. To identify the role of NaV1.1 on neuronal and network activity, cultures were treated with a dose-response of the NaV1.1 potentiator δ-theraphotoxin-Hm1a. This resulted in a strong increase in firing rates of putative GABAergic neurons, an increase in the intraburst firing rate, and eliminated network bursting. These results validate that potentiation of NaV1.1 in Dravet patient iPSC-derived neurons results in decreased firing synchrony in neuronal networks through increased GABAergic neuron activity and support the use of human neurons and HD-MEAs as viable high-throughput electrophysiological platform to enable therapeutic discovery. Close https://www.biorxiv.org/content/10.1101/2023.09.28.559990v1 doi:10.1101/2023.09.28.559990 Close
	Metto, Abigael C; Telgkamp, Petra; McLane-Svoboda, Autumn K; Gilad, Assaf A; Pelled, Galit Closed-loop neurostimulation via expression of magnetogenetics-sensitive protein in inhibitory neurons leads to reduction of seizure activity in a rat model of epilepsy Journal Article Brain Research, 2023. Abstract \| Links \| BibTeX \| Tags: 3D Culture, closed loop stimulation, HD-MEA, MaxOne, Slices @article{Metto2023, title = {Closed-loop neurostimulation via expression of magnetogenetics-sensitive protein in inhibitory neurons leads to reduction of seizure activity in a rat model of epilepsy}, author = {Abigael C. Metto and Petra Telgkamp and Autumn K. McLane-Svoboda and Assaf A. Gilad and Galit Pelled}, url = {https://www.sciencedirect.com/science/article/pii/S0006899323003621}, doi = {https://doi.org/10.1016/j.brainres.2023.148591}, year = {2023}, date = {2023-09-24}, journal = {Brain Research}, abstract = {On-demand neurostimulation has shown success in epilepsy patients with pharmacoresistant seizures. Seizures produce magnetic fields that can be recorded using magnetoencephalography. We developed a new closed-loop approach to control seizure activity based on magnetogenetics using the electromagnetic perceptive gene (EPG) that encodes a protein that responds to magnetic fields. The EPG transgene was expressed in inhibitory interneurons under the hDlx promoter and kainic acid was used to induce acute seizures. In vivo electrophysiological signals were recorded. We found that hDlx EPG rats exhibited a significant delay in the onset of first seizure (1142.72 ± 186.35 s) compared to controls (644.03 ± 15.06 s) and significantly less seizures (4.11 ± 1.03) compared to controls (8.33 ± 1.58). These preliminary findings suggest that on-demand activation of EPG expressed in inhibitory interneurons suppresses seizure activity, and magnetogenetics via EPG may be an effective strategy to alleviate seizure severity in a closed-loop, and cell-specific fashion.}, keywords = {3D Culture, closed loop stimulation, HD-MEA, MaxOne, Slices}, pubstate = {published}, tppubtype = {article} } Close On-demand neurostimulation has shown success in epilepsy patients with pharmacoresistant seizures. Seizures produce magnetic fields that can be recorded using magnetoencephalography. We developed a new closed-loop approach to control seizure activity based on magnetogenetics using the electromagnetic perceptive gene (EPG) that encodes a protein that responds to magnetic fields. The EPG transgene was expressed in inhibitory interneurons under the hDlx promoter and kainic acid was used to induce acute seizures. In vivo electrophysiological signals were recorded. We found that hDlx EPG rats exhibited a significant delay in the onset of first seizure (1142.72 ± 186.35 s) compared to controls (644.03 ± 15.06 s) and significantly less seizures (4.11 ± 1.03) compared to controls (8.33 ± 1.58). These preliminary findings suggest that on-demand activation of EPG expressed in inhibitory interneurons suppresses seizure activity, and magnetogenetics via EPG may be an effective strategy to alleviate seizure severity in a closed-loop, and cell-specific fashion. Close https://www.sciencedirect.com/science/article/pii/S0006899323003621 doi:https://doi.org/10.1016/j.brainres.2023.148591 Close
	Levi, Timothee; Beaubois, Romain; Cheslet, Jérémy; Duenki, Tomoya; Khoyratee, Farad; Branchereau, Pascal; Ikeuchi, Yoshiho BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network Journal Article Research Square, 2023. Abstract \| Links \| BibTeX \| Tags: closed loop stimulation, MaxOne, MEA Technology, Organoids @article{Levi2023, title = {BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network}, author = {Timothee Levi and Romain Beaubois and Jérémy Cheslet and Tomoya Duenki and Farad Khoyratee and Pascal Branchereau and Yoshiho Ikeuchi}, url = {https://www.researchsquare.com}, doi = {10.21203/rs.3.rs-3191285/v1}, year = {2023}, date = {2023-09-15}, journal = {Research Square}, abstract = {Characterization and modeling of biological neural networks is a field opening to major advances in our understanding of the mechanisms governing the functioning of the brain and the different pathologies that can affect it. Recent researches in bioelectronics and neuromorphic engineering lead to the design of the new generation of neuroprosthesis. Here we show a novel real-time, biomimetic and energy-efficient neural network for bio-hybrid experiments and parallel emulation. This novel system is used to investigate and reproduce neural network dynamics. The setup is running on a digital platform using a System on Chip (SoC) featuring both Programmable Logic (PL) and processors in a Processing System (PS) part. The FPGA part is computing the biomimetic and real-time electrical activities of Hodgkin-Huxley neural network while the processors handle monitoring and communication. New methods of resource and power optimization has been applied to the FPGA to allow detailed neuron modeling with synapses showing short term plasticity. The system is validated by comparison with biological data and model. We also demonstrate the feasibility of bio-hybrid experiments with different bio-physical interface and different biological cells. The complete setup achieves communication with a fully flexible real-time device thus constituting a step towards neuromorphic-based neuroprosthesis for bioelectrical therapeutics.}, keywords = {closed loop stimulation, MaxOne, MEA Technology, Organoids}, pubstate = {published}, tppubtype = {article} } Close Characterization and modeling of biological neural networks is a field opening to major advances in our understanding of the mechanisms governing the functioning of the brain and the different pathologies that can affect it. Recent researches in bioelectronics and neuromorphic engineering lead to the design of the new generation of neuroprosthesis. Here we show a novel real-time, biomimetic and energy-efficient neural network for bio-hybrid experiments and parallel emulation. This novel system is used to investigate and reproduce neural network dynamics. The setup is running on a digital platform using a System on Chip (SoC) featuring both Programmable Logic (PL) and processors in a Processing System (PS) part. The FPGA part is computing the biomimetic and real-time electrical activities of Hodgkin-Huxley neural network while the processors handle monitoring and communication. New methods of resource and power optimization has been applied to the FPGA to allow detailed neuron modeling with synapses showing short term plasticity. The system is validated by comparison with biological data and model. We also demonstrate the feasibility of bio-hybrid experiments with different bio-physical interface and different biological cells. The complete setup achieves communication with a fully flexible real-time device thus constituting a step towards neuromorphic-based neuroprosthesis for bioelectrical therapeutics. Close https://www.researchsquare.com doi:10.21203/rs.3.rs-3191285/v1 Close
	Silverman, Jill L; Fenton, Timothy; Haouchine, Olivia; Hallam, Elizabeth; Smith, Emily; Jackson, Kiya; Rahbarian, Darlene; Canales, Cesar; Adhikari, Anna; Nord, Alex; Ben-Shalom, Roy Hyperexcitability and translational phenotypes in a preclinical model of SYNGAP1mutations Journal Article Research Square, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, Activity Scan Assay, HD-MEA, MaxOne, Network Assay, Primary Neuronal Cell Culture @article{Silverman2023, title = {Hyperexcitability and translational phenotypes in a preclinical model of SYNGAP1mutations}, author = {Jill L. Silverman and Timothy Fenton and Olivia Haouchine and Elizabeth Hallam and Emily Smith and Kiya Jackson and Darlene Rahbarian and Cesar Canales and Anna Adhikari and Alex Nord and Roy Ben-Shalom}, url = {https://www.researchsquare.com/article/rs-3246655/v1}, doi = {https://doi.org/10.21203/rs.3.rs-3246655/v1}, year = {2023}, date = {2023-09-13}, journal = {Research Square}, abstract = {SYNGAP1is a critical gene for neuronal development, synaptic structure, and function. Although rare, the disruption of SYNGAP1directly causes a genetically identi able neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability. Without functional SynGAP1 protein, patients present with intellectual disability, motor impairments, and epilepsy. Previous work using mouse models with a variety of germline and conditional mutations has helped delineate SynGAP1’s critical roles in neuronal structure and function, as well as key biochemical signaling pathways essential to synapse integrity. Homozygous loss of SYNGAP1is embryonically lethal. Heterozygous mutations of SynGAP1result in a broad range of phenotypes including increased locomotor activity, impaired working spatial memory, impaired cued fear memory, and increased stereotypic behavior. Ourinvivofunctional data, using the original germline mutation mouse line from the Huganir laboratory, corroborated robust hyperactivity and learning and memory de cits. Here, we describe impairments in the translational biomarker domain of sleep, characterized using neurophysiological data collected with wireless telemetric electroencephalography (EEG). We discoveredSyngap1+/− mice exhibited elevated spike trains in both number and duration, in addition to elevated power, most notably in the delta power band. Primary neurons fromSyngap1+/− mice displayed increased network ring activity, greater spikes per burst, and shorter inter-burst intervals between peaks using high density micro-electrode arrays (HD-MEA). This work is translational, innovative, and highly signi cant as it outlines functional impairments in Syngap1mutant mice. Simultaneously, the work utilized untethered, wireless neurophysiology that can discover potential biomarkers of Syngap1RID, for clinical trials, as it has done with other NDDs. Our work is substantial forward progress toward translational work for SynGAP1R-ID as it bridges in-vitroelectrophysiological neuronal activity and function with invivoneurophysiological brain activity and function. These data elucidate multiple quantitative, translational biomarkers invivoand invitrofor the development of treatments for SYNGAP1-related intellectual disability.}, keywords = {2D Neuronal Culture, Activity Scan Assay, HD-MEA, MaxOne, Network Assay, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close SYNGAP1is a critical gene for neuronal development, synaptic structure, and function. Although rare, the disruption of SYNGAP1directly causes a genetically identi able neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability. Without functional SynGAP1 protein, patients present with intellectual disability, motor impairments, and epilepsy. Previous work using mouse models with a variety of germline and conditional mutations has helped delineate SynGAP1’s critical roles in neuronal structure and function, as well as key biochemical signaling pathways essential to synapse integrity. Homozygous loss of SYNGAP1is embryonically lethal. Heterozygous mutations of SynGAP1result in a broad range of phenotypes including increased locomotor activity, impaired working spatial memory, impaired cued fear memory, and increased stereotypic behavior. Ourinvivofunctional data, using the original germline mutation mouse line from the Huganir laboratory, corroborated robust hyperactivity and learning and memory de cits. Here, we describe impairments in the translational biomarker domain of sleep, characterized using neurophysiological data collected with wireless telemetric electroencephalography (EEG). We discoveredSyngap1+/− mice exhibited elevated spike trains in both number and duration, in addition to elevated power, most notably in the delta power band. Primary neurons fromSyngap1+/− mice displayed increased network ring activity, greater spikes per burst, and shorter inter-burst intervals between peaks using high density micro-electrode arrays (HD-MEA). This work is translational, innovative, and highly signi cant as it outlines functional impairments in Syngap1mutant mice. Simultaneously, the work utilized untethered, wireless neurophysiology that can discover potential biomarkers of Syngap1RID, for clinical trials, as it has done with other NDDs. Our work is substantial forward progress toward translational work for SynGAP1R-ID as it bridges in-vitroelectrophysiological neuronal activity and function with invivoneurophysiological brain activity and function. These data elucidate multiple quantitative, translational biomarkers invivoand invitrofor the development of treatments for SYNGAP1-related intellectual disability. Close https://www.researchsquare.com/article/rs-3246655/v1 doi:https://doi.org/10.21203/rs.3.rs-3246655/v1 Close
	Habibollahi, Forough; Kagan, Brett J; Burkitt, Anthony N; French, Chris Critical dynamics arise during structured information presentation within embodied in vitro neuronal networks Journal Article Nature Communications, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Metrics, MEA Technology, Primary Neuronal Cell Culture @article{Habibollahi2023, title = {Critical dynamics arise during structured information presentation within embodied in vitro neuronal networks}, author = {Forough Habibollahi and Brett J. Kagan and Anthony N. Burkitt and Chris French }, url = {https://www.nature.com/articles/s41467-023-41020-3}, doi = {https://doi.org/10.1038/s41467-023-41020-3}, year = {2023}, date = {2023-08-30}, journal = {Nature Communications}, abstract = {Understanding how brains process information is an incredibly difficult task. Amongst the metrics characterising information processing in the brain, observations of dynamic near-critical states have generated significant interest. However, theoretical and experimental limitations associated with human and animal models have precluded a definite answer about when and why neural criticality arises with links from attention, to cognition, and even to consciousness. To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of ‘Pong’ to demonstrate Synthetic Biological Intelligence (SBI). We demonstrate that critical dynamics emerge when neural networks receive task-related structured sensory input, reorganizing the system to a near-critical state. Additionally, better task performance correlated with proximity to critical dynamics. However, criticality alone is insufficient for a neuronal network to demonstrate learning in the absence of additional information regarding the consequences of previous actions. These findings offer compelling support that neural criticality arises as a base feature of incoming structured information processing without the need for higher order cognition.}, keywords = {2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Metrics, MEA Technology, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close Understanding how brains process information is an incredibly difficult task. Amongst the metrics characterising information processing in the brain, observations of dynamic near-critical states have generated significant interest. However, theoretical and experimental limitations associated with human and animal models have precluded a definite answer about when and why neural criticality arises with links from attention, to cognition, and even to consciousness. To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of ‘Pong’ to demonstrate Synthetic Biological Intelligence (SBI). We demonstrate that critical dynamics emerge when neural networks receive task-related structured sensory input, reorganizing the system to a near-critical state. Additionally, better task performance correlated with proximity to critical dynamics. However, criticality alone is insufficient for a neuronal network to demonstrate learning in the absence of additional information regarding the consequences of previous actions. These findings offer compelling support that neural criticality arises as a base feature of incoming structured information processing without the need for higher order cognition. Close https://www.nature.com/articles/s41467-023-41020-3 doi:https://doi.org/10.1038/s41467-023-41020-3 Close
	Radivojevic, Milos; Punga, Anna Rostedt Functional imaging of conduction dynamics in cortical and spinal axons Journal Article eLife, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, Axon Tracking Assay, MaxOne, MEA Technology, Primary Neuronal Cell Culture @article{Radivojevic2023_2, title = {Functional imaging of conduction dynamics in cortical and spinal axons}, author = {Milos Radivojevic and Anna Rostedt Punga}, url = {https://elifesciences.org/articles/86512}, doi = {https://doi.org/10.7554/eLife.86512}, year = {2023}, date = {2023-08-22}, journal = {eLife}, abstract = {Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here, we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-cm-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 m of cortical and spinal axons in total and found specific features in their structure and function.}, keywords = {2D Neuronal Culture, Axon Tracking Assay, MaxOne, MEA Technology, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here, we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-cm-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 m of cortical and spinal axons in total and found specific features in their structure and function. Close https://elifesciences.org/articles/86512 doi:https://doi.org/10.7554/eLife.86512 Close
	Duru, Jens; Maurer, Benedikt; Doran, Ciara Giles; Jelitto, Robert; Küchler, Joël; Ihle, Stephan J; Ruff, Tobias; John, Robert; Genocchi, Barbara; Vörös, János Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays Journal Article Biosensors and Bioelectronics, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, MaxOne, Stimulation @article{Duru2023b, title = {Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays}, author = {Jens Duru and Benedikt Maurer and Ciara Giles Doran and Robert Jelitto and Joël Küchler and Stephan J. Ihle and Tobias Ruff and Robert John and Barbara Genocchi and János Vörös }, url = {https://www.sciencedirect.com/science/article/pii/S095656632300533X?via%3Dihub}, doi = {https://doi.org/10.1016/j.bios.2023.115591}, year = {2023}, date = {2023-08-18}, journal = {Biosensors and Bioelectronics}, abstract = {Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks' early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.}, keywords = {2D Neuronal Culture, HD-MEA, MaxOne, Stimulation}, pubstate = {published}, tppubtype = {article} } Close Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks' early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation. Close https://www.sciencedirect.com/science/article/pii/S095656632300533X?via%3Dihub doi:https://doi.org/10.1016/j.bios.2023.115591 Close
	Ulusan, Hasan; Diggelmann, Roland; Bartram, Julian; Magnan, Chloe; Kumar, Sreedhar; Hierlemann, Andreas Multi-Functional HD-MEA Platform for High-Resolution Impedance Imaging and Electrophysiological Recordings of Brain Slices Conference 2023 IEEE BioSensors Conference (BioSensors), IEEE, 2023, ISBN: 9798350346046. Abstract \| Links \| BibTeX \| Tags: ETH-CMOS-MEA, MEA Technology @conference{Ulusan2023, title = {Multi-Functional HD-MEA Platform for High-Resolution Impedance Imaging and Electrophysiological Recordings of Brain Slices}, author = {Hasan Ulusan and Roland Diggelmann and Julian Bartram and Chloe Magnan and Sreedhar Kumar and Andreas Hierlemann}, url = {https://ieeexplore.ieee.org/document/10280868/}, doi = {10.1109/BioSensors58001.2023.10280868}, isbn = {9798350346046}, year = {2023}, date = {2023-07-30}, booktitle = {2023 IEEE BioSensors Conference (BioSensors)}, pages = {1-4}, publisher = {IEEE}, abstract = {We present a high-resolution impedance imaging and electrophysiological recording platform and demonstrate its capabilities with brain slices. The platform is easy to operate featuring an efficient data acquisition system and user-friendly software that runs on a host computer. The data acquisi tion platform relies on an FPGA system that enable s bidirectional communication between the host computer and the high-density microelectrode array (HD-MEA). The software on the host computer helps to record and online visuali ze the HD -MEA data. Moreover, online filtering (and spike detection ) features rapid visual feedback t hat enables the experimenter to reconfigure the HD -MEA. The platform includes a custom designed pressing device to affix the brain slice on the HD-MEA and maintain good electrode-tissue contact. We validated the system with mouse acute cerebellar brain slices; high-resolution impedance imaging and electrophysiological recordings yielded data that were consistent with optical imaging. Moreover, the platform enabled the selection of highly active regions for recordings with high-density configuration s and monitor multiple neurons in the same area at single-cell resolution.}, keywords = {ETH-CMOS-MEA, MEA Technology}, pubstate = {published}, tppubtype = {conference} } Close We present a high-resolution impedance imaging and electrophysiological recording platform and demonstrate its capabilities with brain slices. The platform is easy to operate featuring an efficient data acquisition system and user-friendly software that runs on a host computer. The data acquisi tion platform relies on an FPGA system that enable s bidirectional communication between the host computer and the high-density microelectrode array (HD-MEA). The software on the host computer helps to record and online visuali ze the HD -MEA data. Moreover, online filtering (and spike detection ) features rapid visual feedback t hat enables the experimenter to reconfigure the HD -MEA. The platform includes a custom designed pressing device to affix the brain slice on the HD-MEA and maintain good electrode-tissue contact. We validated the system with mouse acute cerebellar brain slices; high-resolution impedance imaging and electrophysiological recordings yielded data that were consistent with optical imaging. Moreover, the platform enabled the selection of highly active regions for recordings with high-density configuration s and monitor multiple neurons in the same area at single-cell resolution. Close https://ieeexplore.ieee.org/document/10280868/ doi:10.1109/BioSensors58001.2023.10280868 Close
	Miyahara, Yuki; Shimba, Kenta; Kotani, Kiyoshi; Jimbo, Yasuhiko Development of a Hypersensitivity Evaluation Method for Cultured Sensory Neurons Using Electrical Activity Recording Conference IEEE EMBC 2023 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, Activity Scan Assay, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture @conference{Miyahara2023, title = {Development of a Hypersensitivity Evaluation Method for Cultured Sensory Neurons Using Electrical Activity Recording}, author = {Yuki Miyahara and Kenta Shimba and Kiyoshi Kotani and Yasuhiko Jimbo}, url = {https://arinex.com.au/EMBC/pdf/full-paper_363.pdf}, year = {2023}, date = {2023-07-27}, organization = {IEEE EMBC 2023}, abstract = {Investigation of hypersensitivity caused by peripheral sensitization progression is important for developing novel pain treatments. Existing methods cannot record plastic changes in neuronal activity because they occur over a few days. We aimed to establish an efficient method to evaluate neuronal activity alterations caused by peripheral sensitization on highdensity microelectrode arrays (HD-MEAs) which can record neuronal activity for a long time. Rat dorsal root ganglion (DRG) neurons were dissected from rat embryos and cultured on HDMEAs. DRG neurons were labeled with NeuO, live staining dye. Neurons were detected with the fluorescence signal and electrodes were selected with the fluorescence images. The number of DRG neurons, whose activity were recorded, detected based on fluorescence observation was five times greater than that based on neuronal activity. Analysis of changes in neuronal activity observed in pharmacological stimulation experiments suggested that substance P induced peripheral sensitization and enhanced capsaicin sensitivity. In addition, results of immunofluorescence staining suggested that peripheral sensitization occurred mostly in neurons that co-expressed transient receptor potential vanilloid 1 (TRPV1) and neurokinin 1 receptor (NK1R). In conclusion, we established an efficient method for assessing the effects of peripheral sensitization on DRG neurons cultured on HD-MEAs.}, keywords = {2D Neuronal Culture, Activity Scan Assay, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {conference} } Close Investigation of hypersensitivity caused by peripheral sensitization progression is important for developing novel pain treatments. Existing methods cannot record plastic changes in neuronal activity because they occur over a few days. We aimed to establish an efficient method to evaluate neuronal activity alterations caused by peripheral sensitization on highdensity microelectrode arrays (HD-MEAs) which can record neuronal activity for a long time. Rat dorsal root ganglion (DRG) neurons were dissected from rat embryos and cultured on HDMEAs. DRG neurons were labeled with NeuO, live staining dye. Neurons were detected with the fluorescence signal and electrodes were selected with the fluorescence images. The number of DRG neurons, whose activity were recorded, detected based on fluorescence observation was five times greater than that based on neuronal activity. Analysis of changes in neuronal activity observed in pharmacological stimulation experiments suggested that substance P induced peripheral sensitization and enhanced capsaicin sensitivity. In addition, results of immunofluorescence staining suggested that peripheral sensitization occurred mostly in neurons that co-expressed transient receptor potential vanilloid 1 (TRPV1) and neurokinin 1 receptor (NK1R). In conclusion, we established an efficient method for assessing the effects of peripheral sensitization on DRG neurons cultured on HD-MEAs. Close https://arinex.com.au/EMBC/pdf/full-paper_363.pdf Close
	Akita, Dai; Suwa, Eisuke; Ikeda, Narumitsu; Takahashi, Hirokazu Neural Activity and Information Processing Capacity of Neuronal Culture Conference IEEE EMBC 2023 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Stimulation @conference{Akita2023, title = {Neural Activity and Information Processing Capacity of Neuronal Culture}, author = {Dai Akita and Eisuke Suwa and Narumitsu Ikeda and Hirokazu Takahashi}, url = {https://arinex.com.au/EMBC/pdf/full-paper_654.pdf}, year = {2023}, date = {2023-07-27}, organization = {IEEE EMBC 2023}, abstract = {Whether artificial or living, neural networks perform tremendously diverse kinds of information processing, such as visual feature extraction, speech recognition, motor control, and so on. Some studies have evaluated the computational ability of living neural networks based on the performances of specific tasks, yet could not comprehensively grasp the versatile ability. In this study, we investigated dissociated culture of neurons as a physical reservoir, which generates diverse outputs through linear regression, or readout, of the dynamical states. Based on the theory of reservoir computing, the potential computational capabilities of neuronal culture were evaluated by the information processing capacity (IPC), which indicates how a target function can be achieved from the given dynamics. As a result, we found that the neuronal culture exhibited significant IPC and that IPC varied with the inter-step interval (ISI), the time step of reservoir computing. The cultures exhibited a memory capacity of 10 time steps for computation, and this memory capacity decayed at an ISI of 5 ms or shorter. In addition, the IPC had a significant positive correlation with the intensity of the evoked response relative to spontaneous activity. The multiple regression model with evoked response and ISI showed the positive effect of evoked response and 30 ms as the best ISI for IPC. These results suggest that the distinct evoked response and the optimal time step to interact with the neuronal culture are key factors to uncover computational resources from the neuronal system.}, keywords = {2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Stimulation}, pubstate = {published}, tppubtype = {conference} } Close Whether artificial or living, neural networks perform tremendously diverse kinds of information processing, such as visual feature extraction, speech recognition, motor control, and so on. Some studies have evaluated the computational ability of living neural networks based on the performances of specific tasks, yet could not comprehensively grasp the versatile ability. In this study, we investigated dissociated culture of neurons as a physical reservoir, which generates diverse outputs through linear regression, or readout, of the dynamical states. Based on the theory of reservoir computing, the potential computational capabilities of neuronal culture were evaluated by the information processing capacity (IPC), which indicates how a target function can be achieved from the given dynamics. As a result, we found that the neuronal culture exhibited significant IPC and that IPC varied with the inter-step interval (ISI), the time step of reservoir computing. The cultures exhibited a memory capacity of 10 time steps for computation, and this memory capacity decayed at an ISI of 5 ms or shorter. In addition, the IPC had a significant positive correlation with the intensity of the evoked response relative to spontaneous activity. The multiple regression model with evoked response and ISI showed the positive effect of evoked response and 30 ms as the best ISI for IPC. These results suggest that the distinct evoked response and the optimal time step to interact with the neuronal culture are key factors to uncover computational resources from the neuronal system. Close https://arinex.com.au/EMBC/pdf/full-paper_654.pdf Close
	Yamamoto, Hideaki; Hirano-Iwata, Ayumi; Sato, Shigeo Microfluidic technologies for reconstituting neuronal network functions in vitro Journal Article JSAP Review, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Microfluidics @article{Yamamoto2023, title = {Microfluidic technologies for reconstituting neuronal network functions in vitro}, author = {Hideaki Yamamoto and Ayumi Hirano-Iwata and Shigeo Sato}, url = {https://www.jstage.jst.go.jp/article/oubutsu/92/5/92_278/_article/-char/en}, doi = {10.11470/oubutsu.92.5_278}, year = {2023}, date = {2023-07-06}, journal = {JSAP Review}, abstract = {The structure and function of complex neuronal networks in the brain can be partially reconstituted in vitro by integrating cell culture and microfluidic device technologies. In this report, we review our recent studies on developing microfluidic devices to reconstitute small neuronal networks bearing a modular structure, which is a canonical structure found in the nervous systems of animals. We also describe the process of recording functional activity from the reconstituted neuronal networks. These fundamental technologies offer novel tools for investigating structure–function relationships in living neuronal networks and exploring the physical basis of biological computing in the brain.}, keywords = {2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Microfluidics}, pubstate = {published}, tppubtype = {article} } Close The structure and function of complex neuronal networks in the brain can be partially reconstituted in vitro by integrating cell culture and microfluidic device technologies. In this report, we review our recent studies on developing microfluidic devices to reconstitute small neuronal networks bearing a modular structure, which is a canonical structure found in the nervous systems of animals. We also describe the process of recording functional activity from the reconstituted neuronal networks. These fundamental technologies offer novel tools for investigating structure–function relationships in living neuronal networks and exploring the physical basis of biological computing in the brain. Close https://www.jstage.jst.go.jp/article/oubutsu/92/5/92_278/_article/-char/en doi:10.11470/oubutsu.92.5_278 Close
	McSweeney, Danny; English, Jay; Howell, Ethan; Ribbe, Fumiko; Pak, ChangHui Measuring Neuronal Network Activity Using Human Induced Neuronal Cells - Stem Cell-Based Neural Model Systems for Brain Disorders Book Chapter Methods in Molecular Biology, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Metrics, MEA Technology, Network Assay @inbook{McSweeney2023, title = {Measuring Neuronal Network Activity Using Human Induced Neuronal Cells - Stem Cell-Based Neural Model Systems for Brain Disorders}, author = {Danny McSweeney and Jay English and Ethan Howell and Fumiko Ribbe and ChangHui Pak}, url = {https://link.springer.com/protocol/10.1007/978-1-0716-3287-1_19}, year = {2023}, date = {2023-06-11}, publisher = {Methods in Molecular Biology}, abstract = {Synchronous firing of neurons, often referred to as “network activity” or “network bursting,” is an indication of a mature and synaptically connected network of neurons. We previously reported this phenomenon in 2D human neuronal in vitro models (McSweeney et al. iScience 25:105187, 2022). Using induced neurons (iNs) differentiated from human pluripotent stem cells (hPSCs) coupled with high-density microelectrodes arrays (HD-MEAs), we probed the underlying patterns of neuronal activity and found irregularities in network signaling across mutant states (McSweeney et al. iScience 25:105187, 2022). Here, we describe methods for plating cortical excitatory iNs differentiated from hPSCs on top of HD-MEAs and culturing iNs to maturity, examples of representative human wild-type Ngn2-iN data, and troubleshooting tips and tricks for the experimenter interested in integrating HD-MEAs into one’s research approach.}, keywords = {2D Neuronal Culture, Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Metrics, MEA Technology, Network Assay}, pubstate = {published}, tppubtype = {inbook} } Close Synchronous firing of neurons, often referred to as “network activity” or “network bursting,” is an indication of a mature and synaptically connected network of neurons. We previously reported this phenomenon in 2D human neuronal in vitro models (McSweeney et al. iScience 25:105187, 2022). Using induced neurons (iNs) differentiated from human pluripotent stem cells (hPSCs) coupled with high-density microelectrodes arrays (HD-MEAs), we probed the underlying patterns of neuronal activity and found irregularities in network signaling across mutant states (McSweeney et al. iScience 25:105187, 2022). Here, we describe methods for plating cortical excitatory iNs differentiated from hPSCs on top of HD-MEAs and culturing iNs to maturity, examples of representative human wild-type Ngn2-iN data, and troubleshooting tips and tricks for the experimenter interested in integrating HD-MEAs into one’s research approach. Close https://link.springer.com/protocol/10.1007/978-1-0716-3287-1_19 Close
	Zhao, Eric T; Hull, Jacob M; Hemed, Nofar Mintz; Ulusan, Hasan; Bartram, Julian; Zhang, Anqi; Wang, Pingyu; Pham, Albert; Silvia Ronchi, John Huguenard R; Hierlemann, Andreas; Melosh, Nicholas A A CMOS-based highly scalable flexible neural electrode interface Journal Article Science Advances, 2023. Abstract \| Links \| BibTeX \| Tags: 3D Culture, HD-MEA, MaxOne, Other Tissues, Slices @article{Zhao2023, title = {A CMOS-based highly scalable flexible neural electrode interface}, author = {Eric T. Zhao and Jacob M. Hull and Nofar Mintz Hemed and Hasan Ulusan and Julian Bartram and Anqi Zhang and Pingyu Wang and Albert Pham and Silvia Ronchi, John R. Huguenard and Andreas Hierlemann and Nicholas A. Melosh}, url = {https://www.science.org/doi/10.1126/sciadv.adf9524}, doi = {DOI: 10.1126/sciadv.adf9524}, year = {2023}, date = {2023-06-07}, journal = {Science Advances}, abstract = {Perception, thoughts, and actions are encoded by the coordinated activity of large neuronal populations spread over large areas. However, existing electrophysiological devices are limited by their scalability in capturing this cortex-wide activity. Here, we developed an electrode connector based on an ultra-conformable thin-film electrode array that self-assembles onto silicon microelectrode arrays enabling multithousand channel counts at a millimeter scale. The interconnects are formed using microfabricated electrode pads suspended by thin support arms, termed Flex2Chip. Capillary-assisted assembly drives the pads to deform toward the chip surface, and van der Waals forces maintain this deformation, establishing Ohmic contact. Flex2Chip arrays successfully measured extracellular action potentials ex vivo and resolved micrometer scale seizure propagation trajectories in epileptic mice. We find that seizure dynamics in absence epilepsy in the Scn8a+/− model do not have constant propagation trajectories.}, keywords = {3D Culture, HD-MEA, MaxOne, Other Tissues, Slices}, pubstate = {published}, tppubtype = {article} } Close Perception, thoughts, and actions are encoded by the coordinated activity of large neuronal populations spread over large areas. However, existing electrophysiological devices are limited by their scalability in capturing this cortex-wide activity. Here, we developed an electrode connector based on an ultra-conformable thin-film electrode array that self-assembles onto silicon microelectrode arrays enabling multithousand channel counts at a millimeter scale. The interconnects are formed using microfabricated electrode pads suspended by thin support arms, termed Flex2Chip. Capillary-assisted assembly drives the pads to deform toward the chip surface, and van der Waals forces maintain this deformation, establishing Ohmic contact. Flex2Chip arrays successfully measured extracellular action potentials ex vivo and resolved micrometer scale seizure propagation trajectories in epileptic mice. We find that seizure dynamics in absence epilepsy in the Scn8a+/− model do not have constant propagation trajectories. Close https://www.science.org/doi/10.1126/sciadv.adf9524 doi:DOI: 10.1126/sciadv.adf9524 Close
	Girardi, Gregory; Zumpano, Danielle; Goshi, Noah; Raybould, Helen; Seker, Erkin Cultured Vagal Afferent Neurons as Sensors for Intestinal Effector Molecules Journal Article biosensors, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture @article{Girardi2023, title = {Cultured Vagal Afferent Neurons as Sensors for Intestinal Effector Molecules}, author = {Gregory Girardi and Danielle Zumpano and Noah Goshi and Helen Raybould and Erkin Seker}, url = {https://www.mdpi.com/2079-6374/13/6/601}, doi = {10.3390/bios13060601}, year = {2023}, date = {2023-05-31}, journal = {biosensors}, abstract = {The gut–brain axis embodies the bi-directional communication between the gastrointestinal tract and the central nervous system (CNS), where vagal afferent neurons (VANs) serve as sensors for a variety of gut-derived signals. The gut is colonized by a large and diverse population of microorganisms that communicate via small (effector) molecules, which also act on the VAN terminals situated in the gut viscera and consequently influence many CNS processes. However, the convoluted in vivo environment makes it difficult to study the causative impact of the effector molecules on VAN activation or desensitization. Here, we report on a VAN culture and its proof-of-principle demonstration as a cell-based sensor to monitor the influence of gastrointestinal effector molecules on neuronal behavior. We initially compared the effect of surface coatings (poly-L-lysine vs. Matrigel) and culture media composition (serum vs. growth factor supplement) on neurite growth as a surrogate of VAN regeneration following tissue harvesting, where the Matrigel coating, but not the media composition, played a significant role in the increased neurite growth. We then used both live-cell calcium imaging and extracellular electrophysiological recordings to show that the VANs responded to classical effector molecules of endogenous and exogenous origin (cholecystokinin serotonin and capsaicin) in a complex fashion. We expect this study to enable platforms for screening various effector molecules and their influence on VAN activity, assessed by their information-rich electrophysiological fingerprints.}, keywords = {2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close The gut–brain axis embodies the bi-directional communication between the gastrointestinal tract and the central nervous system (CNS), where vagal afferent neurons (VANs) serve as sensors for a variety of gut-derived signals. The gut is colonized by a large and diverse population of microorganisms that communicate via small (effector) molecules, which also act on the VAN terminals situated in the gut viscera and consequently influence many CNS processes. However, the convoluted in vivo environment makes it difficult to study the causative impact of the effector molecules on VAN activation or desensitization. Here, we report on a VAN culture and its proof-of-principle demonstration as a cell-based sensor to monitor the influence of gastrointestinal effector molecules on neuronal behavior. We initially compared the effect of surface coatings (poly-L-lysine vs. Matrigel) and culture media composition (serum vs. growth factor supplement) on neurite growth as a surrogate of VAN regeneration following tissue harvesting, where the Matrigel coating, but not the media composition, played a significant role in the increased neurite growth. We then used both live-cell calcium imaging and extracellular electrophysiological recordings to show that the VANs responded to classical effector molecules of endogenous and exogenous origin (cholecystokinin serotonin and capsaicin) in a complex fashion. We expect this study to enable platforms for screening various effector molecules and their influence on VAN activity, assessed by their information-rich electrophysiological fingerprints. Close https://www.mdpi.com/2079-6374/13/6/601 doi:10.3390/bios13060601 Close
	Bartram, Julian; Franke, Felix; Kumar, Sreedhar Saseendran; Buccino, Alessio Paolo; Xue, Xiaohan; Gänswein, Tobias; Schröter, Manuel; Kim, Taehoon; Kasuba, Krishna Chaitanya; Hierlemann, Andreas Parallel reconstruction of the excitatory and inhibitory inputs received by single neurons reveals the synaptic basis of recurrent spiking Journal Article eLife, 2023. Abstract \| Links \| BibTeX \| Tags: HD-MEA, MaxOne, MEA Metrics, MEA Technology, Modeling, Primary Neuronal Cell Culture, Spike Sorting @article{Bartram2023b, title = {Parallel reconstruction of the excitatory and inhibitory inputs received by single neurons reveals the synaptic basis of recurrent spiking}, author = {Julian Bartram and Felix Franke and Sreedhar Saseendran Kumar and Alessio Paolo Buccino and Xiaohan Xue and Tobias Gänswein and Manuel Schröter and Taehoon Kim and Krishna Chaitanya Kasuba and Andreas Hierlemann}, url = {https://elifesciences.org/reviewed-preprints/86820}, doi = {10.7554/eLife.86820}, year = {2023}, date = {2023-05-17}, journal = {eLife}, abstract = {Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between the synaptic input patterns and the spiking output of individual neurons remains largely unresolved. Here, we developed, validated and applied a novel in vitro experimental platform and analytical procedures that provide – for individual neurons – simultaneous excitatory and inhibitory synaptic activity estimates during recurrent network activity. Our approach combines whole-network high-density microelectrode array (HD-MEA) recordings from rat neuronal cultures with patch clamping and enables a comprehensive mapping and characterization of active incoming connections to single postsynaptic neurons. We found that, during network states with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided precisely with the maxima of fast fluctuations in the input E/I ratio. These spike-associated E/I ratio escalations were largely due to a rapid bidirectional change in synaptic inhibition that was modulated by the network-activity level. Our approach also uncovered the underlying circuit architecture and we show that individual neurons received a few key inhibitory connections – often from special hub neurons – that were instrumental in controlling postsynaptic spiking. Balanced network theory predicts dynamical regimes governed by small and rapid input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of cortical networks in general.}, keywords = {HD-MEA, MaxOne, MEA Metrics, MEA Technology, Modeling, Primary Neuronal Cell Culture, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between the synaptic input patterns and the spiking output of individual neurons remains largely unresolved. Here, we developed, validated and applied a novel in vitro experimental platform and analytical procedures that provide – for individual neurons – simultaneous excitatory and inhibitory synaptic activity estimates during recurrent network activity. Our approach combines whole-network high-density microelectrode array (HD-MEA) recordings from rat neuronal cultures with patch clamping and enables a comprehensive mapping and characterization of active incoming connections to single postsynaptic neurons. We found that, during network states with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided precisely with the maxima of fast fluctuations in the input E/I ratio. These spike-associated E/I ratio escalations were largely due to a rapid bidirectional change in synaptic inhibition that was modulated by the network-activity level. Our approach also uncovered the underlying circuit architecture and we show that individual neurons received a few key inhibitory connections – often from special hub neurons – that were instrumental in controlling postsynaptic spiking. Balanced network theory predicts dynamical regimes governed by small and rapid input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of cortical networks in general. Close https://elifesciences.org/reviewed-preprints/86820 doi:10.7554/eLife.86820 Close
	Duru, Jens; Maurer, Benedikt; Doran, Ciara Giles; Jelitto, Robert; Küchler, Joël; Ihle, Stephan J; Ruff, Tobias; John, Robert; Genocchi, Barbara; Vörös, János Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays Journal Article SSRN, 2023. Abstract \| Links \| BibTeX \| Tags: HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Spike Sorting, Stimulation @article{Duru2023, title = {Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays}, author = {Jens Duru and Benedikt Maurer and Ciara Giles Doran and Robert Jelitto and Joël Küchler and Stephan J. Ihle and Tobias Ruff and Robert John and Barbara Genocchi and János Vörös}, url = {https://www.ssrn.com/abstract=4427959}, doi = {DOI: 10.2139/ssrn.4427959}, year = {2023}, date = {2023-04-24}, journal = {SSRN}, abstract = {Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks’ early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.}, keywords = {HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Spike Sorting, Stimulation}, pubstate = {published}, tppubtype = {article} } Close Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks’ early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation. Close https://www.ssrn.com/abstract=4427959 doi:DOI: 10.2139/ssrn.4427959 Close
	Cerina, Marta; Piastra, Maria Carla; Frega, Monica The potential of in vitro neuronal networks cultured on Micro Electrode Arrays for biomedical research Journal Article Progress in Biomedical Engineering, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, 3D Culture, Brain Slice, IPSC, MEA Technology, Organoids, Primary Neuronal Cell Culture @article{Cerina2023, title = {The potential of in vitro neuronal networks cultured on Micro Electrode Arrays for biomedical research}, author = {Marta Cerina and Maria Carla Piastra and Monica Frega}, url = {https://iopscience.iop.org/article/10.1088/2516-1091/acce12}, doi = {10.1088/2516-1091/acce12}, year = {2023}, date = {2023-04-18}, journal = {Progress in Biomedical Engineering}, abstract = {In vitro neuronal models have become an important tool to study healthy and diseased neuronal circuits. The growing interest of neuroscientists to explore the dynamics of neuronal systems and the increasing need to observe, measure and manipulate not only single neurons but populations of cells pushed for technological advancement. In this sense, Micro-Electrode Arrays (MEAs) emerged as a promising technique, made of cell culture dishes with embedded micro-electrodes allowing non-invasive and relatively simple measurement of the activity of neuronal cultures at the network level. In the past decade, MEAs popularity has rapidly grown. MEA devices have been extensively used to measure the activity of neuronal cultures mainly derived from rodents. Rodent neuronal cultures on MEAs have been employed to investigate physiological mechanisms, study the effect of chemicals in neurotoxicity screenings, and model the electrophysiological phenotype of neuronal networks in different pathological conditions. With the advancements in human induced pluripotent stem cells (hiPSCs) technology, the differentiation of human neurons from the cells of adult donors became possible. hiPSCsderived neuronal networks on MEAs have been employed to develop patient-specific in vitro platforms to characterize the pathophysiological phenotype and to test drugs, paving the way towards personalized medicine. In this review, we first describe MEA technology and the information that can be obtained from MEA recordings. Then, we give an overview of studies in which MEAs have been used in combination with different neuronal systems (i.e., rodent 2D and 3D neuronal cultures, organotypic brain slices, hiPSCs-derived 2D and 3D neuronal cultures, and brain organoids) for biomedical research, including physiology studies, neurotoxicity screenings, disease modeling, and drug testing. We end by discussing potential, challenges and future perspectives of MEA technology, and providing some guidance for the choice of the neuronal model and MEA device, experimental design, data analysis and reporting for scientific publications.}, keywords = {2D Neuronal Culture, 3D Culture, Brain Slice, IPSC, MEA Technology, Organoids, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close In vitro neuronal models have become an important tool to study healthy and diseased neuronal circuits. The growing interest of neuroscientists to explore the dynamics of neuronal systems and the increasing need to observe, measure and manipulate not only single neurons but populations of cells pushed for technological advancement. In this sense, Micro-Electrode Arrays (MEAs) emerged as a promising technique, made of cell culture dishes with embedded micro-electrodes allowing non-invasive and relatively simple measurement of the activity of neuronal cultures at the network level. In the past decade, MEAs popularity has rapidly grown. MEA devices have been extensively used to measure the activity of neuronal cultures mainly derived from rodents. Rodent neuronal cultures on MEAs have been employed to investigate physiological mechanisms, study the effect of chemicals in neurotoxicity screenings, and model the electrophysiological phenotype of neuronal networks in different pathological conditions. With the advancements in human induced pluripotent stem cells (hiPSCs) technology, the differentiation of human neurons from the cells of adult donors became possible. hiPSCsderived neuronal networks on MEAs have been employed to develop patient-specific in vitro platforms to characterize the pathophysiological phenotype and to test drugs, paving the way towards personalized medicine. In this review, we first describe MEA technology and the information that can be obtained from MEA recordings. Then, we give an overview of studies in which MEAs have been used in combination with different neuronal systems (i.e., rodent 2D and 3D neuronal cultures, organotypic brain slices, hiPSCs-derived 2D and 3D neuronal cultures, and brain organoids) for biomedical research, including physiology studies, neurotoxicity screenings, disease modeling, and drug testing. We end by discussing potential, challenges and future perspectives of MEA technology, and providing some guidance for the choice of the neuronal model and MEA device, experimental design, data analysis and reporting for scientific publications. Close https://iopscience.iop.org/article/10.1088/2516-1091/acce12 doi:10.1088/2516-1091/acce12 Close
	Xu, He Jax; Yao, Yao; Yao, Fenyong; Chen, Jiehui; Li, Meishi; Yang, Xianfa; Li, Sheng; Lu, Fangru; Hu, Ping; He, Shuijin; Peng, Guangdun; Jing, Naihe Generation of functional posterior spinal motor neurons from hPSCs-derived human spinal cord neural progenitor cells Journal Article Cell Regeneration, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, Activity Scan Assay, Axon Tracking Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Network Assay, Organoids @article{Xu2023, title = {Generation of functional posterior spinal motor neurons from hPSCs-derived human spinal cord neural progenitor cells}, author = {He Jax Xu and Yao Yao and Fenyong Yao and Jiehui Chen and Meishi Li and Xianfa Yang and Sheng Li and Fangru Lu and Ping Hu and Shuijin He and Guangdun Peng and Naihe Jing}, url = {https://cellregeneration.springeropen.com/articles/10.1186/s13619-023-00159-6}, doi = {10.1186/s13619-023-00159-6}, year = {2023}, date = {2023-03-23}, journal = {Cell Regeneration}, abstract = {Spinal motor neurons deficiency results in a series of devastating disorders such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA) and spinal cord injury (SCI). These disorders are currently incurable, while human pluripotent stem cells (hPSCs)-derived spinal motor neurons are promising but suffered from inappropriate regional identity and functional immaturity for the study and treatment of posterior spinal cord related injuries. In this study, we have established human spinal cord neural progenitor cells (hSCNPCs) via hPSCs differentiated neuromesodermal progenitors (NMPs) and demonstrated the hSCNPCs can be continuously expanded up to 40 passages. hSCNPCs can be rapidly differentiated into posterior spinal motor neurons with high efficiency. The functional maturity has been examined in detail. Moreover, a co-culture scheme which is compatible for both neural and muscular differentiation is developed to mimic the neuromuscular junction (NMJ) formation in vitro. Together, these studies highlight the potential avenues for generating clinically relevant spinal motor neurons and modeling neuromuscular diseases through our defined hSCNPCs.}, keywords = {2D Neuronal Culture, Activity Scan Assay, Axon Tracking Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Network Assay, Organoids}, pubstate = {published}, tppubtype = {article} } Close Spinal motor neurons deficiency results in a series of devastating disorders such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA) and spinal cord injury (SCI). These disorders are currently incurable, while human pluripotent stem cells (hPSCs)-derived spinal motor neurons are promising but suffered from inappropriate regional identity and functional immaturity for the study and treatment of posterior spinal cord related injuries. In this study, we have established human spinal cord neural progenitor cells (hSCNPCs) via hPSCs differentiated neuromesodermal progenitors (NMPs) and demonstrated the hSCNPCs can be continuously expanded up to 40 passages. hSCNPCs can be rapidly differentiated into posterior spinal motor neurons with high efficiency. The functional maturity has been examined in detail. Moreover, a co-culture scheme which is compatible for both neural and muscular differentiation is developed to mimic the neuromuscular junction (NMJ) formation in vitro. Together, these studies highlight the potential avenues for generating clinically relevant spinal motor neurons and modeling neuromuscular diseases through our defined hSCNPCs. Close https://cellregeneration.springeropen.com/articles/10.1186/s13619-023-00159-6 doi:10.1186/s13619-023-00159-6 Close
	Radivojevic, Milos; Punga, Anna Rostedt Functional imaging of conduction dynamics in cortical and spinal axons Journal Article BioRxiv, 2023. Abstract \| Links \| BibTeX \| Tags: MaxOne @article{Radivojevic2023, title = {Functional imaging of conduction dynamics in cortical and spinal axons}, author = {Milos Radivojevic and Anna Rostedt Punga}, url = {https://www.biorxiv.org/content/10.1101/2023.02.28.530461v1}, doi = {https://doi.org/10.1101/2023.02.28.530461}, year = {2023}, date = {2023-03-01}, journal = {BioRxiv}, abstract = {Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-centimeter-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 meters of cortical and spinal axons in total and found specific features in their structure and function.}, keywords = {MaxOne}, pubstate = {published}, tppubtype = {article} } Close Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-centimeter-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 meters of cortical and spinal axons in total and found specific features in their structure and function. Close https://www.biorxiv.org/content/10.1101/2023.02.28.530461v1 doi:https://doi.org/10.1101/2023.02.28.530461 Close

204 entries « ‹ 1 of 5 › »

Selected Publications

High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels

Presenting measurements of neuronal preparations with a novel CMOS-based microelectrode array at high-spatiotemporal-resolution on subcellular, cellular, and network level.

J. Müller, M. Ballini, P. Livi, Y. Chen, M. Radivojevic, A. Shadmani, V. Viswam, I. L. Jones, M. Fiscella, R. Diggelmann, A. Stettler, U. Frey, D. J. Bakkum, and A. Hierlemann, “High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels,” Lab Chip, vol. 15, no. 13, pp. 2767–2780, May 2015.

Revealing Neuronal Function through Microelectrode Array Recordings

Reviewing the current understanding of microelectrode signals and the techniques for analyzing them, with focus on the ongoing advancements in microelectrode technology (in vivo and in vitro) and recent advanced microelectrode array measurement methods that facilitate the understanding of single neurons and network function.

M. E. J. Obien, K. Deligkaris, T. Bullmann, D. J. Bakkum, and U. Frey, “Revealing Neuronal Function through Microelectrode Array Recordings,” Front. Neurosci., 8:423, Jan 2015.

A 1024-Channel CMOS Microelectrode Array With 26,400 Electrodes for Recording and Stimulation of Electrogenic Cells In Vitro

A high-resolution CMOS-based microelectrode array featuring 1,024 low-noise readout channels, 26,400 electrodes at a density of 3,265 electrodes per mm², including on-chip 10bit ADCs and consuming only 75 mW.

M. Ballini, J. Muller, P. Livi, Y. Chen, U. Frey, A. Stettler, A. Shadmani, V. Viswam, I. L. Jones, D. Jackel, M. Radivojevic, M. K. Lewandowska, W. Gong, M. Fiscella, D. J. Bakkum, F. Heer, and A. Hierlemann, “A 1024-Channel CMOS Microelectrode Array With 26,400 Electrodes for Recording and Stimulation of Electrogenic Cells In Vitro,” IEEE Journal of Solid-State Circuits, vol. 49, no. 11, pp. 2705-2719, 2014.

Tracking axonal action potential propagation on a high-density microelectrode array across hundreds of sites

Demonstrating a method to electrically visualize action potential propagation on axons and revealing
large variations in velocity.

D. J. Bakkum, U. Frey, M. Radivojevic, T. L. Russell, J. Muller, M. Fiscella, H. Takahashi, and A. Hierlemann, “Tracking axonal action potential propagation on a high-density microelectrode array across hundreds of sites,” Nature Communications, 4:2181, Jul 2013.

Microelectronic System for High-Resolution Mapping of Extracellular Electric Fields Applied to Brain Slices

Recording and modeling extracellular action potentials of Purkinje cells at subcellular resolution.

U. Frey, U. Egert, F. Heer, S. Hafizovic, and A. Hierlemann, “Microelectronic System for High-Resolution Mapping of Extracellular Electric Fields Applied to Brain Slices,” Biosensors and Bioelectronics, vol. 24, no. 7, pp. 2191-2198, 2009.

Modulation of Cardiomyocyte Electrical Properties Using Regulated Bone Morphogenetic Protein-2 Expression

Controlling BMP-2 expression to modulate the electrophysiological properties of cardiomyocytes using an HD-MEA for detailed monitoring.

C. D. Sanchez-Bustamante, U. Frey, J. M. Kelm, A. Hierlemann, and M. Fussenegger,
“Modulation of Cardiomyocyte Electrical Properties Using Regulated Bone Morphogenetic Protein-2 Expression,” Tissue Engineering Part A, vol. 14, no. 12, pp. 1969-1988, 2008.

2024
	Zhang, Xinyu; Burattini, Margherita; Duru, Jens; Chala, Nafsika; Wyssen, Nino; Cofiño-Fabres, Carla; Rivera-Arbeláez, José Manuel; Passier, Robert; Poulikakos, Dimos; Aldo Ferrari, Christina Tringides ; Vörös, János; Luciani, Giovanni Battista; Miragoli, Michele; Zambelli, Tomaso Multimodal Mapping of Electrical and Mechanical Latency of Human-Induced Pluripotent Stem Cell-Derived Cardiomyocyte Layers Journal Article ACS Nano, 2024, ISSN: 1936-0851. Abstract \| Links \| BibTeX \| Tags: Cardiomyocytes, HD-MEA, IPSC, MaxOne, MEA Technology @article{Zhang2024, title = {Multimodal Mapping of Electrical and Mechanical Latency of Human-Induced Pluripotent Stem Cell-Derived Cardiomyocyte Layers}, author = {Xinyu Zhang and Margherita Burattini and Jens Duru and Nafsika Chala and Nino Wyssen and Carla Cofiño-Fabres and José Manuel Rivera-Arbeláez and Robert Passier and Dimos Poulikakos and Aldo Ferrari, Christina Tringides and János Vörös and Giovanni Battista Luciani and Michele Miragoli and Tomaso Zambelli}, url = {https://doi.org/10.1021/acsnano.4c03896}, doi = {10.1021/acsnano.4c03896}, issn = {1936-0851}, year = {2024}, date = {2024-08-22}, journal = {ACS Nano}, abstract = {The synchronization of the electrical and mechanical coupling assures the physiological pump function of the heart, but life-threatening pathologies may jeopardize this equilibrium. Recently, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a model for personalized investigation because they can recapitulate human diseased traits, such as compromised electrical capacity or mechanical circuit disruption. This research avails the model of hiPSC-CMs and showcases innovative techniques to study the electrical and mechanical properties as well as their modulation due to inherited cardiomyopathies. In this work, hiPSC-CMs carrying either Brugada syndrome (BRU) or dilated cardiomyopathy (DCM), were organized in a bilayer configuration to first validate the experimental methods and second mimic the physiological environment. High-density CMOS-based microelectrode arrays (HD-MEA) have been employed to study the electrical activity. Furthermore, mechanical function was investigated via quantitative video-based evaluation, upon stimulation with a β-adrenergic agonist. This study introduces two experimental methods. First, high-throughput mechanical measurements in the hiPSC-CM layers (xy-inspection) are obtained using both a recently developed optical tracker (OPT) and confocal reference-free traction force microscopy (cTFM) aimed to quantify cardiac kinematics. Second, atomic force microscopy (AFM) with FluidFM probes, combined with the xy-inspection methods, supplemented a three-dimensional understanding of cell−cell mechanical coupling (xyz-inspection). This particular combination represents amulti-technique approach to detecting electrical and mechanical latency among the cell layers, examining differences and possible implications following inherited cardiomyopathies. It can not only detect disease characteristics in the proposed in vitro model but also quantitatively assess its response to drugs, thereby demonstrating its feasibility as ascalable tool for clinical and pharmacological studies.}, keywords = {Cardiomyocytes, HD-MEA, IPSC, MaxOne, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close The synchronization of the electrical and mechanical coupling assures the physiological pump function of the heart, but life-threatening pathologies may jeopardize this equilibrium. Recently, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a model for personalized investigation because they can recapitulate human diseased traits, such as compromised electrical capacity or mechanical circuit disruption. This research avails the model of hiPSC-CMs and showcases innovative techniques to study the electrical and mechanical properties as well as their modulation due to inherited cardiomyopathies. In this work, hiPSC-CMs carrying either Brugada syndrome (BRU) or dilated cardiomyopathy (DCM), were organized in a bilayer configuration to first validate the experimental methods and second mimic the physiological environment. High-density CMOS-based microelectrode arrays (HD-MEA) have been employed to study the electrical activity. Furthermore, mechanical function was investigated via quantitative video-based evaluation, upon stimulation with a β-adrenergic agonist. This study introduces two experimental methods. First, high-throughput mechanical measurements in the hiPSC-CM layers (xy-inspection) are obtained using both a recently developed optical tracker (OPT) and confocal reference-free traction force microscopy (cTFM) aimed to quantify cardiac kinematics. Second, atomic force microscopy (AFM) with FluidFM probes, combined with the xy-inspection methods, supplemented a three-dimensional understanding of cell−cell mechanical coupling (xyz-inspection). This particular combination represents amulti-technique approach to detecting electrical and mechanical latency among the cell layers, examining differences and possible implications following inherited cardiomyopathies. It can not only detect disease characteristics in the proposed in vitro model but also quantitatively assess its response to drugs, thereby demonstrating its feasibility as ascalable tool for clinical and pharmacological studies. Close https://doi.org/10.1021/acsnano.4c03896 doi:10.1021/acsnano.4c03896 Close
	Cartiglia, Matteo; Costa, Filippo; Narayanan, Shyam; Bui, Cat-Vu H; Ulusan, Hasan; Risia, Nicoletta; Haessig, Germain; Hierlemann, Andreas; Cardes, Fernando; Indiveri, Giacomo A 4096 Channel Event-based Multielectrode Array with Asynchronous Outputs Compatible with Neuromorphic Processors Journal Article Nature Communications, 2024. Abstract \| Links \| BibTeX \| Tags: ETH-CMOS-MEA, MEA Technology @article{Cartiglia2024, title = {A 4096 Channel Event-based Multielectrode Array with Asynchronous Outputs Compatible with Neuromorphic Processors}, author = {Matteo Cartiglia and Filippo Costa and Shyam Narayanan and Cat-Vu H. Bui and Hasan Ulusan and Nicoletta Risia and Germain Haessig and Andreas Hierlemann and Fernando Cardes and Giacomo Indiveri}, url = {https://www.nature.com/articles/s41467-024-50783-2}, doi = {10.1038/s41467-024-50783-2}, year = {2024}, date = {2024-08-21}, journal = {Nature Communications}, abstract = {io-signal sensing is pivotal in medical bioelectronics. Traditional methods focus on high sampling rates, leading to large amounts of irrelevant data and high energy consumption. We introduce a self-clocked microelectrode array (MEA) that digitizes bio-signals at the pixel level by encoding changes as asynchronous digital address-events only when they exceed a threshold, significantly reducing off-chip data transmission. This novel MEA comprises a 64 × 64 electrode array, an asynchronous 2D-arbiter, and an Address-Event Representation (AER) communication block. Each pixel operates autonomously, monitoring voltage fluctuations from cellular activity and producing digital pulses for significant changes. Positive and negative signal changes are encoded as “up” and “down” events and are routed off-chip via the asynchronous arbiter. We present results from chip characterization and experimental measurements using electrogenic cells. Additionally, we interface the MEA to a mixed-signal neuromorphic processor, demonstrating a prototype for end-to-end event-based bio-signal sensing and processing.}, keywords = {ETH-CMOS-MEA, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close io-signal sensing is pivotal in medical bioelectronics. Traditional methods focus on high sampling rates, leading to large amounts of irrelevant data and high energy consumption. We introduce a self-clocked microelectrode array (MEA) that digitizes bio-signals at the pixel level by encoding changes as asynchronous digital address-events only when they exceed a threshold, significantly reducing off-chip data transmission. This novel MEA comprises a 64 × 64 electrode array, an asynchronous 2D-arbiter, and an Address-Event Representation (AER) communication block. Each pixel operates autonomously, monitoring voltage fluctuations from cellular activity and producing digital pulses for significant changes. Positive and negative signal changes are encoded as “up” and “down” events and are routed off-chip via the asynchronous arbiter. We present results from chip characterization and experimental measurements using electrogenic cells. Additionally, we interface the MEA to a mixed-signal neuromorphic processor, demonstrating a prototype for end-to-end event-based bio-signal sensing and processing. Close https://www.nature.com/articles/s41467-024-50783-2 doi:10.1038/s41467-024-50783-2 Close
	Lee, Jihyun; Duperrex, Eliane; El-Battrawy, Ibrahim; Hohn, Alyssa; M., Ardan; Saguner, ; Duru, Firat; Emmenegger, Vishalini; Cyganek, Lukas; Hierlemann, Andreas; Ulusan, Hasan CardioMEA: Comprehensive Data Analysis Platform for Studying Cardiac Diseases and Drug Responses Journal Article bioRxiv, 2024. Abstract \| Links \| BibTeX \| Tags: Cardiomyocytes, IPSC, MEA Technology @article{Lee2024, title = {CardioMEA: Comprehensive Data Analysis Platform for Studying Cardiac Diseases and Drug Responses}, author = {Jihyun Lee and Eliane Duperrex and Ibrahim El-Battrawy and Alyssa Hohn and Ardan M. and Saguner and Firat Duru and Vishalini Emmenegger and Lukas Cyganek and Andreas Hierlemann and Hasan Ulusan}, url = {https://www.biorxiv.org/content/10.1101/2024.07.28.605490v1}, doi = {10.1101/2024.07.28.605490}, year = {2024}, date = {2024-07-29}, journal = {bioRxiv}, abstract = {In recent years, high-density microelectrode arrays (HD-MEAs) have emerged as a 25 valuable tool in preclinical research for characterizing the electrophysiology of human 26 induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). HD-MEAs enable the 27 capturing of both extracellular and intracellular signals on a large scale, while minimizing 28 potential damage to the cell. However, a gap exists between technological advancements 29 of HD-MEAs and the availability of effective data-analysis platforms. To address this 30 need, we introduce CardioMEA, a comprehensive data-analysis platform designed 31 specifically for HD-MEA data that have been obtained from iPSC-CMs. CardioMEA 32 features scalable data processing pipelines and an interactive web-based dashboard for 33 advanced visualization and analysis. In addition to its core functionalities, CardioMEA incorporates modules designed to discern crucial electrophysiological features between diseased and healthy iPSC-CMs. Notably, CardioMEA has the unique capability to analyze both extracellular and intracellular signals, thereby facilitating customized analyses for specific research tasks. We demonstrate the practical application of CardioMEA by analyzing electrophysiological signals from iPSC-CM cultures exposed to seven antiarrhythmic drugs. CardioMEA holds great potential as an intuitive, user-friendly platform for studying cardiac diseases and assessing drug effects.}, keywords = {Cardiomyocytes, IPSC, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close In recent years, high-density microelectrode arrays (HD-MEAs) have emerged as a 25 valuable tool in preclinical research for characterizing the electrophysiology of human 26 induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). HD-MEAs enable the 27 capturing of both extracellular and intracellular signals on a large scale, while minimizing 28 potential damage to the cell. However, a gap exists between technological advancements 29 of HD-MEAs and the availability of effective data-analysis platforms. To address this 30 need, we introduce CardioMEA, a comprehensive data-analysis platform designed 31 specifically for HD-MEA data that have been obtained from iPSC-CMs. CardioMEA 32 features scalable data processing pipelines and an interactive web-based dashboard for 33 advanced visualization and analysis. In addition to its core functionalities, CardioMEA incorporates modules designed to discern crucial electrophysiological features between diseased and healthy iPSC-CMs. Notably, CardioMEA has the unique capability to analyze both extracellular and intracellular signals, thereby facilitating customized analyses for specific research tasks. We demonstrate the practical application of CardioMEA by analyzing electrophysiological signals from iPSC-CM cultures exposed to seven antiarrhythmic drugs. CardioMEA holds great potential as an intuitive, user-friendly platform for studying cardiac diseases and assessing drug effects. Close https://www.biorxiv.org/content/10.1101/2024.07.28.605490v1 doi:10.1101/2024.07.28.605490 Close
	Hoang, Huu; Matsumoto, Nobuyoshi; Miyano, Miyuki; Ikegaya, Yuji; Cortese, Aurelio Dopamine-induced Relaxation of Connectivity Diversifies Burst Patterns in Cultured Hippocampal Networks Journal Article bioRxiv, 2024. Abstract \| Links \| BibTeX \| Tags: Activity Scan Assay, HD-MEA, MaxOne, MEA Technology, Network Assay, Neuronal Networks, Primary Neuronal Cell Culture @article{Hoang2024, title = {Dopamine-induced Relaxation of Connectivity Diversifies Burst Patterns in Cultured Hippocampal Networks}, author = {Huu Hoang and Nobuyoshi Matsumoto and Miyuki Miyano and Yuji Ikegaya and Aurelio Cortese}, url = {https://www.biorxiv.org/content/10.1101/2024.06.26.600923v1}, doi = {10.1101/2024.06.26.600923}, year = {2024}, date = {2024-06-30}, journal = {bioRxiv}, abstract = {The intricate interplay of neurotransmitters orchestrates a symphony of neural activity in the hippocampus, with dopamine emerging as a key conductor in this complex ensemble. Despite numerous studies uncovering the cellular mechanisms of dopamine, its influence on hippocampal neural networks remains elusive. Combining in vitro electrophysiological recordings of rat embryonic hippocampal neurons, pharmacological interventions, and computational analyses of spike trains, we found that dopamine induces a relaxation in network connectivity, characterised by a reduction in spike coherence. This relaxation expands the repertoire of burst dynamics within these hippocampal networks, a phenomenon notably absent under the administration of dopamine antagonists. Our study provides a thorough understanding of the roles of dopamine signalling in shaping functional networks of hippocampal neurons.}, keywords = {Activity Scan Assay, HD-MEA, MaxOne, MEA Technology, Network Assay, Neuronal Networks, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close The intricate interplay of neurotransmitters orchestrates a symphony of neural activity in the hippocampus, with dopamine emerging as a key conductor in this complex ensemble. Despite numerous studies uncovering the cellular mechanisms of dopamine, its influence on hippocampal neural networks remains elusive. Combining in vitro electrophysiological recordings of rat embryonic hippocampal neurons, pharmacological interventions, and computational analyses of spike trains, we found that dopamine induces a relaxation in network connectivity, characterised by a reduction in spike coherence. This relaxation expands the repertoire of burst dynamics within these hippocampal networks, a phenomenon notably absent under the administration of dopamine antagonists. Our study provides a thorough understanding of the roles of dopamine signalling in shaping functional networks of hippocampal neurons. Close https://www.biorxiv.org/content/10.1101/2024.06.26.600923v1 doi:10.1101/2024.06.26.600923 Close
	Beaubois, Romain; Cheslet, Jérémy; Duenki, Tomoya; Venuto, Giuseppe De; Carè, Marta; Khoyratee, Farad; Chiappalone, Michela; Branchereau, Pascal; Ikeuchi, Yoshiho; Levi, Timothée BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network Journal Article Nature Communications, 2024. Abstract \| Links \| BibTeX \| Tags: Activity Scan Assay, closed loop stimulation, HD-MEA, IPSC, MaxOne, MEA Technology, Modeling, Organoids, Stimulation @article{Beaubois2024, title = {BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network}, author = {Romain Beaubois and Jérémy Cheslet and Tomoya Duenki and Giuseppe De Venuto and Marta Carè and Farad Khoyratee and Michela Chiappalone and Pascal Branchereau and Yoshiho Ikeuchi and Timothée Levi }, url = {https://www.nature.com/articles/s41467-024-48905-x}, doi = {10.1038/s41467-024-48905-x}, year = {2024}, date = {2024-06-20}, journal = {Nature Communications}, abstract = {Characterization and modeling of biological neural networks has emerged as a field driving significant advancements in our understanding of brain function and related pathologies. As of today, pharmacological treatments for neurological disorders remain limited, pushing the exploration of promising alternative approaches such as electroceutics. Recent research in bioelectronics and neuromorphic engineering have fostered the development of the new generation of neuroprostheses for brain repair. However, achieving their full potential necessitates a deeper understanding of biohybrid interaction. In this study, we present a novel real-time, biomimetic, cost-effective and user-friendly neural network capable of real-time emulation for biohybrid experiments. Our system facilitates the investigation and replication of biophysically detailed neural network dynamics while prioritizing cost-efficiency, flexibility and ease of use. We showcase the feasibility of conducting biohybrid experiments using standard biophysical interfaces and a variety of biological cells as well as real-time emulation of diverse network configurations. We envision our system as a crucial step towards the development of neuromorphic-based neuroprostheses for bioelectrical therapeutics, enabling seamless communication with biological networks on a comparable timescale. Its embedded real-time functionality enhances practicality and accessibility, amplifying its potential for real-world applications in biohybrid experiments.}, keywords = {Activity Scan Assay, closed loop stimulation, HD-MEA, IPSC, MaxOne, MEA Technology, Modeling, Organoids, Stimulation}, pubstate = {published}, tppubtype = {article} } Close Characterization and modeling of biological neural networks has emerged as a field driving significant advancements in our understanding of brain function and related pathologies. As of today, pharmacological treatments for neurological disorders remain limited, pushing the exploration of promising alternative approaches such as electroceutics. Recent research in bioelectronics and neuromorphic engineering have fostered the development of the new generation of neuroprostheses for brain repair. However, achieving their full potential necessitates a deeper understanding of biohybrid interaction. In this study, we present a novel real-time, biomimetic, cost-effective and user-friendly neural network capable of real-time emulation for biohybrid experiments. Our system facilitates the investigation and replication of biophysically detailed neural network dynamics while prioritizing cost-efficiency, flexibility and ease of use. We showcase the feasibility of conducting biohybrid experiments using standard biophysical interfaces and a variety of biological cells as well as real-time emulation of diverse network configurations. We envision our system as a crucial step towards the development of neuromorphic-based neuroprostheses for bioelectrical therapeutics, enabling seamless communication with biological networks on a comparable timescale. Its embedded real-time functionality enhances practicality and accessibility, amplifying its potential for real-world applications in biohybrid experiments. Close https://www.nature.com/articles/s41467-024-48905-x doi:10.1038/s41467-024-48905-x Close
	Buccino, Alessio Paolo; Damart, Tanguy; Bartram, Julian; Mandge, Darshan; Xue, Xiaohan; Zbili, Mickael; Gänswein, Tobias; Jaquier, Aurélien; Emmenegger, Vishalini; Markram, Henry; Hierlemann, Andreas; Geit, Werner Van A Multimodal Fitting Approach to Construct Single-Neuron Models with Patch Clamp and High-Density Microelectrode Arrays Journal Article Neural Computation (MIT Press), 2024. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, ETH-CMOS-MEA, HD-MEA, MEA Metrics, MEA Technology @article{Buccino2024, title = {A Multimodal Fitting Approach to Construct Single-Neuron Models with Patch Clamp and High-Density Microelectrode Arrays}, author = {Alessio Paolo Buccino and Tanguy Damart and Julian Bartram and Darshan Mandge and Xiaohan Xue and Mickael Zbili and Tobias Gänswein and Aurélien Jaquier and Vishalini Emmenegger and Henry Markram and Andreas Hierlemann and Werner Van Geit}, url = {https://direct.mit.edu/neco/article/doi/10.1162/neco_a_01672/121124/A-Multimodal-Fitting-Approach-to-Construct-Single}, doi = {10.1162/neco_a_01672}, year = {2024}, date = {2024-06-07}, journal = {Neural Computation (MIT Press)}, abstract = {In computational neuroscience, multicompartment models are among the most biophysically realistic representations of single neurons. Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions. The experimental data are then used to fit the many parameters of the model. While patching of the soma is currently the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections. Recording from the soma alone makes it hard to observe and correctly parameterize the activity of nonsomatic compartments. In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density microelectrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at subcellular resolution. In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models. We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone. We also demonstrate our procedure using experimental data by constructing cell models from in vitro cell cultures. The proposed multimodal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and provide the field with neuronal models that are more realistic and can be better validated.}, keywords = {2D Neuronal Culture, ETH-CMOS-MEA, HD-MEA, MEA Metrics, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close In computational neuroscience, multicompartment models are among the most biophysically realistic representations of single neurons. Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions. The experimental data are then used to fit the many parameters of the model. While patching of the soma is currently the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections. Recording from the soma alone makes it hard to observe and correctly parameterize the activity of nonsomatic compartments. In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density microelectrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at subcellular resolution. In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models. We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone. We also demonstrate our procedure using experimental data by constructing cell models from in vitro cell cultures. The proposed multimodal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and provide the field with neuronal models that are more realistic and can be better validated. Close https://direct.mit.edu/neco/article/doi/10.1162/neco_a_01672/121124/A-Multimodal[...] doi:10.1162/neco_a_01672 Close
	Servais, Bram; Mahmoudi, Negar; Gautam, Vini; Tong, Wei; Ibbotson, Michael R; Nisbet, David R; Collins, David Engineering Brain-on-a-Chip Platforms Journal Article Nature Reviews Bioengineering, 2024. Abstract \| Links \| BibTeX \| Tags: 3D Culture, MEA Technology @article{Servais2024, title = {Engineering Brain-on-a-Chip Platforms}, author = {Bram Servais and Negar Mahmoudi and Vini Gautam and Wei Tong and Michael R. Ibbotson and David R. Nisbet and David Collins}, url = {https://www.nature.com/articles/s44222-024-00184-3}, doi = {10.1038/s44222-024-00184-3}, year = {2024}, date = {2024-06-05}, journal = {Nature Reviews Bioengineering}, abstract = {The increasing prevalence of neurological and psychiatric diseases, such as Alzheimer disease and schizophrenia, necessitates the development of new research tools to investigate these diseases and develop effective treatments. Thus, in vitro brain models, such as brain-on-a-chip devices, have been developed to mimic in vivo biochemical and mechanobiological interactions and to monitor their electrochemical activity. In this Review, we discuss the technologies to build complex brain models. We discuss progress in microfluidic and semiconductor-based technologies that facilitate in vitro modelling of the blood–brain barrier and neuronal circuits to study pathophysiological processes. We further discuss advances in 3D tissue engineering, electrode strategies and materials that, when combined, could allow simulation of the native complexity of brain regions and the interrogation of their activity at cellular length scales. Furthermore, we explore the engineering challenges and opportunities for complex physiologically relevant brain-on-a-chip devices and their future progress.}, keywords = {3D Culture, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close The increasing prevalence of neurological and psychiatric diseases, such as Alzheimer disease and schizophrenia, necessitates the development of new research tools to investigate these diseases and develop effective treatments. Thus, in vitro brain models, such as brain-on-a-chip devices, have been developed to mimic in vivo biochemical and mechanobiological interactions and to monitor their electrochemical activity. In this Review, we discuss the technologies to build complex brain models. We discuss progress in microfluidic and semiconductor-based technologies that facilitate in vitro modelling of the blood–brain barrier and neuronal circuits to study pathophysiological processes. We further discuss advances in 3D tissue engineering, electrode strategies and materials that, when combined, could allow simulation of the native complexity of brain regions and the interrogation of their activity at cellular length scales. Furthermore, we explore the engineering challenges and opportunities for complex physiologically relevant brain-on-a-chip devices and their future progress. Close https://www.nature.com/articles/s44222-024-00184-3 doi:10.1038/s44222-024-00184-3 Close
	Sifringer, Léo; Fratzl, Alex; Clément, Blandine F; Chansoria, Parth; Mönkemöller, Leah S; Duru, Jens; Ihle, Stephan J; Steffens, Simon; Beltraminelli, Anna; Ceylan, Eylul; Hengsteler, Julian; Maurer, Benedikt; Weaver, Sean M; Tringides, Christina M; Vulić, Katarina; Madduri, Srinivas; Zenobi-Wong, Marcy; Roska, Botond; Vörös, János; Ruff, Tobias An implantable biohybrid nerve model towards synaptic deep brain stimulation Journal Article bioRxiv, 2024. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, 3D Culture, CMOS, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Retina @article{Sifringer2024, title = {An implantable biohybrid nerve model towards synaptic deep brain stimulation}, author = {Léo Sifringer and Alex Fratzl and Blandine F. Clément and Parth Chansoria and Leah S. Mönkemöller and Jens Duru and Stephan J. Ihle and Simon Steffens and Anna Beltraminelli and Eylul Ceylan and Julian Hengsteler and Benedikt Maurer and Sean M. Weaver and Christina M. Tringides and Katarina Vulić and Srinivas Madduri and Marcy Zenobi-Wong and Botond Roska and János Vörös and Tobias Ruff}, url = {http://biorxiv.org/lookup/doi/10.1101/2024.05.31.596665}, doi = {10.1101/2024.05.31.596665}, year = {2024}, date = {2024-06-03}, journal = {bioRxiv}, abstract = {Restoring functional vision in blind patients lacking a healthy optic nerve requires bypassing retinal circuits, ideally, by directly stimulating the visual thalamus. However, available deep brain stimulation electrodes do not provide the resolution required for vision restoration. We developed an implantable biohybrid nerve model designed for synaptic stimulation of deep brain targets. The interface combines a stretchable stimulation array with an aligned microfluidic axon guidance system seeded with neural spheroids to facilitate the development of a 3 mm long nerve-like structure. A bioresorbable hydrogel nerve conduit was used as a bridge between the tissue and the biohybrid implant. We demonstrated stimulation of spheroids within the biohybrid structure in vitro and used high-density CMOS microelectrode arrays to show faithful activity conduction across the device. Finally, implantation of the biohybrid nerve onto the mouse cortex showed that neural spheroids grow axons in vivo and remain functionally active for more than 22 days post-implantation.}, keywords = {2D Neuronal Culture, 3D Culture, CMOS, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Retina}, pubstate = {published}, tppubtype = {article} } Close Restoring functional vision in blind patients lacking a healthy optic nerve requires bypassing retinal circuits, ideally, by directly stimulating the visual thalamus. However, available deep brain stimulation electrodes do not provide the resolution required for vision restoration. We developed an implantable biohybrid nerve model designed for synaptic stimulation of deep brain targets. The interface combines a stretchable stimulation array with an aligned microfluidic axon guidance system seeded with neural spheroids to facilitate the development of a 3 mm long nerve-like structure. A bioresorbable hydrogel nerve conduit was used as a bridge between the tissue and the biohybrid implant. We demonstrated stimulation of spheroids within the biohybrid structure in vitro and used high-density CMOS microelectrode arrays to show faithful activity conduction across the device. Finally, implantation of the biohybrid nerve onto the mouse cortex showed that neural spheroids grow axons in vivo and remain functionally active for more than 22 days post-implantation. Close http://biorxiv.org/lookup/doi/10.1101/2024.05.31.596665 doi:10.1101/2024.05.31.596665 Close
	Khajehnejad, Moein; Habibollahi, Forough; Paul, Aswin; Razi, Adeel; Kagan, Brett J Biological Neurons Compete with Deep Reinforcement Learning in Sample Efficiency in a Simulated Gameworld Journal Article arXiv , 2024. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, closed loop stimulation, HD-MEA, IPSC, Machine Learning, MaxOne, Modeling, Primary Neuronal Cell Culture @article{Khajehnejad2024, title = {Biological Neurons Compete with Deep Reinforcement Learning in Sample Efficiency in a Simulated Gameworld}, author = {Moein Khajehnejad and Forough Habibollahi and Aswin Paul and Adeel Razi and Brett J. Kagan}, url = {http://arxiv.org/abs/2405.16946}, doi = { https://doi.org/10.48550/arXiv.2405.16946}, year = {2024}, date = {2024-05-27}, journal = {arXiv }, abstract = {How do biological systems and machine learning algorithms compare in the number of samples required to show significant improvements in completing a task? We compared the learning efficiency of in vitro biological neural networks to the state-of-the-art deep reinforcement learning (RL) algorithms in a simplified simulation of the game `Pong'. Using DishBrain, a system that embodies in vitro neural networks with in silico computation using a high-density multi-electrode array, we contrasted the learning rate and the performance of these biological systems against time-matched learning from three state-of-the-art deep RL algorithms (i.e., DQN, A2C, and PPO) in the same game environment. This allowed a meaningful comparison between biological neural systems and deep RL. We find that when samples are limited to a real-world time course, even these very simple biological cultures outperformed deep RL algorithms across various game performance characteristics, implying a higher sample efficiency. Ultimately, even when tested across multiple types of information input to assess the impact of higher dimensional data input, biological neurons showcased faster learning than all deep reinforcement learning agents.}, keywords = {2D Neuronal Culture, closed loop stimulation, HD-MEA, IPSC, Machine Learning, MaxOne, Modeling, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close How do biological systems and machine learning algorithms compare in the number of samples required to show significant improvements in completing a task? We compared the learning efficiency of in vitro biological neural networks to the state-of-the-art deep reinforcement learning (RL) algorithms in a simplified simulation of the game `Pong'. Using DishBrain, a system that embodies in vitro neural networks with in silico computation using a high-density multi-electrode array, we contrasted the learning rate and the performance of these biological systems against time-matched learning from three state-of-the-art deep RL algorithms (i.e., DQN, A2C, and PPO) in the same game environment. This allowed a meaningful comparison between biological neural systems and deep RL. We find that when samples are limited to a real-world time course, even these very simple biological cultures outperformed deep RL algorithms across various game performance characteristics, implying a higher sample efficiency. Ultimately, even when tested across multiple types of information input to assess the impact of higher dimensional data input, biological neurons showcased faster learning than all deep reinforcement learning agents. Close http://arxiv.org/abs/2405.16946 doi: https://doi.org/10.48550/arXiv.2405.16946 Close
	Bucci, Annalisa; Büttner, Marc; Domdei, Niklas; Rosselli, Federica Bianca; Znidaric, Matej; Diggelmann, Roland; Gennaro, Martina De; Cowan, Cameron S; Harmening, Wolf; Hierlemann, Andreas; Roska, Botond; Franke, Felix Action potential propagation speed compensates for traveling distance in the human retina Journal Article bioRxiv , 2024. Abstract \| Links \| BibTeX \| Tags: Activity Assay, Activity Scan Assay, Axon Tracking Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Microfluidics, Modeling, Retina, Slices, Spike Sorting @article{Bucci2024, title = {Action potential propagation speed compensates for traveling distance in the human retina}, author = {Annalisa Bucci and Marc Büttner and Niklas Domdei and Federica Bianca Rosselli and Matej Znidaric and Roland Diggelmann and Martina De Gennaro and Cameron S. Cowan and Wolf Harmening and Andreas Hierlemann and Botond Roska and Felix Franke }, url = {http://biorxiv.org/lookup/doi/10.1101/2024.04.30.591867}, doi = {10.1101/2024.04.30.591867}, year = {2024}, date = {2024-05-01}, journal = {bioRxiv }, abstract = {Neural information processing requires accurately timed action potentials arriving from presynaptic neurons at the postsynaptic neuron. However, axons of ganglion cells in the human retina feature low axonal conduction speeds and vastly different lengths, which poses a challenge to the brain for constructing a temporally coherent image over the visual field. Combining results from microelectrode array recordings, human behavioral measurements, transmission electron microscopy, and mathematical modelling of the retinal nerve fiber layer, we demonstrate that axonal propagation speeds compensate for variations in axonal length across the human retina including the fovea. The human brain synchronizes the arrival times of action potentials at the optic disc by increasing the diameters of longer axons, which increases their propagation speeds.}, keywords = {Activity Assay, Activity Scan Assay, Axon Tracking Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Microfluidics, Modeling, Retina, Slices, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close Neural information processing requires accurately timed action potentials arriving from presynaptic neurons at the postsynaptic neuron. However, axons of ganglion cells in the human retina feature low axonal conduction speeds and vastly different lengths, which poses a challenge to the brain for constructing a temporally coherent image over the visual field. Combining results from microelectrode array recordings, human behavioral measurements, transmission electron microscopy, and mathematical modelling of the retinal nerve fiber layer, we demonstrate that axonal propagation speeds compensate for variations in axonal length across the human retina including the fovea. The human brain synchronizes the arrival times of action potentials at the optic disc by increasing the diameters of longer axons, which increases their propagation speeds. Close http://biorxiv.org/lookup/doi/10.1101/2024.04.30.591867 doi:10.1101/2024.04.30.591867 Close
	Donner, Christian; Bartram, Julian; Hornauer, Philipp; Kim, Taehoon; Roqueiro, Damian; Hierlemann, Andreas; Obozinski, Guillaume; Schröter, Manuel Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains Journal Article PLOS Computational Biology, 2024. Abstract \| Links \| BibTeX \| Tags: ETH-CMOS-MEA, HD-MEA, MaxTwo, MEA Metrics, MEA Technology, Modeling, Primary Neuronal Cell Culture, Spike Sorting, Synapses @article{Donner2024, title = {Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains}, author = {Christian Donner and Julian Bartram and Philipp Hornauer and Taehoon Kim and Damian Roqueiro and Andreas Hierlemann and Guillaume Obozinski and Manuel Schröter }, url = {https://dx.plos.org/10.1371/journal.pcbi.1011964}, doi = {10.1371/journal.pcbi.1011964}, year = {2024}, date = {2024-04-29}, journal = {PLOS Computational Biology}, abstract = {Probing the architecture of neuronal circuits and the principles that underlie their functional organization remains an important challenge of modern neurosciences. This holds true, in particular, for the inference of neuronal connectivity from large-scale extracellular recordings. Despite the popularity of this approach and a number of elaborate methods to reconstruct networks, the degree to which synaptic connections can be reconstructed from spike-train recordings alone remains controversial. Here, we provide a framework to probe and compare connectivity inference algorithms, using a combination of synthetic ground-truth and in vitro data sets, where the connectivity labels were obtained from simultaneous high-density microelectrode array (HD-MEA) and patch-clamp recordings. We find that reconstruction performance critically depends on the regularity of the recorded spontaneous activity, i.e., their dynamical regime, the type of connectivity, and the amount of available spike-train data. We therefore introduce an ensemble artificial neural network (eANN) to improve connectivity inference. We train the eANN on the validated outputs of six established inference algorithms and show how it improves network reconstruction accuracy and robustness. Overall, the eANN demonstrated strong performance across different dynamical regimes, worked well on smaller datasets, and improved the detection of synaptic connectivity, especially inhibitory connections. Results indicated that the eANN also improved the topological characterization of neuronal networks. The presented methodology contributes to advancing the performance of inference algorithms and facilitates our understanding of how neuronal activity relates to synaptic connectivity. Author summary This study introduces an ensemble artificial neural network (eANN) to infer neuronal connectivity from spike times. We benchmark the eANN against existing connectivity inference algorithms and validate it using in silico simulations and in vitro data obtained from parallel high-density microelectrode array (HD-MEA) and patch-clamp recordings. Results demonstrate that the eANN outperforms all other algorithms across different dynamical regimes and provides a more accurate description of the underlying topological organization of the studied networks. Further examinations of the eANN’s output are conducted to identify which input features are most instrumental in achieving this enhanced performance. In sum, the eANN is a promising approach to improve connectivity inference from spike-train data.}, keywords = {ETH-CMOS-MEA, HD-MEA, MaxTwo, MEA Metrics, MEA Technology, Modeling, Primary Neuronal Cell Culture, Spike Sorting, Synapses}, pubstate = {published}, tppubtype = {article} } Close Probing the architecture of neuronal circuits and the principles that underlie their functional organization remains an important challenge of modern neurosciences. This holds true, in particular, for the inference of neuronal connectivity from large-scale extracellular recordings. Despite the popularity of this approach and a number of elaborate methods to reconstruct networks, the degree to which synaptic connections can be reconstructed from spike-train recordings alone remains controversial. Here, we provide a framework to probe and compare connectivity inference algorithms, using a combination of synthetic ground-truth and in vitro data sets, where the connectivity labels were obtained from simultaneous high-density microelectrode array (HD-MEA) and patch-clamp recordings. We find that reconstruction performance critically depends on the regularity of the recorded spontaneous activity, i.e., their dynamical regime, the type of connectivity, and the amount of available spike-train data. We therefore introduce an ensemble artificial neural network (eANN) to improve connectivity inference. We train the eANN on the validated outputs of six established inference algorithms and show how it improves network reconstruction accuracy and robustness. Overall, the eANN demonstrated strong performance across different dynamical regimes, worked well on smaller datasets, and improved the detection of synaptic connectivity, especially inhibitory connections. Results indicated that the eANN also improved the topological characterization of neuronal networks. The presented methodology contributes to advancing the performance of inference algorithms and facilitates our understanding of how neuronal activity relates to synaptic connectivity. Author summary This study introduces an ensemble artificial neural network (eANN) to infer neuronal connectivity from spike times. We benchmark the eANN against existing connectivity inference algorithms and validate it using in silico simulations and in vitro data obtained from parallel high-density microelectrode array (HD-MEA) and patch-clamp recordings. Results demonstrate that the eANN outperforms all other algorithms across different dynamical regimes and provides a more accurate description of the underlying topological organization of the studied networks. Further examinations of the eANN’s output are conducted to identify which input features are most instrumental in achieving this enhanced performance. In sum, the eANN is a promising approach to improve connectivity inference from spike-train data. Close https://dx.plos.org/10.1371/journal.pcbi.1011964 doi:10.1371/journal.pcbi.1011964 Close
	Kesdoğan, Aylin B; Neureiter, Anika; Gaebler, Arnim J; Kalia, Anil K; Körner, Jannis; Lampert, Angelika Analgesic Effect of Botulinum Toxin in Neuropathic Pain is Sodium Channel Independent Journal Article Neuropharmacology, 2024. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, Activity Scan Assay, HD-MEA, IPSC, MaxTwo, MEA Metrics, MEA Technology @article{Kesdoğan2024, title = {Analgesic Effect of Botulinum Toxin in Neuropathic Pain is Sodium Channel Independent}, author = {Aylin B. Kesdoğan and Anika Neureiter and Arnim J. Gaebler and Anil K. Kalia and Jannis Körner and Angelika Lampert }, url = {https://www.sciencedirect.com/science/article/pii/S0028390824001369?via%3Dihub}, doi = {10.1016/j.neuropharm.2024.109967}, year = {2024}, date = {2024-04-23}, journal = {Neuropharmacology}, abstract = {Botulinum neurotoxin type A BoNT/A is used off-label as a third line therapy for neuropathic pain. However, the mechanism of action remains unclear. In recent years, the role of voltage-gated sodium channels (Nav) in neuropathic pain became evident and it was suggested that block of sodium channels by BoNT/A would contribute to its analgesic effect. We assessed sodium channel function in the presence of BoNT/A in heterologously expressed Nav1.7, Nav1.3, and the neuronal cell line ND7/23 by high throughput automated and manual patch-clamp. We used both the full protein and the isolated catalytic light chain LC/A for acute or long-term extracellular or intracellular exposure. To assess the toxin's effect in a human cellular system, we differentiated induced pluripotent stem cells (iPSC) into sensory neurons from a healthy control and a patient suffering from a hereditary neuropathic pain syndrome (inherited erythromelalgia) carrying the Nav1.7/p.Q875E-mutation and carried out multielectrode-array measurements. Both BoNT/A and the isolated catalytic light chain LC/A showed limited effects in heterologous expression systems and the neuronal cell line ND7/23. Spontaneous activity in iPSC derived sensory neurons remained unaltered upon BoNT/A exposure both in neurons from the healthy control and the mutation carrying patient. BoNT/A may not specifically be beneficial in pain syndromes linked to sodium channel variants. The favorable effects of BoNT/A in neuropathic pain are likely based on mechanisms other than sodium channel blockage and new approaches to understand BoNT/A's therapeutic effects are necessary.}, keywords = {2D Neuronal Culture, Activity Scan Assay, HD-MEA, IPSC, MaxTwo, MEA Metrics, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close Botulinum neurotoxin type A BoNT/A is used off-label as a third line therapy for neuropathic pain. However, the mechanism of action remains unclear. In recent years, the role of voltage-gated sodium channels (Nav) in neuropathic pain became evident and it was suggested that block of sodium channels by BoNT/A would contribute to its analgesic effect. We assessed sodium channel function in the presence of BoNT/A in heterologously expressed Nav1.7, Nav1.3, and the neuronal cell line ND7/23 by high throughput automated and manual patch-clamp. We used both the full protein and the isolated catalytic light chain LC/A for acute or long-term extracellular or intracellular exposure. To assess the toxin's effect in a human cellular system, we differentiated induced pluripotent stem cells (iPSC) into sensory neurons from a healthy control and a patient suffering from a hereditary neuropathic pain syndrome (inherited erythromelalgia) carrying the Nav1.7/p.Q875E-mutation and carried out multielectrode-array measurements. Both BoNT/A and the isolated catalytic light chain LC/A showed limited effects in heterologous expression systems and the neuronal cell line ND7/23. Spontaneous activity in iPSC derived sensory neurons remained unaltered upon BoNT/A exposure both in neurons from the healthy control and the mutation carrying patient. BoNT/A may not specifically be beneficial in pain syndromes linked to sodium channel variants. The favorable effects of BoNT/A in neuropathic pain are likely based on mechanisms other than sodium channel blockage and new approaches to understand BoNT/A's therapeutic effects are necessary. Close https://www.sciencedirect.com/science/article/pii/S0028390824001369?via%3Dihub doi:10.1016/j.neuropharm.2024.109967 Close
	van der Molen, Tjitse; Lim, Max; Bartram, Julian; Cheng, Zhuowei; Robbins, Ash; Parks, David F; Petzold, Linda R; Hierlemann, Andreas; Haussler, David; Hansma, Paul K; Tovar, Kenneth R; Kosik, Kenneth S RT-Sort: an action potential propagation-based algorithm for real time spike detection and sorting with millisecond latencies Journal Article bioRxiv, 2024. Abstract \| Links \| BibTeX \| Tags: 3D Culture, Action Potential, closed loop stimulation, HD-MEA, MEA Metrics, MEA Technology, Organoids, Spike Sorting, Stimulation @article{vanderMolen2024, title = {RT-Sort: an action potential propagation-based algorithm for real time spike detection and sorting with millisecond latencies}, author = {Tjitse van der Molen and Max Lim and Julian Bartram and Zhuowei Cheng and Ash Robbins and David F. Parks and Linda R. Petzold and Andreas Hierlemann and David Haussler and Paul K. Hansma and Kenneth R. Tovar and Kenneth S. Kosik}, url = {http://biorxiv.org/lookup/doi/10.1101/2024.04.08.588620}, doi = {10.1101/2024.04.08.588620}, year = {2024}, date = {2024-04-12}, journal = {bioRxiv}, abstract = {With the use of high density multi electrode recording devices, electrophysiological signals resulting from action potentials of individual neurons can now be reliably detected on multiple adjacent recording electrodes both in vivo and in vitro. Spike sorting assigns these signals to putative neural sources. However, until now, spike sorting can only be performed after completion of the recording, preventing true real time usage of spike sorting algorithms. Utilizing the unique propagation patterns of action potentials along axons detected as high fidelity sequential activations on adjacent electrodes, together with a convolutional neural network based spike detection algorithm, we introduce RT-Sort (Real Time Sorting), a spike sorting algorithm that enables the sorted detection of action potentials within 7.5ms±1.5ms (mean±STD) after the waveform trough while the recording remains ongoing. RT-Sort’s true real-time spike sorting capabilities enable closed loop experiments with latencies comparable to synaptic delay times. We show RT-Sort’s performance on both Multi-Electrode Arrays as well as Neuropixels probes to exemplify RT-Sort’s functionality on different types of recording hardware and electrode configurations.}, keywords = {3D Culture, Action Potential, closed loop stimulation, HD-MEA, MEA Metrics, MEA Technology, Organoids, Spike Sorting, Stimulation}, pubstate = {published}, tppubtype = {article} } Close With the use of high density multi electrode recording devices, electrophysiological signals resulting from action potentials of individual neurons can now be reliably detected on multiple adjacent recording electrodes both in vivo and in vitro. Spike sorting assigns these signals to putative neural sources. However, until now, spike sorting can only be performed after completion of the recording, preventing true real time usage of spike sorting algorithms. Utilizing the unique propagation patterns of action potentials along axons detected as high fidelity sequential activations on adjacent electrodes, together with a convolutional neural network based spike detection algorithm, we introduce RT-Sort (Real Time Sorting), a spike sorting algorithm that enables the sorted detection of action potentials within 7.5ms±1.5ms (mean±STD) after the waveform trough while the recording remains ongoing. RT-Sort’s true real-time spike sorting capabilities enable closed loop experiments with latencies comparable to synaptic delay times. We show RT-Sort’s performance on both Multi-Electrode Arrays as well as Neuropixels probes to exemplify RT-Sort’s functionality on different types of recording hardware and electrode configurations. Close http://biorxiv.org/lookup/doi/10.1101/2024.04.08.588620 doi:10.1101/2024.04.08.588620 Close
	Tetzlaff, Svenja K; Reyhan, Ekin; Bengtson, Peter C; Schroers, Julian; Wagner, Julia; Schubert, Marc C; Layer, Nikolas; Puschhof, Maria C; Faymonville, Anton J; Drewa, Nina; Pramatarov, Rangel L; Wissmann, Niklas; Alhalabi, Obada; Heuer, Alina; Sivapalan, Nirosan; Campos, Joaquín; Boztepe, Berin; Scheck, Jonas G; Villa, Giulia; Schröter, Manuel; Sahm, Felix; Forsberg-Nilsson, Karin; Breckwoldt, Michael O; Acuna, Claudio; Suchorska, Bogdana; Heiland, Dieter Henrik; Saez-Rodriguez, Julio; Venkataramani, Varun Characterizing and targeting glioblastoma neuron-tumor networks with retrograde tracing Journal Article bioRxiv, 2024. Abstract \| Links \| BibTeX \| Tags: 3D Culture, HD-MEA, MaxTwo, MEA Metrics, MEA Technology, Organoids, Primary Neuronal Cell Culture @article{Tetzlaff2024, title = {Characterizing and targeting glioblastoma neuron-tumor networks with retrograde tracing}, author = {Svenja K. Tetzlaff and Ekin Reyhan and C. Peter Bengtson and Julian Schroers and Julia Wagner and Marc C. Schubert and Nikolas Layer and Maria C. Puschhof and Anton J. Faymonville and Nina Drewa and Rangel L. Pramatarov and Niklas Wissmann and Obada Alhalabi and Alina Heuer and Nirosan Sivapalan and Joaquín Campos and Berin Boztepe and Jonas G. Scheck and Giulia Villa and Manuel Schröter and Felix Sahm and Karin Forsberg-Nilsson and Michael O. Breckwoldt and Claudio Acuna and Bogdana Suchorska and Dieter Henrik Heiland and Julio Saez-Rodriguez and Varun Venkataramani}, url = {http://biorxiv.org/lookup/doi/10.1101/2024.03.18.585565}, doi = {10.1101/2024.03.18.585565}, year = {2024}, date = {2024-03-22}, journal = {bioRxiv}, abstract = {Glioblastomas are invasive brain tumors with high therapeutic resistance. Neuron-to-glioma synapses have been shown to promote glioblastoma progression. However, a characterization of tumor-connected neurons has been hampered by a lack of technologies. Here, we adapted retrograde tracing using rabies viruses to investigate and manipulate neuron-tumor networks. Glioblastoma rapidly integrated into neural circuits across the brain engaging in widespread functional communication, with acetylcholinergic neurons driving glioblastoma invasion. We uncovered patient-specific and tumor cell state-dependent differences in synaptogenic gene expression associated with neuron-tumor connectivity and subsequent invasivity. Importantly, radiotherapy enhanced neuron-tumor connectivity by increased neuronal activity. In turn, simultaneous neuronal activity inhibition and radiotherapy showed increased therapeutic effects, indicative of a role for neuron-to-glioma synapses in contributing to therapeutic resistance. Lastly, rabies-mediated genetic ablation of tumor-connected neurons halted glioblastoma progression, offering a viral strategy to tackle glioblastoma. Together, this study provides a framework to comprehensively characterize neuron-tumor networks and target glioblastoma.}, keywords = {3D Culture, HD-MEA, MaxTwo, MEA Metrics, MEA Technology, Organoids, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close Glioblastomas are invasive brain tumors with high therapeutic resistance. Neuron-to-glioma synapses have been shown to promote glioblastoma progression. However, a characterization of tumor-connected neurons has been hampered by a lack of technologies. Here, we adapted retrograde tracing using rabies viruses to investigate and manipulate neuron-tumor networks. Glioblastoma rapidly integrated into neural circuits across the brain engaging in widespread functional communication, with acetylcholinergic neurons driving glioblastoma invasion. We uncovered patient-specific and tumor cell state-dependent differences in synaptogenic gene expression associated with neuron-tumor connectivity and subsequent invasivity. Importantly, radiotherapy enhanced neuron-tumor connectivity by increased neuronal activity. In turn, simultaneous neuronal activity inhibition and radiotherapy showed increased therapeutic effects, indicative of a role for neuron-to-glioma synapses in contributing to therapeutic resistance. Lastly, rabies-mediated genetic ablation of tumor-connected neurons halted glioblastoma progression, offering a viral strategy to tackle glioblastoma. Together, this study provides a framework to comprehensively characterize neuron-tumor networks and target glioblastoma. Close http://biorxiv.org/lookup/doi/10.1101/2024.03.18.585565 doi:10.1101/2024.03.18.585565 Close
	Fenton, Timothy A; Haouchine, Olivia Y; Hallam, Elizabeth L; Smith, Emily M; Jackson, Kiya C; Rahbarian, Darlene; Canales, Cesar; Adhikari, Anna; Nord, Alexander S; Ben-Shalom, Roy; Silverman, Jill L Hyperexcitability and translational phenotypes in a preclinical mouse model of SYNGAP1-Related Intellectual Disability Journal Article Research Square, 2024. Abstract \| Links \| BibTeX \| Tags: Activity Scan Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Network Assay, Primary Neuronal Cell Culture, Spike Sorting @article{Fenton2024, title = {Hyperexcitability and translational phenotypes in a preclinical mouse model of SYNGAP1-Related Intellectual Disability}, author = {Timothy A Fenton and Olivia Y Haouchine and Elizabeth L Hallam and Emily M Smith and Kiya C Jackson and Darlene Rahbarian and Cesar Canales and Anna Adhikari and Alexander S Nord and Roy Ben-Shalom and Jill L Silverman}, url = {https://www.researchsquare.com/article/rs-4067746/v1}, doi = {10.21203/rs.3.rs-4067746/v1}, year = {2024}, date = {2024-03-19}, journal = {Research Square}, abstract = {Disruption of SYNGAP1 directly causes a genetically identifiable neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability (SRID). Without functional SynGAP1 protein, individuals are developmentally delayed and have prominent features of intellectual disability, motor impairments, and epilepsy. Over the past two decades, there have been numerous discoveries indicting the critical role of Syngap1. Several rodent models with a loss of Syngap1 have been engineered identifying precise roles in neuronal structure and function, as well as key biochemical pathways key for synapse integrity. Homozygous loss of Syngap1 is lethal. Heterozygous mutations of Syngap1 result in a broad range of behavioral phenotypes. Our in vivo functional data, using the mouse model from the Huganir laboratory, corroborated earlier reported behaviors including robust hyperactivity and deficits in learning and memory in young adults. In extension, we report impairments in slow wave sleep, a critical component of the domain of sleep. We characterized Syngap1+/- mice by using neurophysiology collected with wireless, telemetric electroencephalography (EEG). Syngap1+/- mice also exhibited elevated spiking events and spike trains, in addition to elevated power, most notably in the delta frequency band. For the first time, we illustrated how primary neurons from Syngap1+/- mice function and display increased network firing activity, greater bursts, and shorter inter-burst intervals between peaks by employing high density microelectrode arrays (HD-MEA). Our reported data bridge in-vitro electrophysiological neuronal activity and function with in vivo neurophysiological brain activity and function. These data elucidate quantitative, translational biomarkers in vivo and in vitro that can be utilized for the development of and efficacy assessment of targeted treatments for SRID.}, keywords = {Activity Scan Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Network Assay, Primary Neuronal Cell Culture, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close Disruption of SYNGAP1 directly causes a genetically identifiable neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability (SRID). Without functional SynGAP1 protein, individuals are developmentally delayed and have prominent features of intellectual disability, motor impairments, and epilepsy. Over the past two decades, there have been numerous discoveries indicting the critical role of Syngap1. Several rodent models with a loss of Syngap1 have been engineered identifying precise roles in neuronal structure and function, as well as key biochemical pathways key for synapse integrity. Homozygous loss of Syngap1 is lethal. Heterozygous mutations of Syngap1 result in a broad range of behavioral phenotypes. Our in vivo functional data, using the mouse model from the Huganir laboratory, corroborated earlier reported behaviors including robust hyperactivity and deficits in learning and memory in young adults. In extension, we report impairments in slow wave sleep, a critical component of the domain of sleep. We characterized Syngap1+/- mice by using neurophysiology collected with wireless, telemetric electroencephalography (EEG). Syngap1+/- mice also exhibited elevated spiking events and spike trains, in addition to elevated power, most notably in the delta frequency band. For the first time, we illustrated how primary neurons from Syngap1+/- mice function and display increased network firing activity, greater bursts, and shorter inter-burst intervals between peaks by employing high density microelectrode arrays (HD-MEA). Our reported data bridge in-vitro electrophysiological neuronal activity and function with in vivo neurophysiological brain activity and function. These data elucidate quantitative, translational biomarkers in vivo and in vitro that can be utilized for the development of and efficacy assessment of targeted treatments for SRID. Close https://www.researchsquare.com/article/rs-4067746/v1 doi:10.21203/rs.3.rs-4067746/v1 Close
	Voitiuk, Kateryna; Seiler, Spencer T; de Melo, Mirella Pessoa; Geng, Jinghui; Hernandez, Sebastian; Schweiger, Hunter E; Sevetson, Jess L; Parks, David F; Robbins, Ash; Torres-Montoya, Sebastian; Ehrlich, Drew; Elliott, Matthew A T; Sharf, Tal; Haussler, David; Mostajo-Radji, Mohammed A; Salama, Sofie R; Teodorescu, Mircea A feedback-driven IoT microfluidic, electrophysiology, and imaging platform for brain organoid studies Journal Article bioRxiv, 2024. Abstract \| Links \| BibTeX \| Tags: Activity Scan Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Microfluidics, Organoids @article{Voitiuk2024, title = {A feedback-driven IoT microfluidic, electrophysiology, and imaging platform for brain organoid studies}, author = {Kateryna Voitiuk and Spencer T. Seiler and Mirella Pessoa de Melo and Jinghui Geng and Sebastian Hernandez and Hunter E. Schweiger and Jess L. Sevetson and David F. Parks and Ash Robbins and Sebastian Torres-Montoya and Drew Ehrlich and Matthew A.T. Elliott and Tal Sharf and David Haussler and Mohammed A. Mostajo-Radji and Sofie R. Salama and Mircea Teodorescu}, url = {http://biorxiv.org/lookup/doi/10.1101/2024.03.15.585237}, doi = {10.1101/2024.03.15.585237}, year = {2024}, date = {2024-03-17}, journal = {bioRxiv}, abstract = {The analysis of tissue cultures, particularly brain organoids, takes a high degree of coordination, measurement, and monitoring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Unified by an Internet of Things (IoT) architecture, our approach enables continuous, communicative interactions among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids and monitor their neuronal activity. The organoids are cultured in custom, 3D-printed chambers attached to commercial microelectrode arrays for electrophysiology monitoring. Periodic feeding is achieved using programmable microfluidic pumps. We developed computer vision fluid volume estimations of aspirated media, achieving high accuracy, and used feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a 7-day study of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated experimental samples maintained robust neural activity throughout the experiment, comparable with the control samples. The automated system enabled hourly electrophysiology recordings that revealed dramatic temporal changes in neuron firing rates not observed in once-a-day recordings. One-Sentence Summary: An IoT laboratory robotics system that enables touch-free feeding, imaging, and electrophysiology of brain organoids.}, keywords = {Activity Scan Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Microfluidics, Organoids}, pubstate = {published}, tppubtype = {article} } Close The analysis of tissue cultures, particularly brain organoids, takes a high degree of coordination, measurement, and monitoring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Unified by an Internet of Things (IoT) architecture, our approach enables continuous, communicative interactions among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids and monitor their neuronal activity. The organoids are cultured in custom, 3D-printed chambers attached to commercial microelectrode arrays for electrophysiology monitoring. Periodic feeding is achieved using programmable microfluidic pumps. We developed computer vision fluid volume estimations of aspirated media, achieving high accuracy, and used feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a 7-day study of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated experimental samples maintained robust neural activity throughout the experiment, comparable with the control samples. The automated system enabled hourly electrophysiology recordings that revealed dramatic temporal changes in neuron firing rates not observed in once-a-day recordings. One-Sentence Summary: An IoT laboratory robotics system that enables touch-free feeding, imaging, and electrophysiology of brain organoids. Close http://biorxiv.org/lookup/doi/10.1101/2024.03.15.585237 doi:10.1101/2024.03.15.585237 Close
	Kasuba, Krishna Chaitanya; Buccino, Alessio Paolo; Bartram, Julian; Gaub, Benjamin M; Fauser, Felix J; Ronchi, Silvia; Kumar, Sreedhar Saseendran; Geissler, Sydney; Nava, Michele M; Hierlemann, Andreas; Müller, Daniel J Mechanical stimulation and electrophysiological monitoring at subcellular resolution reveals differential mechanosensation of neurons within networks Journal Article Nature Nanotechnology, 2024. Abstract \| Links \| BibTeX \| Tags: Action Potential, Brain Slice, HD-MEA, MaxOne, Primary Neuronal Cell Culture, Spike Sorting @article{Kasuba2024, title = {Mechanical stimulation and electrophysiological monitoring at subcellular resolution reveals differential mechanosensation of neurons within networks}, author = {Krishna Chaitanya Kasuba and Alessio Paolo Buccino and Julian Bartram and Benjamin M. Gaub and Felix J. Fauser and Silvia Ronchi and Sreedhar Saseendran Kumar and Sydney Geissler and Michele M. Nava and Andreas Hierlemann and Daniel J. Müller }, url = {https://www.nature.com/articles/s41565-024-01609-1}, doi = {10.1038/s41565-024-01609-1}, year = {2024}, date = {2024-02-20}, journal = {Nature Nanotechnology}, abstract = {A growing consensus that the brain is a mechanosensitive organ is driving the need for tools that mechanically stimulate and simultaneously record the electrophysiological response of neurons within neuronal networks. Here we introduce a synchronized combination of atomic force microscopy, high-density microelectrode array and fluorescence microscopy to monitor neuronal networks and to mechanically characterize and stimulate individual neurons at piconewton force sensitivity and nanometre precision while monitoring their electrophysiological activity at subcellular spatial and millisecond temporal resolution. No correlation is found between mechanical stiffness and electrophysiological activity of neuronal compartments. Furthermore, spontaneously active neurons show exceptional functional resilience to static mechanical compression of their soma. However, application of fast transient (∼500 ms) mechanical stimuli to the neuronal soma can evoke action potentials, which depend on the anchoring of neuronal membrane and actin cytoskeleton. Neurons show higher responsivity, including bursts of action potentials, to slower transient mechanical stimuli (∼60 s). Moreover, transient and repetitive application of the same compression modulates the neuronal firing rate. Seemingly, neuronal networks can differentiate and respond to specific characteristics of mechanical stimulation. Ultimately, the developed multiparametric tool opens the door to explore manifold nanomechanobiological responses of neuronal systems and new ways of mechanical control.}, keywords = {Action Potential, Brain Slice, HD-MEA, MaxOne, Primary Neuronal Cell Culture, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close A growing consensus that the brain is a mechanosensitive organ is driving the need for tools that mechanically stimulate and simultaneously record the electrophysiological response of neurons within neuronal networks. Here we introduce a synchronized combination of atomic force microscopy, high-density microelectrode array and fluorescence microscopy to monitor neuronal networks and to mechanically characterize and stimulate individual neurons at piconewton force sensitivity and nanometre precision while monitoring their electrophysiological activity at subcellular spatial and millisecond temporal resolution. No correlation is found between mechanical stiffness and electrophysiological activity of neuronal compartments. Furthermore, spontaneously active neurons show exceptional functional resilience to static mechanical compression of their soma. However, application of fast transient (∼500 ms) mechanical stimuli to the neuronal soma can evoke action potentials, which depend on the anchoring of neuronal membrane and actin cytoskeleton. Neurons show higher responsivity, including bursts of action potentials, to slower transient mechanical stimuli (∼60 s). Moreover, transient and repetitive application of the same compression modulates the neuronal firing rate. Seemingly, neuronal networks can differentiate and respond to specific characteristics of mechanical stimulation. Ultimately, the developed multiparametric tool opens the door to explore manifold nanomechanobiological responses of neuronal systems and new ways of mechanical control. Close https://www.nature.com/articles/s41565-024-01609-1 doi:10.1038/s41565-024-01609-1 Close
	Hruska-Plochan, Marian; Wiersma, Vera I; Betz, Katharina M; Mallona, Izaskun; Ronchi, Silvia; Maniecka, Zuzanna; Hock, Eva-Maria; Tantardini, Elena; Laferriere, Florent; Sahadevan, Sonu; Hoop, Vanessa; Delvendahl, Igor; Pérez-Berlanga, Manuela; Gatta, Beatrice; Panatta, Martina; van der Bourg, Alexander; Bohaciakova, Dasa; Sharma, Puneet; Vos, Laura De; Frontzek, Karl; Aguzzi, Adriano; Lashley, Tammaryn; Robinson, Mark D; Karayannis, Theofanis; Mueller, Martin; Hierlemann, Andreas; Polymenidou, Magdalini A model of human neural networks reveals NPTX2 pathology in ALS and FTLD Journal Article Nature, 2024. Abstract \| Links \| BibTeX \| Tags: Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Network Assay, Primary Neuronal Cell Culture, Spike Sorting @article{Hruska-Plochan2024, title = {A model of human neural networks reveals NPTX2 pathology in ALS and FTLD}, author = {Marian Hruska-Plochan and Vera I. Wiersma and Katharina M. Betz and Izaskun Mallona and Silvia Ronchi and Zuzanna Maniecka and Eva-Maria Hock and Elena Tantardini and Florent Laferriere and Sonu Sahadevan and Vanessa Hoop and Igor Delvendahl and Manuela Pérez-Berlanga and Beatrice Gatta and Martina Panatta and Alexander van der Bourg and Dasa Bohaciakova and Puneet Sharma and Laura De Vos and Karl Frontzek and Adriano Aguzzi and Tammaryn Lashley and Mark D. Robinson and Theofanis Karayannis and Martin Mueller and Andreas Hierlemann and Magdalini Polymenidou }, url = {https://www.nature.com/articles/s41586-024-07042-7}, doi = {10.1038/s41586-024-07042-7}, year = {2024}, date = {2024-02-14}, journal = {Nature}, abstract = {Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1, which involve human-specific mechanisms that cannot be directly studied in animal models. Here, to explore the emergence and consequences of TDP-43 pathologies, we generated induced pluripotent stem cell-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors. Single-cell transcriptomics and comparison to independent neural stem cells showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks (which we designate iNets). Neuronal and glial maturation in iNets was similar to that of cortical organoids. Overexpression of wild-type TDP-43 in a minority of neurons within iNets led to progressive fragmentation and aggregation of the protein, resulting in a partial loss of function and neurotoxicity. Single-cell transcriptomics revealed a novel set of misregulated RNA targets in TDP-43-overexpressing neurons and in patients with TDP-43 proteinopathies exhibiting a loss of nuclear TDP-43. The strongest misregulated target encoded the synaptic protein NPTX2, the levels of which are controlled by TDP-43 binding on its 3′ untranslated region. When NPTX2 was overexpressed in iNets, it exhibited neurotoxicity, whereas correcting NPTX2 misregulation partially rescued neurons from TDP-43-induced neurodegeneration. Notably, NPTX2 was consistently misaccumulated in neurons from patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby revealing a TDP-43-dependent pathway of neurotoxicity.}, keywords = {Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Network Assay, Primary Neuronal Cell Culture, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1, which involve human-specific mechanisms that cannot be directly studied in animal models. Here, to explore the emergence and consequences of TDP-43 pathologies, we generated induced pluripotent stem cell-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors. Single-cell transcriptomics and comparison to independent neural stem cells showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks (which we designate iNets). Neuronal and glial maturation in iNets was similar to that of cortical organoids. Overexpression of wild-type TDP-43 in a minority of neurons within iNets led to progressive fragmentation and aggregation of the protein, resulting in a partial loss of function and neurotoxicity. Single-cell transcriptomics revealed a novel set of misregulated RNA targets in TDP-43-overexpressing neurons and in patients with TDP-43 proteinopathies exhibiting a loss of nuclear TDP-43. The strongest misregulated target encoded the synaptic protein NPTX2, the levels of which are controlled by TDP-43 binding on its 3′ untranslated region. When NPTX2 was overexpressed in iNets, it exhibited neurotoxicity, whereas correcting NPTX2 misregulation partially rescued neurons from TDP-43-induced neurodegeneration. Notably, NPTX2 was consistently misaccumulated in neurons from patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby revealing a TDP-43-dependent pathway of neurotoxicity. Close https://www.nature.com/articles/s41586-024-07042-7 doi:10.1038/s41586-024-07042-7 Close
	Wang, Guodong; Zhang, Dandan; Qin, Liangshan; Liu, Quanhui; Tang, Wenkui; Liu, Mingxing; Xu, Fan; Tang, Fen; Cheng, Leping; Mo, Huiming; Yuan, Xiang; Wang, Zhiqiang; Huang, Ben Forskolin-driven conversion of human somatic cells into induced neurons through regulation of the cAMP-CREB1-JNK signaling Journal Article Theranostics , 2024. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology @article{Wang2024, title = {Forskolin-driven conversion of human somatic cells into induced neurons through regulation of the cAMP-CREB1-JNK signaling}, author = {Guodong Wang and Dandan Zhang and Liangshan Qin and Quanhui Liu and Wenkui Tang and Mingxing Liu and Fan Xu and Fen Tang and Leping Cheng and Huiming Mo and Xiang Yuan and Zhiqiang Wang and Ben Huang}, url = {https://www.thno.org/v14p1701.htm}, doi = {10.7150/thno.92700}, year = {2024}, date = {2024-02-11}, journal = {Theranostics }, abstract = {Human somatic cells can be reprogrammed into neuron cell fate through regulation of a single transcription factor or application of small molecule cocktails. Methods: Here, we report that forskolin efficiently induces the conversion of human somatic cells into induced neurons (FiNs). Results: A large population of neuron-like phenotype cells was observed as early as 24-36 h post-induction. There were >90% TUJ1-, >80% MAP2-, and >80% NEUN-positive neurons at 5 days post-induction. Multiple subtypes of neurons were present among TUJ1-positive cells, including >60% cholinergic, >20% glutamatergic, >10% GABAergic, and >5% dopaminergic neurons. FiNs exhibited typical neural electrophysiological activity in vitro and the ability to survive in vitro and in vivo more than 2 months. Mechanistically, forskolin functions in FiN reprogramming by regulating the cAMP-CREB1-JNK signals, which upregulates cAMP-CREB1 expression and downregulates JNK expression. Conclusion: Overall, our studies identify a safer and efficient single-small-molecule-driven reprogramming approach for induced neuron generation and reveal a novel regulatory mechanism of neuronal cell fate acquisition.}, keywords = {2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close Human somatic cells can be reprogrammed into neuron cell fate through regulation of a single transcription factor or application of small molecule cocktails. Methods: Here, we report that forskolin efficiently induces the conversion of human somatic cells into induced neurons (FiNs). Results: A large population of neuron-like phenotype cells was observed as early as 24-36 h post-induction. There were >90% TUJ1-, >80% MAP2-, and >80% NEUN-positive neurons at 5 days post-induction. Multiple subtypes of neurons were present among TUJ1-positive cells, including >60% cholinergic, >20% glutamatergic, >10% GABAergic, and >5% dopaminergic neurons. FiNs exhibited typical neural electrophysiological activity in vitro and the ability to survive in vitro and in vivo more than 2 months. Mechanistically, forskolin functions in FiN reprogramming by regulating the cAMP-CREB1-JNK signals, which upregulates cAMP-CREB1 expression and downregulates JNK expression. Conclusion: Overall, our studies identify a safer and efficient single-small-molecule-driven reprogramming approach for induced neuron generation and reveal a novel regulatory mechanism of neuronal cell fate acquisition. Close https://www.thno.org/v14p1701.htm doi:10.7150/thno.92700 Close
	Hornauer, Philipp; Prack, Gustavo; Anastasi, Nadia; Ronchi, Silvia; Kim, Taehoon; Donner, Christian; Fiscella, Michele; Borgwardt, Karsten; Taylor, Verdon; Jagasia, Ravi; Roqueiro, Damian; Hierlemann, Andreas; Schröter, Manuel DeePhys: A machine learning–assisted platform for electrophysiological phenotyping of human neuronal networks Journal Article Stem Cell Reports, 2024. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Technology, Spike Sorting @article{Hornauer2024, title = {DeePhys: A machine learning–assisted platform for electrophysiological phenotyping of human neuronal networks}, author = {Philipp Hornauer and Gustavo Prack and Nadia Anastasi and Silvia Ronchi and Taehoon Kim and Christian Donner and Michele Fiscella and Karsten Borgwardt and Verdon Taylor and Ravi Jagasia and Damian Roqueiro and Andreas Hierlemann and Manuel Schröter}, url = {https://www.sciencedirect.com/science/article/pii/S2213671123005015}, doi = {10.1016/j.stemcr.2023.12.008}, year = {2024}, date = {2024-01-25}, journal = {Stem Cell Reports}, abstract = {Reproducible functional assays to study in vitro neuronal networks represent an important cornerstone in the quest to develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven functional phenotyping of in vitro neuronal cultures recorded by high-density microelectrode arrays. DeePhys is a modular workflow that offers a range of techniques to extract features from spike-sorted data, allowing for the examination of functional phenotypes both at the individual cell and network levels, as well as across development. In addition, DeePhys incorporates the capability to integrate novel features and to use machine-learning-assisted approaches, which facilitates a comprehensive evaluation of pharmacological interventions. To illustrate its practical application, we apply DeePhys to human induced pluripotent stem cell–derived dopaminergic neurons obtained from both patients and healthy individuals and showcase how DeePhys enables phenotypic screenings.}, keywords = {2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Technology, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close Reproducible functional assays to study in vitro neuronal networks represent an important cornerstone in the quest to develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven functional phenotyping of in vitro neuronal cultures recorded by high-density microelectrode arrays. DeePhys is a modular workflow that offers a range of techniques to extract features from spike-sorted data, allowing for the examination of functional phenotypes both at the individual cell and network levels, as well as across development. In addition, DeePhys incorporates the capability to integrate novel features and to use machine-learning-assisted approaches, which facilitates a comprehensive evaluation of pharmacological interventions. To illustrate its practical application, we apply DeePhys to human induced pluripotent stem cell–derived dopaminergic neurons obtained from both patients and healthy individuals and showcase how DeePhys enables phenotypic screenings. Close https://www.sciencedirect.com/science/article/pii/S2213671123005015 doi:10.1016/j.stemcr.2023.12.008 Close
2023
	van der Molen, Tjitse; Spaeth, Alex; Chini, Mattia; Bartram, Julian; Dendukuri, Aditya; Zhang, Zongren; Bhaskaran-Nair, Kiran; Blauvelt, Lon J; Petzold, Linda R; Hansma, Paul K; Teodorescu, Mircea; Hierlemann, Andreas; Hengen, Keith B; Hanganu-Opatz, Ileana L; Kosik, Kenneth S; Sharf, Tal Protosequences in human cortical organoids model intrinsic states in the developing cortex Journal Article bioRxiv, 2023. Abstract \| Links \| BibTeX \| Tags: MaxOne, Organoids @article{Molen2023, title = {Protosequences in human cortical organoids model intrinsic states in the developing cortex}, author = {Tjitse van der Molen and Alex Spaeth and Mattia Chini and Julian Bartram and Aditya Dendukuri and Zongren Zhang and Kiran Bhaskaran-Nair and Lon J. Blauvelt and Linda R. Petzold and Paul K. Hansma and Mircea Teodorescu and Andreas Hierlemann and Keith B. Hengen and Ileana L. Hanganu-Opatz and Kenneth S. Kosik and Tal Sharf}, url = {https://www.biorxiv.org/content/10.1101/2023.12.29.573646v1}, doi = {10.1101/2023.12.29.573646}, year = {2023}, date = {2023-12-30}, journal = {bioRxiv}, abstract = {Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development.}, keywords = {MaxOne, Organoids}, pubstate = {published}, tppubtype = {article} } Close Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development. Close https://www.biorxiv.org/content/10.1101/2023.12.29.573646v1 doi:10.1101/2023.12.29.573646 Close
	Cai, Hongwei; Ao, Zheng; Tian, Chunhui; Wu, Zhuhao; Liu, Hongcheng; Tchieu, Jason; Gu, Mingxia; Mackie, Ken; Guo, Feng Brain organoid reservoir computing for artificial intelligence Journal Article Nature Electronics, 2023. Abstract \| Links \| BibTeX \| Tags: 3D Culture, HD-MEA, Machine Learning, MaxOne, MEA Technology, Organoids, Stimulation @article{Cai2023b, title = {Brain organoid reservoir computing for artificial intelligence}, author = {Hongwei Cai and Zheng Ao and Chunhui Tian and Zhuhao Wu and Hongcheng Liu and Jason Tchieu and Mingxia Gu and Ken Mackie and Feng Guo }, url = {https://www.nature.com/articles/s41928-023-01069-w}, doi = {10.1038/s41928-023-01069-w}, year = {2023}, date = {2023-12-11}, journal = {Nature Electronics}, abstract = {Brain-inspired computing hardware aims to emulate the structure and working principles of the brain and could be used to address current limitations in artificial intelligence technologies. However, brain-inspired silicon chips are still limited in their ability to fully mimic brain function as most examples are built on digital electronic principles. Here we report an artificial intelligence hardware approach that uses adaptive reservoir computation of biological neural networks in a brain organoid. In this approach—which is termed Brainoware—computation is performed by sending and receiving information from the brain organoid using a high-density multielectrode array. By applying spatiotemporal electrical stimulation, nonlinear dynamics and fading memory properties are achieved, as well as unsupervised learning from training data by reshaping the organoid functional connectivity. We illustrate the practical potential of this technique by using it for speech recognition and nonlinear equation prediction in a reservoir computing framework.}, keywords = {3D Culture, HD-MEA, Machine Learning, MaxOne, MEA Technology, Organoids, Stimulation}, pubstate = {published}, tppubtype = {article} } Close Brain-inspired computing hardware aims to emulate the structure and working principles of the brain and could be used to address current limitations in artificial intelligence technologies. However, brain-inspired silicon chips are still limited in their ability to fully mimic brain function as most examples are built on digital electronic principles. Here we report an artificial intelligence hardware approach that uses adaptive reservoir computation of biological neural networks in a brain organoid. In this approach—which is termed Brainoware—computation is performed by sending and receiving information from the brain organoid using a high-density multielectrode array. By applying spatiotemporal electrical stimulation, nonlinear dynamics and fading memory properties are achieved, as well as unsupervised learning from training data by reshaping the organoid functional connectivity. We illustrate the practical potential of this technique by using it for speech recognition and nonlinear equation prediction in a reservoir computing framework. Close https://www.nature.com/articles/s41928-023-01069-w doi:10.1038/s41928-023-01069-w Close
	Ryu, Seungmi; Weber, Claire; Chu, Pei-Hsuan; Ernest, Ben; Jovanovic, Vukasin M; Deng, Tao; Slamecka, Jaroslav; Hong, Hyenjong; Jethmalani, Yogita; Baskir, Hannah M; Inman, Jason; Braisted, John; Hirst, Marissa B; Simeonov, Anton; Voss, Ty C; Tristan, Carlos A; Singeç, Ilyas Stress-free cell aggregation by using the CEPT cocktail enhances embryoid body and organoid fitness Journal Article Biofabrication, 2023. Abstract \| Links \| BibTeX \| Tags: 3D Culture, Activity Scan Assay, HD-MEA, MEA Technology, Organoids @article{Ryu2023, title = {Stress-free cell aggregation by using the CEPT cocktail enhances embryoid body and organoid fitness}, author = {Seungmi Ryu and Claire Weber and Pei-Hsuan Chu and Ben Ernest and Vukasin M Jovanovic and Tao Deng and Jaroslav Slamecka and Hyenjong Hong and Yogita Jethmalani and Hannah M Baskir and Jason Inman and John Braisted and Marissa B Hirst and Anton Simeonov and Ty C Voss and Carlos A Tristan and Ilyas Singeç}, url = {https://dx.doi.org/10.1088/1758-5090/ad0d13}, doi = {10.1088/1758-5090/ad0d13}, year = {2023}, date = {2023-12-11}, journal = {Biofabrication}, abstract = {Embryoid bodies (EBs) and self-organizing organoids derived from human pluripotent stem cells (hPSCs) recapitulate tissue development in a dish and hold great promise for disease modeling and drug development. However, current protocols are hampered by cellular stress and apoptosis during cell aggregation, resulting in variability and impaired cell differentiation. Here, we demonstrate that EBs and various organoid models (e.g., brain, gut, kidney) can be optimized by using the small molecule cocktail named CEPT (chroman 1, emricasan, polyamines, trans-ISRIB), a polypharmacological approach that ensures cytoprotection and cell survival. Application of CEPT for just 24 h during cell aggregation has long-lasting consequences affecting morphogenesis, gene expression, cellular differentiation, and organoid function. Various qualification methods confirmed that CEPT treatment enhanced experimental reproducibility and consistently improved EB and organoid fitness as compared to the widely used ROCK inhibitor Y-27632. Collectively, we discovered that stress-free cell aggregation and superior cell survival in the presence of CEPT are critical quality control determinants that establish a robust foundation for bioengineering complex tissue and organ models.}, keywords = {3D Culture, Activity Scan Assay, HD-MEA, MEA Technology, Organoids}, pubstate = {published}, tppubtype = {article} } Close Embryoid bodies (EBs) and self-organizing organoids derived from human pluripotent stem cells (hPSCs) recapitulate tissue development in a dish and hold great promise for disease modeling and drug development. However, current protocols are hampered by cellular stress and apoptosis during cell aggregation, resulting in variability and impaired cell differentiation. Here, we demonstrate that EBs and various organoid models (e.g., brain, gut, kidney) can be optimized by using the small molecule cocktail named CEPT (chroman 1, emricasan, polyamines, trans-ISRIB), a polypharmacological approach that ensures cytoprotection and cell survival. Application of CEPT for just 24 h during cell aggregation has long-lasting consequences affecting morphogenesis, gene expression, cellular differentiation, and organoid function. Various qualification methods confirmed that CEPT treatment enhanced experimental reproducibility and consistently improved EB and organoid fitness as compared to the widely used ROCK inhibitor Y-27632. Collectively, we discovered that stress-free cell aggregation and superior cell survival in the presence of CEPT are critical quality control determinants that establish a robust foundation for bioengineering complex tissue and organ models. Close https://dx.doi.org/10.1088/1758-5090/ad0d13 Close
	Friston, Karl J; Salvatori, Tommaso; Isomura, Takuya; Tschantz, Alexander; Kiefer, Alex; Verbelen, Tim; Koudahl, Magnus; Paul, Aswin; Parr, Thomas; Razi, Adeel; Kagan, Brett; Buckley, Christopher L; and Ramstead, Maxwell J D Active Inference and Intentional Behaviour Journal Article arXiv, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Technology, Stimulation @article{Friston2023, title = {Active Inference and Intentional Behaviour}, author = {Karl J. Friston and Tommaso Salvatori and Takuya Isomura and Alexander Tschantz and Alex Kiefer and Tim Verbelen and Magnus Koudahl and Aswin Paul and Thomas Parr and Adeel Razi and Brett Kagan and Christopher L. Buckley and and Maxwell J. D. Ramstead}, url = {http://arxiv.org/abs/2312.07547}, doi = {10.48550/arXiv.2312.07547}, year = {2023}, date = {2023-12-06}, journal = {arXiv}, abstract = {Recent advances in theoretical biology suggest that basal cognition and sentient behaviour are emergent properties of in vitro cell cultures and neuronal networks, respectively. Such neuronal networks spontaneously learn structured behaviours in the absence of reward or reinforcement. In this paper, we characterise this kind of selforganisation through the lens of the free energy principle, i.e., as self-evidencing. We do this by first discussing the definitions of reactive and sentient behaviour in the setting of active inference, which describes the behaviour of agents that model the consequences of their actions. We then introduce a formal account of intentional behaviour, that describes agents as driven by a preferred endpoint or goal in latent state-spaces. We then investigate these forms of (reactive, sentient, and intentional) behaviour using simulations. First, we simulate the aforementioned in vitro experiments, in which neuronal cultures spontaneously learn to play Pong, by implementing nested, free energy minimising processes. The simulations are then used to deconstruct the ensuing predictive behaviour—leading to the distinction between merely reactive, sentient, and intentional behaviour, with the latter formalised in terms of inductive planning. This distinction is further studied using simple machine learning benchmarks (navigation in a grid world and the Tower of Hanoi problem), that show how quickly and efficiently adaptive behaviour emerges under an inductive form of active inference.}, keywords = {2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Technology, Stimulation}, pubstate = {published}, tppubtype = {article} } Close Recent advances in theoretical biology suggest that basal cognition and sentient behaviour are emergent properties of in vitro cell cultures and neuronal networks, respectively. Such neuronal networks spontaneously learn structured behaviours in the absence of reward or reinforcement. In this paper, we characterise this kind of selforganisation through the lens of the free energy principle, i.e., as self-evidencing. We do this by first discussing the definitions of reactive and sentient behaviour in the setting of active inference, which describes the behaviour of agents that model the consequences of their actions. We then introduce a formal account of intentional behaviour, that describes agents as driven by a preferred endpoint or goal in latent state-spaces. We then investigate these forms of (reactive, sentient, and intentional) behaviour using simulations. First, we simulate the aforementioned in vitro experiments, in which neuronal cultures spontaneously learn to play Pong, by implementing nested, free energy minimising processes. The simulations are then used to deconstruct the ensuing predictive behaviour—leading to the distinction between merely reactive, sentient, and intentional behaviour, with the latter formalised in terms of inductive planning. This distinction is further studied using simple machine learning benchmarks (navigation in a grid world and the Tower of Hanoi problem), that show how quickly and efficiently adaptive behaviour emerges under an inductive form of active inference. Close http://arxiv.org/abs/2312.07547 doi:10.48550/arXiv.2312.07547 Close
	Elliott, Matthew A T; Schweiger, Hunter E; Robbins, Ash; Vera-Choqqueccota, Samira; Ehrlich, Drew; Hernandez, Sebastian; Voitiuk, Kateryna; Geng, Jinghui; Sevetson, Jess L; Core, Cordero; Rosen, Yohei M; Teodorescu, Mircea; Wagner, Nico O; Haussler, David; Mostajo-Radji, Mohammed A Internet-Connected Cortical Organoids for Project-Based Stem Cell and Neuroscience Education Journal Article eNeuro, 2023. Abstract \| Links \| BibTeX \| Tags: 3D Culture, Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Organoids, Spike Sorting, Stimulation @article{Elliott2023, title = {Internet-Connected Cortical Organoids for Project-Based Stem Cell and Neuroscience Education}, author = {Matthew A. T. Elliott and Hunter E. Schweiger and Ash Robbins and Samira Vera-Choqqueccota and Drew Ehrlich and Sebastian Hernandez and Kateryna Voitiuk and Jinghui Geng and Jess L. Sevetson and Cordero Core and Yohei M. Rosen and Mircea Teodorescu and Nico O. Wagner and David Haussler and Mohammed A. Mostajo-Radji}, url = {https://www.eneuro.org/lookup/doi/10.1523/ENEURO.0308-23.2023}, doi = {10.1523/ENEURO.0308-23.2023}, year = {2023}, date = {2023-11-28}, journal = {eNeuro}, abstract = {The introduction of Internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell (PSC)-derived cortical organoids in two different settings: using microscopy to monitor organoid growth in an introductory tissue culture course and using high-density (HD) multielectrode arrays (MEAs) to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training.}, keywords = {3D Culture, Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Organoids, Spike Sorting, Stimulation}, pubstate = {published}, tppubtype = {article} } Close The introduction of Internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell (PSC)-derived cortical organoids in two different settings: using microscopy to monitor organoid growth in an introductory tissue culture course and using high-density (HD) multielectrode arrays (MEAs) to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training. Close https://www.eneuro.org/lookup/doi/10.1523/ENEURO.0308-23.2023 doi:10.1523/ENEURO.0308-23.2023 Close
	Kobayashi, Toki; Shimba, Kenta; Kotani, Kiyoshi; Jimbo, Yasuhiko Measuring and Inducing the Plasticity of Single-Neuron Scale at Multiple Points Conference ISSS Xplore, 2023. Abstract \| Links \| BibTeX \| Tags: HD-MEA, MaxOne, Primary Neuronal Cell Culture, Stimulation @conference{Kobayashi2023, title = {Measuring and Inducing the Plasticity of Single-Neuron Scale at Multiple Points}, author = {Toki Kobayashi and Kenta Shimba and Kiyoshi Kotani and Yasuhiko Jimbo}, url = {https://ieeexplore.ieee.org/abstract/document/10322076}, doi = {10.1109/BMEiCON60347.2023.10322076}, year = {2023}, date = {2023-11-22}, journal = {IEEE Xplore}, publisher = {ISSS Xplore}, abstract = {Information processing in the brain is supported by the plasticity of the connections of neurons in biological neuronal networks. There is a gap between our understanding on plasticity of individual connections and that of the neuronal networks. Here, we aimed to induce and measure plasticity at the connections of individual neurons and at the network level. We achieved inducing plasticity with a combination of single cell stimulation by optogenetics and high-resolution extracellular potentials recording by high-density microelectrode array. Spike timing plasticity in a single neuron was successfully measured. Although we also tried to induce synaptic potentiation by tetanus stimulation, no significant change was observed. In the future, we will investigate how the plasticity of individual connections changes dynamics of entire network.}, keywords = {HD-MEA, MaxOne, Primary Neuronal Cell Culture, Stimulation}, pubstate = {published}, tppubtype = {conference} } Close Information processing in the brain is supported by the plasticity of the connections of neurons in biological neuronal networks. There is a gap between our understanding on plasticity of individual connections and that of the neuronal networks. Here, we aimed to induce and measure plasticity at the connections of individual neurons and at the network level. We achieved inducing plasticity with a combination of single cell stimulation by optogenetics and high-resolution extracellular potentials recording by high-density microelectrode array. Spike timing plasticity in a single neuron was successfully measured. Although we also tried to induce synaptic potentiation by tetanus stimulation, no significant change was observed. In the future, we will investigate how the plasticity of individual connections changes dynamics of entire network. Close https://ieeexplore.ieee.org/abstract/document/10322076 doi:10.1109/BMEiCON60347.2023.10322076 Close
	Tamatani, Chie; Shimba, Kenta; andYasuhiko Jimbo, Kiyoshi Kotani Activity- and Spatial-dependent Variations in Axonal Conduction Recorded from Microtunnel Electrodes Conference IEEE Xplore, 2023. Abstract \| Links \| BibTeX \| Tags: HD-MEA, MaxOne @conference{Tamatani2023, title = {Activity- and Spatial-dependent Variations in Axonal Conduction Recorded from Microtunnel Electrodes}, author = {Chie Tamatani and Kenta Shimba and Kiyoshi Kotani andYasuhiko Jimbo }, url = {https://ieeexplore.ieee.org/abstract/document/10321980}, doi = {10.1109/BMEiCON60347.2023.10321980}, year = {2023}, date = {2023-11-22}, publisher = {IEEE Xplore}, abstract = {Axons are not simple transmission cables in neuronal networks, but they are directly involved in information processing. We developed a novel culture device that aims to assess axonal conduction properties. The microdevice consists of microtunnels directly fabricated on high-density microelectrode array. Neuron growth and axon isolation were confirmed by immunofluorescent staining and neural activity recording. Several dozens of electrodes were detected from each tunnel and signals had enough S/N ratio to handle each spike event. Activity- and spatial-dependent variations in conduction velocity were observed. These results suggest that our microdevice is feasible to study axonal information processing.}, keywords = {HD-MEA, MaxOne}, pubstate = {published}, tppubtype = {conference} } Close Axons are not simple transmission cables in neuronal networks, but they are directly involved in information processing. We developed a novel culture device that aims to assess axonal conduction properties. The microdevice consists of microtunnels directly fabricated on high-density microelectrode array. Neuron growth and axon isolation were confirmed by immunofluorescent staining and neural activity recording. Several dozens of electrodes were detected from each tunnel and signals had enough S/N ratio to handle each spike event. Activity- and spatial-dependent variations in conduction velocity were observed. These results suggest that our microdevice is feasible to study axonal information processing. Close https://ieeexplore.ieee.org/abstract/document/10321980 doi:10.1109/BMEiCON60347.2023.10321980 Close
	Sawada, Tomoyo; Barbosa, André R; Araujo, Bruno; McCord, Alejandra E; D’Ignazio, Laura; Benjamin, Kynon J M; Sheehan, Bonna; Zabolocki, Michael; Feltrin, Arthur; Arora, Ria; Brandtjen, Anna C; Kleinman, Joel E; Hyde, Thomas M; Bardy, Cedric; Weinberger, Daniel R; Paquola, Apuã C M; Erwin, Jennifer A Recapitulation of Perturbed Striatal Gene Expression Dynamics of Donor’s Brains With Ventral Forebrain Organoids Derived From the Same Individuals With Schizophrenia Journal Article American Journal of Psychiatry, 2023, ISSN: 0002-953X. Abstract \| Links \| BibTeX \| Tags: 3D Culture, Activity Scan Assay, HD-MEA, MaxTwo, Network Assay, Organoids @article{Tomoyo2023, title = {Recapitulation of Perturbed Striatal Gene Expression Dynamics of Donor’s Brains With Ventral Forebrain Organoids Derived From the Same Individuals With Schizophrenia}, author = {Tomoyo Sawada and André R. Barbosa and Bruno Araujo and Alejandra E. McCord and Laura D’Ignazio and Kynon J.M. Benjamin and Bonna Sheehan and Michael Zabolocki and Arthur Feltrin and Ria Arora and Anna C. Brandtjen and Joel E. Kleinman and Thomas M. Hyde and Cedric Bardy and Daniel R. Weinberger and Apuã C.M. Paquola and Jennifer A. Erwin}, url = {https://ajp.psychiatryonline.org/doi/10.1176/appi.ajp.20220723}, doi = {10.1176/appi.ajp.20220723}, issn = {0002-953X}, year = {2023}, date = {2023-11-02}, journal = {American Journal of Psychiatry}, abstract = {Objective: Schizophrenia is a brain disorder that originates during neurodevelopment and has complex genetic and environmental etiologies. Despite decades of clinical evidence of altered striatal function in affected patients, studies examining its cellular and molecular mechanisms in humans are limited. To explore neurodevelopmental alterations in the striatum associated with schizophrenia, the authors established a method for the differentiation of induced pluripotent stem cells (iPSCs) into ventral forebrain organoids (VFOs). Methods: VFOs were generated from postmortem dural fibroblast–derived iPSCs of four individuals with schizophrenia and four neurotypical control individuals for whom postmortem caudate genotypes and transcriptomic data were profiled in the BrainSeq neurogenomics consortium. Individuals were selected such that the two groups had nonoverlapping schizophrenia polygenic risk scores (PRSs). Results: Single-cell RNA sequencing analyses of VFOs revealed differences in developmental trajectory between schizophrenia and control individuals in which inhibitory neuronal cells from the patients exhibited accelerated maturation. Furthermore, upregulated genes in inhibitory neurons in schizophrenia VFOs showed a significant overlap with upregulated genes in postmortem caudate tissue of individuals with schizophrenia compared with control individuals, including the donors of the iPSC cohort. Conclusions: The findings suggest that striatal neurons derived from high-PRS individuals with schizophrenia carry abnormalities that originated during early brain development and that the VFO model can recapitulate disease-relevant cell type–specific neurodevelopmental phenotypes in a dish.}, keywords = {3D Culture, Activity Scan Assay, HD-MEA, MaxTwo, Network Assay, Organoids}, pubstate = {published}, tppubtype = {article} } Close Objective: Schizophrenia is a brain disorder that originates during neurodevelopment and has complex genetic and environmental etiologies. Despite decades of clinical evidence of altered striatal function in affected patients, studies examining its cellular and molecular mechanisms in humans are limited. To explore neurodevelopmental alterations in the striatum associated with schizophrenia, the authors established a method for the differentiation of induced pluripotent stem cells (iPSCs) into ventral forebrain organoids (VFOs). Methods: VFOs were generated from postmortem dural fibroblast–derived iPSCs of four individuals with schizophrenia and four neurotypical control individuals for whom postmortem caudate genotypes and transcriptomic data were profiled in the BrainSeq neurogenomics consortium. Individuals were selected such that the two groups had nonoverlapping schizophrenia polygenic risk scores (PRSs). Results: Single-cell RNA sequencing analyses of VFOs revealed differences in developmental trajectory between schizophrenia and control individuals in which inhibitory neuronal cells from the patients exhibited accelerated maturation. Furthermore, upregulated genes in inhibitory neurons in schizophrenia VFOs showed a significant overlap with upregulated genes in postmortem caudate tissue of individuals with schizophrenia compared with control individuals, including the donors of the iPSC cohort. Conclusions: The findings suggest that striatal neurons derived from high-PRS individuals with schizophrenia carry abnormalities that originated during early brain development and that the VFO model can recapitulate disease-relevant cell type–specific neurodevelopmental phenotypes in a dish. Close https://ajp.psychiatryonline.org/doi/10.1176/appi.ajp.20220723 doi:10.1176/appi.ajp.20220723 Close
	Nakajima, Ryota; Shirakami, Arata; Tsumura, Hayato; Matsuda, Kouki; Nakamura, Eita; Shimono, Masanori Mutual generation in neuronal activity across the brain via deep neural approach, and its network interpretation Journal Article Communications Biology, 2023. Abstract \| Links \| BibTeX \| Tags: Brain Slice, HD-MEA, MaxOne, MEA Technology @article{Nakajima2023, title = {Mutual generation in neuronal activity across the brain via deep neural approach, and its network interpretation}, author = {Ryota Nakajima and Arata Shirakami and Hayato Tsumura and Kouki Matsuda and Eita Nakamura and Masanori Shimono}, url = {https://www.nature.com/articles/s42003-023-05453-2}, doi = {10.1038/s42003-023-05453-2}, year = {2023}, date = {2023-10-31}, journal = {Communications Biology}, abstract = {In the brain, many regions work in a network-like association, yet it is not known how durable these associations are in terms of activity and could survive without structural connections. To assess the association or similarity between brain regions with a generating approach, this study evaluated the similarity of activities of neurons within each region after disconnecting between regions. The “generation” approach here refers to using a multi-layer LSTM (Long Short-Term Memory) model to learn the rules of activity generation in one region and then apply that knowledge to generate activity in other regions. Surprisingly, the results revealed that activity generation from one region to disconnected regions was possible with similar accuracy to generation between the same regions in many cases. Notably, firing rates and synchronization of firing between neuron pairs, often used as neuronal representations, could be reproduced with precision. Additionally, accuracies were associated with the relative angle between brain regions and the strength of the structural connections that initially connected them. This outcome enables us to look into trends governing non-uniformity of the cortex based on the potential to generate informative data and reduces the need for animal experiments.}, keywords = {Brain Slice, HD-MEA, MaxOne, MEA Technology}, pubstate = {published}, tppubtype = {article} } Close In the brain, many regions work in a network-like association, yet it is not known how durable these associations are in terms of activity and could survive without structural connections. To assess the association or similarity between brain regions with a generating approach, this study evaluated the similarity of activities of neurons within each region after disconnecting between regions. The “generation” approach here refers to using a multi-layer LSTM (Long Short-Term Memory) model to learn the rules of activity generation in one region and then apply that knowledge to generate activity in other regions. Surprisingly, the results revealed that activity generation from one region to disconnected regions was possible with similar accuracy to generation between the same regions in many cases. Notably, firing rates and synchronization of firing between neuron pairs, often used as neuronal representations, could be reproduced with precision. Additionally, accuracies were associated with the relative angle between brain regions and the strength of the structural connections that initially connected them. This outcome enables us to look into trends governing non-uniformity of the cortex based on the potential to generate informative data and reduces the need for animal experiments. Close https://www.nature.com/articles/s42003-023-05453-2 doi:10.1038/s42003-023-05453-2 Close
	Duru, Jens; Rüfenacht, Arielle; Löhle, Josephine; Pozzi, Marcello; Forró, Csaba; Ledermann, Linus; Bernardi, Aeneas; Matter, Michael; Renia, André; Simona, Benjamin; Tringides, Christina M; Bernhard, Stéphane; Ihle, Stephan J; Hengsteler, Julian; Maurer, Benedikt; Zhanga, Xinyu; Nakatsuka, Nako Driving electrochemical reactions at the microscale using CMOS microelectrode arrays Journal Article Lab on a Chip, 2023, ISSN: 1473-0189. Abstract \| Links \| BibTeX \| Tags: HD-MEA, MaxOne, Primary Neuronal Cell Culture, Stimulation @article{Duru2023c, title = {Driving electrochemical reactions at the microscale using CMOS microelectrode arrays}, author = {Jens Duru and Arielle Rüfenacht and Josephine Löhle and Marcello Pozzi and Csaba Forró and Linus Ledermann and Aeneas Bernardi and Michael Matter and André Renia and Benjamin Simona and Christina M. Tringides and Stéphane Bernhard and Stephan J. Ihle and Julian Hengsteler and Benedikt Maurer and Xinyu Zhanga and Nako Nakatsuka}, url = {https://pubs.rsc.org/en/content/articlelanding/2023/lc/d3lc00630a}, doi = {10.1039/D3LC00630A}, issn = {1473-0189}, year = {2023}, date = {2023-10-30}, journal = {Lab on a Chip}, abstract = {Precise control of pH values at electrode interfaces enables the systematic investigation of pH-dependent processes by electrochemical means. In this work, we employed high-density complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs) as miniaturized systems to induce and confine electrochemical reactions in areas corresponding to the pitch of single electrodes (17.5 μm). First, we present a strategy for generating localized pH patterns on the surface of the CMOS MEA with unprecedented spatial resolution. Leveraging the versatile routing capabilities of the switch matrix beneath the CMOS MEA, we created arbitrary combinations of anodic and cathodic electrodes and hence pH patterns. Moreover, we utilized the system to produce polymeric surface patterns by additive and subtractive methods. For additive patterning, we controlled the in situ formation of polydopamine at the microelectrode surface through oxidation of free dopamine above a threshold pH > 8.5. For subtractive patterning, we removed cell-adhesive poly-L-lysine from the electrode surface and backfilled the voids with antifouling polymers. Such polymers were chosen to provide a proof-of-concept application of controlling neuronal growth via electrochemically-induced patterns on the CMOS MEA surface. Importantly, our platform is compatible with commercially available high-density MEAs and requires no custom equipment, rendering the findings generalizable and accessible.}, keywords = {HD-MEA, MaxOne, Primary Neuronal Cell Culture, Stimulation}, pubstate = {published}, tppubtype = {article} } Close Precise control of pH values at electrode interfaces enables the systematic investigation of pH-dependent processes by electrochemical means. In this work, we employed high-density complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs) as miniaturized systems to induce and confine electrochemical reactions in areas corresponding to the pitch of single electrodes (17.5 μm). First, we present a strategy for generating localized pH patterns on the surface of the CMOS MEA with unprecedented spatial resolution. Leveraging the versatile routing capabilities of the switch matrix beneath the CMOS MEA, we created arbitrary combinations of anodic and cathodic electrodes and hence pH patterns. Moreover, we utilized the system to produce polymeric surface patterns by additive and subtractive methods. For additive patterning, we controlled the in situ formation of polydopamine at the microelectrode surface through oxidation of free dopamine above a threshold pH > 8.5. For subtractive patterning, we removed cell-adhesive poly-L-lysine from the electrode surface and backfilled the voids with antifouling polymers. Such polymers were chosen to provide a proof-of-concept application of controlling neuronal growth via electrochemically-induced patterns on the CMOS MEA surface. Importantly, our platform is compatible with commercially available high-density MEAs and requires no custom equipment, rendering the findings generalizable and accessible. Close https://pubs.rsc.org/en/content/articlelanding/2023/lc/d3lc00630a doi:10.1039/D3LC00630A Close
	hiya Lv,; He, Enhui; Luo, Jinping; Liu, Yaoyao; Liang, Wei; Xu, Shihong; Zhang, Kui; Yang, Yan; Wang, Mixia; Song, Yilin; Wu, Yirong; Cai, Xinxia Using Human-Induced Pluripotent Stem Cell Derived Neurons on Microelectrode Arrays to Model Neurological Disease: A Review Journal Article Advanced Science, 2023. Abstract \| Links \| BibTeX \| Tags: Brain Slice, HD-MEA, IPSC, MEA Technology, Organoids @article{Lv2023, title = {Using Human-Induced Pluripotent Stem Cell Derived Neurons on Microelectrode Arrays to Model Neurological Disease: A Review}, author = {hiya Lv and Enhui He and Jinping Luo and Yaoyao Liu and Wei Liang and Shihong Xu and Kui Zhang and Yan Yang and Mixia Wang and Yilin Song and Yirong Wu and Xinxia Cai}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/advs.202301828}, doi = {10.1002/advs.202301828}, year = {2023}, date = {2023-10-23}, journal = {Advanced Science}, abstract = {In situ physiological signals of in vitro neural disease models are essential for studying pathogenesis and drug screening. Currently, an increasing number of in vitro neural disease models are established using human-induced pluripotent stem cell (hiPSC) derived neurons (hiPSC-DNs) to overcome interspecific gene expression differences. Microelectrode arrays (MEAs) can be readily interfaced with two-dimensional (2D), and more recently, three-dimensional (3D) neural stem cell-derived in vitro models of the human brain to monitor their physiological activity in real time. Therefore, MEAs are emerging and useful tools to model neurological disorders and disease in vitro using human iPSCs. This is enabling a real-time window into neuronal signaling at the network scale from patient derived. This paper provides a comprehensive review of MEA’s role in analyzing neural disease models established by hiPSC-DNs. It covers the significance of MEA fabrication, surface structure and modification schemes for hiPSC-DNs culturing and signal detection. Additionally, this review discusses advances in the development and use of MEA technology to study in vitro neural disease models, including epilepsy, autism spectrum developmental disorder (ASD), and others established using hiPSC-DNs. The paper also highlights the application of MEAs combined with hiPSC-DNs in detecting in vitro neurotoxic substances. Finally, the future development and outlook of multifunctional and integrated devices for in vitro medical diagnostics and treatment are discussed.}, keywords = {Brain Slice, HD-MEA, IPSC, MEA Technology, Organoids}, pubstate = {published}, tppubtype = {article} } Close In situ physiological signals of in vitro neural disease models are essential for studying pathogenesis and drug screening. Currently, an increasing number of in vitro neural disease models are established using human-induced pluripotent stem cell (hiPSC) derived neurons (hiPSC-DNs) to overcome interspecific gene expression differences. Microelectrode arrays (MEAs) can be readily interfaced with two-dimensional (2D), and more recently, three-dimensional (3D) neural stem cell-derived in vitro models of the human brain to monitor their physiological activity in real time. Therefore, MEAs are emerging and useful tools to model neurological disorders and disease in vitro using human iPSCs. This is enabling a real-time window into neuronal signaling at the network scale from patient derived. This paper provides a comprehensive review of MEA’s role in analyzing neural disease models established by hiPSC-DNs. It covers the significance of MEA fabrication, surface structure and modification schemes for hiPSC-DNs culturing and signal detection. Additionally, this review discusses advances in the development and use of MEA technology to study in vitro neural disease models, including epilepsy, autism spectrum developmental disorder (ASD), and others established using hiPSC-DNs. The paper also highlights the application of MEAs combined with hiPSC-DNs in detecting in vitro neurotoxic substances. Finally, the future development and outlook of multifunctional and integrated devices for in vitro medical diagnostics and treatment are discussed. Close https://onlinelibrary.wiley.com/doi/abs/10.1002/advs.202301828 doi:10.1002/advs.202301828 Close
	Kelley, Matt R; Chipman, Laura B; Asano, Shoh; Knott, Matthew; Howard, Samantha T; Berg, Allison P Potentiating NaV1.1 in Dravet syndrome patient iPSC-derived GABAergic neurons increases neuronal firing frequency and decreases network synchrony Journal Article bioRxiv, 2023. Abstract \| Links \| BibTeX \| Tags: Activity Scan Assay, Axon Tracking Assay, HD-MEA, IPSC, MaxTwo, MEA Technology, Network Assay, Spike Sorting @article{Kelley2023, title = {Potentiating NaV1.1 in Dravet syndrome patient iPSC-derived GABAergic neurons increases neuronal firing frequency and decreases network synchrony}, author = {Matt R Kelley and Laura B Chipman and Shoh Asano and Matthew Knott and Samantha T Howard and Allison P Berg}, url = {https://www.biorxiv.org/content/10.1101/2023.09.28.559990v1}, doi = {10.1101/2023.09.28.559990}, year = {2023}, date = {2023-09-29}, journal = {bioRxiv}, abstract = {Dravet syndrome is a developmental and epileptic encephalopathy characterized by seizures, behavioral abnormalities, developmental deficits, and elevated risk of sudden unexpected death in epilepsy (SUDEP). Most patient cases are caused by de novo loss-of-function mutations in the gene SCN1A, causing a haploinsufficiency of the alpha subunit of the voltage-gated sodium channel NaV1.1. Within the brain, NaV1.1 is primarily localized to the axons of inhibitory neurons, and decreased NaV1.1 function is hypothesized to reduce GABAergic inhibitory neurotransmission within the brain, driving neuronal network hyperexcitability and subsequent pathology. We have developed a human in vitro model of Dravet syndrome using differentiated neurons derived from patient iPSC and enriched for GABA expressing neurons. Neurons were plated on high definition multielectrode arrays (HD-MEAs), permitting recordings from the same cultures over the 7-weeks duration of study at the network, single cell, and subcellular resolution. Using this capability, we characterized the features of axonal morphology and physiology. Neurons developed increased spiking activity and synchronous network bursting. Recordings were processed through a spike sorting pipeline for curation of single unit activity and to assess the effects of pharmacological treatments. At 7-weeks, the application of the GABAAR receptor agonist muscimol eliminated network bursting, indicating the presence of GABAergic neurotransmission. To identify the role of NaV1.1 on neuronal and network activity, cultures were treated with a dose-response of the NaV1.1 potentiator δ-theraphotoxin-Hm1a. This resulted in a strong increase in firing rates of putative GABAergic neurons, an increase in the intraburst firing rate, and eliminated network bursting. These results validate that potentiation of NaV1.1 in Dravet patient iPSC-derived neurons results in decreased firing synchrony in neuronal networks through increased GABAergic neuron activity and support the use of human neurons and HD-MEAs as viable high-throughput electrophysiological platform to enable therapeutic discovery.}, keywords = {Activity Scan Assay, Axon Tracking Assay, HD-MEA, IPSC, MaxTwo, MEA Technology, Network Assay, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close Dravet syndrome is a developmental and epileptic encephalopathy characterized by seizures, behavioral abnormalities, developmental deficits, and elevated risk of sudden unexpected death in epilepsy (SUDEP). Most patient cases are caused by de novo loss-of-function mutations in the gene SCN1A, causing a haploinsufficiency of the alpha subunit of the voltage-gated sodium channel NaV1.1. Within the brain, NaV1.1 is primarily localized to the axons of inhibitory neurons, and decreased NaV1.1 function is hypothesized to reduce GABAergic inhibitory neurotransmission within the brain, driving neuronal network hyperexcitability and subsequent pathology. We have developed a human in vitro model of Dravet syndrome using differentiated neurons derived from patient iPSC and enriched for GABA expressing neurons. Neurons were plated on high definition multielectrode arrays (HD-MEAs), permitting recordings from the same cultures over the 7-weeks duration of study at the network, single cell, and subcellular resolution. Using this capability, we characterized the features of axonal morphology and physiology. Neurons developed increased spiking activity and synchronous network bursting. Recordings were processed through a spike sorting pipeline for curation of single unit activity and to assess the effects of pharmacological treatments. At 7-weeks, the application of the GABAAR receptor agonist muscimol eliminated network bursting, indicating the presence of GABAergic neurotransmission. To identify the role of NaV1.1 on neuronal and network activity, cultures were treated with a dose-response of the NaV1.1 potentiator δ-theraphotoxin-Hm1a. This resulted in a strong increase in firing rates of putative GABAergic neurons, an increase in the intraburst firing rate, and eliminated network bursting. These results validate that potentiation of NaV1.1 in Dravet patient iPSC-derived neurons results in decreased firing synchrony in neuronal networks through increased GABAergic neuron activity and support the use of human neurons and HD-MEAs as viable high-throughput electrophysiological platform to enable therapeutic discovery. Close https://www.biorxiv.org/content/10.1101/2023.09.28.559990v1 doi:10.1101/2023.09.28.559990 Close
	Metto, Abigael C; Telgkamp, Petra; McLane-Svoboda, Autumn K; Gilad, Assaf A; Pelled, Galit Closed-loop neurostimulation via expression of magnetogenetics-sensitive protein in inhibitory neurons leads to reduction of seizure activity in a rat model of epilepsy Journal Article Brain Research, 2023. Abstract \| Links \| BibTeX \| Tags: 3D Culture, closed loop stimulation, HD-MEA, MaxOne, Slices @article{Metto2023, title = {Closed-loop neurostimulation via expression of magnetogenetics-sensitive protein in inhibitory neurons leads to reduction of seizure activity in a rat model of epilepsy}, author = {Abigael C. Metto and Petra Telgkamp and Autumn K. McLane-Svoboda and Assaf A. Gilad and Galit Pelled}, url = {https://www.sciencedirect.com/science/article/pii/S0006899323003621}, doi = {https://doi.org/10.1016/j.brainres.2023.148591}, year = {2023}, date = {2023-09-24}, journal = {Brain Research}, abstract = {On-demand neurostimulation has shown success in epilepsy patients with pharmacoresistant seizures. Seizures produce magnetic fields that can be recorded using magnetoencephalography. We developed a new closed-loop approach to control seizure activity based on magnetogenetics using the electromagnetic perceptive gene (EPG) that encodes a protein that responds to magnetic fields. The EPG transgene was expressed in inhibitory interneurons under the hDlx promoter and kainic acid was used to induce acute seizures. In vivo electrophysiological signals were recorded. We found that hDlx EPG rats exhibited a significant delay in the onset of first seizure (1142.72 ± 186.35 s) compared to controls (644.03 ± 15.06 s) and significantly less seizures (4.11 ± 1.03) compared to controls (8.33 ± 1.58). These preliminary findings suggest that on-demand activation of EPG expressed in inhibitory interneurons suppresses seizure activity, and magnetogenetics via EPG may be an effective strategy to alleviate seizure severity in a closed-loop, and cell-specific fashion.}, keywords = {3D Culture, closed loop stimulation, HD-MEA, MaxOne, Slices}, pubstate = {published}, tppubtype = {article} } Close On-demand neurostimulation has shown success in epilepsy patients with pharmacoresistant seizures. Seizures produce magnetic fields that can be recorded using magnetoencephalography. We developed a new closed-loop approach to control seizure activity based on magnetogenetics using the electromagnetic perceptive gene (EPG) that encodes a protein that responds to magnetic fields. The EPG transgene was expressed in inhibitory interneurons under the hDlx promoter and kainic acid was used to induce acute seizures. In vivo electrophysiological signals were recorded. We found that hDlx EPG rats exhibited a significant delay in the onset of first seizure (1142.72 ± 186.35 s) compared to controls (644.03 ± 15.06 s) and significantly less seizures (4.11 ± 1.03) compared to controls (8.33 ± 1.58). These preliminary findings suggest that on-demand activation of EPG expressed in inhibitory interneurons suppresses seizure activity, and magnetogenetics via EPG may be an effective strategy to alleviate seizure severity in a closed-loop, and cell-specific fashion. Close https://www.sciencedirect.com/science/article/pii/S0006899323003621 doi:https://doi.org/10.1016/j.brainres.2023.148591 Close
	Levi, Timothee; Beaubois, Romain; Cheslet, Jérémy; Duenki, Tomoya; Khoyratee, Farad; Branchereau, Pascal; Ikeuchi, Yoshiho BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network Journal Article Research Square, 2023. Abstract \| Links \| BibTeX \| Tags: closed loop stimulation, MaxOne, MEA Technology, Organoids @article{Levi2023, title = {BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network}, author = {Timothee Levi and Romain Beaubois and Jérémy Cheslet and Tomoya Duenki and Farad Khoyratee and Pascal Branchereau and Yoshiho Ikeuchi}, url = {https://www.researchsquare.com}, doi = {10.21203/rs.3.rs-3191285/v1}, year = {2023}, date = {2023-09-15}, journal = {Research Square}, abstract = {Characterization and modeling of biological neural networks is a field opening to major advances in our understanding of the mechanisms governing the functioning of the brain and the different pathologies that can affect it. Recent researches in bioelectronics and neuromorphic engineering lead to the design of the new generation of neuroprosthesis. Here we show a novel real-time, biomimetic and energy-efficient neural network for bio-hybrid experiments and parallel emulation. This novel system is used to investigate and reproduce neural network dynamics. The setup is running on a digital platform using a System on Chip (SoC) featuring both Programmable Logic (PL) and processors in a Processing System (PS) part. The FPGA part is computing the biomimetic and real-time electrical activities of Hodgkin-Huxley neural network while the processors handle monitoring and communication. New methods of resource and power optimization has been applied to the FPGA to allow detailed neuron modeling with synapses showing short term plasticity. The system is validated by comparison with biological data and model. We also demonstrate the feasibility of bio-hybrid experiments with different bio-physical interface and different biological cells. The complete setup achieves communication with a fully flexible real-time device thus constituting a step towards neuromorphic-based neuroprosthesis for bioelectrical therapeutics.}, keywords = {closed loop stimulation, MaxOne, MEA Technology, Organoids}, pubstate = {published}, tppubtype = {article} } Close Characterization and modeling of biological neural networks is a field opening to major advances in our understanding of the mechanisms governing the functioning of the brain and the different pathologies that can affect it. Recent researches in bioelectronics and neuromorphic engineering lead to the design of the new generation of neuroprosthesis. Here we show a novel real-time, biomimetic and energy-efficient neural network for bio-hybrid experiments and parallel emulation. This novel system is used to investigate and reproduce neural network dynamics. The setup is running on a digital platform using a System on Chip (SoC) featuring both Programmable Logic (PL) and processors in a Processing System (PS) part. The FPGA part is computing the biomimetic and real-time electrical activities of Hodgkin-Huxley neural network while the processors handle monitoring and communication. New methods of resource and power optimization has been applied to the FPGA to allow detailed neuron modeling with synapses showing short term plasticity. The system is validated by comparison with biological data and model. We also demonstrate the feasibility of bio-hybrid experiments with different bio-physical interface and different biological cells. The complete setup achieves communication with a fully flexible real-time device thus constituting a step towards neuromorphic-based neuroprosthesis for bioelectrical therapeutics. Close https://www.researchsquare.com doi:10.21203/rs.3.rs-3191285/v1 Close
	Silverman, Jill L; Fenton, Timothy; Haouchine, Olivia; Hallam, Elizabeth; Smith, Emily; Jackson, Kiya; Rahbarian, Darlene; Canales, Cesar; Adhikari, Anna; Nord, Alex; Ben-Shalom, Roy Hyperexcitability and translational phenotypes in a preclinical model of SYNGAP1mutations Journal Article Research Square, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, Activity Scan Assay, HD-MEA, MaxOne, Network Assay, Primary Neuronal Cell Culture @article{Silverman2023, title = {Hyperexcitability and translational phenotypes in a preclinical model of SYNGAP1mutations}, author = {Jill L. Silverman and Timothy Fenton and Olivia Haouchine and Elizabeth Hallam and Emily Smith and Kiya Jackson and Darlene Rahbarian and Cesar Canales and Anna Adhikari and Alex Nord and Roy Ben-Shalom}, url = {https://www.researchsquare.com/article/rs-3246655/v1}, doi = {https://doi.org/10.21203/rs.3.rs-3246655/v1}, year = {2023}, date = {2023-09-13}, journal = {Research Square}, abstract = {SYNGAP1is a critical gene for neuronal development, synaptic structure, and function. Although rare, the disruption of SYNGAP1directly causes a genetically identi able neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability. Without functional SynGAP1 protein, patients present with intellectual disability, motor impairments, and epilepsy. Previous work using mouse models with a variety of germline and conditional mutations has helped delineate SynGAP1’s critical roles in neuronal structure and function, as well as key biochemical signaling pathways essential to synapse integrity. Homozygous loss of SYNGAP1is embryonically lethal. Heterozygous mutations of SynGAP1result in a broad range of phenotypes including increased locomotor activity, impaired working spatial memory, impaired cued fear memory, and increased stereotypic behavior. Ourinvivofunctional data, using the original germline mutation mouse line from the Huganir laboratory, corroborated robust hyperactivity and learning and memory de cits. Here, we describe impairments in the translational biomarker domain of sleep, characterized using neurophysiological data collected with wireless telemetric electroencephalography (EEG). We discoveredSyngap1+/− mice exhibited elevated spike trains in both number and duration, in addition to elevated power, most notably in the delta power band. Primary neurons fromSyngap1+/− mice displayed increased network ring activity, greater spikes per burst, and shorter inter-burst intervals between peaks using high density micro-electrode arrays (HD-MEA). This work is translational, innovative, and highly signi cant as it outlines functional impairments in Syngap1mutant mice. Simultaneously, the work utilized untethered, wireless neurophysiology that can discover potential biomarkers of Syngap1RID, for clinical trials, as it has done with other NDDs. Our work is substantial forward progress toward translational work for SynGAP1R-ID as it bridges in-vitroelectrophysiological neuronal activity and function with invivoneurophysiological brain activity and function. These data elucidate multiple quantitative, translational biomarkers invivoand invitrofor the development of treatments for SYNGAP1-related intellectual disability.}, keywords = {2D Neuronal Culture, Activity Scan Assay, HD-MEA, MaxOne, Network Assay, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close SYNGAP1is a critical gene for neuronal development, synaptic structure, and function. Although rare, the disruption of SYNGAP1directly causes a genetically identi able neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability. Without functional SynGAP1 protein, patients present with intellectual disability, motor impairments, and epilepsy. Previous work using mouse models with a variety of germline and conditional mutations has helped delineate SynGAP1’s critical roles in neuronal structure and function, as well as key biochemical signaling pathways essential to synapse integrity. Homozygous loss of SYNGAP1is embryonically lethal. Heterozygous mutations of SynGAP1result in a broad range of phenotypes including increased locomotor activity, impaired working spatial memory, impaired cued fear memory, and increased stereotypic behavior. Ourinvivofunctional data, using the original germline mutation mouse line from the Huganir laboratory, corroborated robust hyperactivity and learning and memory de cits. Here, we describe impairments in the translational biomarker domain of sleep, characterized using neurophysiological data collected with wireless telemetric electroencephalography (EEG). We discoveredSyngap1+/− mice exhibited elevated spike trains in both number and duration, in addition to elevated power, most notably in the delta power band. Primary neurons fromSyngap1+/− mice displayed increased network ring activity, greater spikes per burst, and shorter inter-burst intervals between peaks using high density micro-electrode arrays (HD-MEA). This work is translational, innovative, and highly signi cant as it outlines functional impairments in Syngap1mutant mice. Simultaneously, the work utilized untethered, wireless neurophysiology that can discover potential biomarkers of Syngap1RID, for clinical trials, as it has done with other NDDs. Our work is substantial forward progress toward translational work for SynGAP1R-ID as it bridges in-vitroelectrophysiological neuronal activity and function with invivoneurophysiological brain activity and function. These data elucidate multiple quantitative, translational biomarkers invivoand invitrofor the development of treatments for SYNGAP1-related intellectual disability. Close https://www.researchsquare.com/article/rs-3246655/v1 doi:https://doi.org/10.21203/rs.3.rs-3246655/v1 Close
	Habibollahi, Forough; Kagan, Brett J; Burkitt, Anthony N; French, Chris Critical dynamics arise during structured information presentation within embodied in vitro neuronal networks Journal Article Nature Communications, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Metrics, MEA Technology, Primary Neuronal Cell Culture @article{Habibollahi2023, title = {Critical dynamics arise during structured information presentation within embodied in vitro neuronal networks}, author = {Forough Habibollahi and Brett J. Kagan and Anthony N. Burkitt and Chris French }, url = {https://www.nature.com/articles/s41467-023-41020-3}, doi = {https://doi.org/10.1038/s41467-023-41020-3}, year = {2023}, date = {2023-08-30}, journal = {Nature Communications}, abstract = {Understanding how brains process information is an incredibly difficult task. Amongst the metrics characterising information processing in the brain, observations of dynamic near-critical states have generated significant interest. However, theoretical and experimental limitations associated with human and animal models have precluded a definite answer about when and why neural criticality arises with links from attention, to cognition, and even to consciousness. To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of ‘Pong’ to demonstrate Synthetic Biological Intelligence (SBI). We demonstrate that critical dynamics emerge when neural networks receive task-related structured sensory input, reorganizing the system to a near-critical state. Additionally, better task performance correlated with proximity to critical dynamics. However, criticality alone is insufficient for a neuronal network to demonstrate learning in the absence of additional information regarding the consequences of previous actions. These findings offer compelling support that neural criticality arises as a base feature of incoming structured information processing without the need for higher order cognition.}, keywords = {2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Metrics, MEA Technology, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close Understanding how brains process information is an incredibly difficult task. Amongst the metrics characterising information processing in the brain, observations of dynamic near-critical states have generated significant interest. However, theoretical and experimental limitations associated with human and animal models have precluded a definite answer about when and why neural criticality arises with links from attention, to cognition, and even to consciousness. To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of ‘Pong’ to demonstrate Synthetic Biological Intelligence (SBI). We demonstrate that critical dynamics emerge when neural networks receive task-related structured sensory input, reorganizing the system to a near-critical state. Additionally, better task performance correlated with proximity to critical dynamics. However, criticality alone is insufficient for a neuronal network to demonstrate learning in the absence of additional information regarding the consequences of previous actions. These findings offer compelling support that neural criticality arises as a base feature of incoming structured information processing without the need for higher order cognition. Close https://www.nature.com/articles/s41467-023-41020-3 doi:https://doi.org/10.1038/s41467-023-41020-3 Close
	Radivojevic, Milos; Punga, Anna Rostedt Functional imaging of conduction dynamics in cortical and spinal axons Journal Article eLife, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, Axon Tracking Assay, MaxOne, MEA Technology, Primary Neuronal Cell Culture @article{Radivojevic2023_2, title = {Functional imaging of conduction dynamics in cortical and spinal axons}, author = {Milos Radivojevic and Anna Rostedt Punga}, url = {https://elifesciences.org/articles/86512}, doi = {https://doi.org/10.7554/eLife.86512}, year = {2023}, date = {2023-08-22}, journal = {eLife}, abstract = {Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here, we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-cm-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 m of cortical and spinal axons in total and found specific features in their structure and function.}, keywords = {2D Neuronal Culture, Axon Tracking Assay, MaxOne, MEA Technology, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here, we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-cm-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 m of cortical and spinal axons in total and found specific features in their structure and function. Close https://elifesciences.org/articles/86512 doi:https://doi.org/10.7554/eLife.86512 Close
	Duru, Jens; Maurer, Benedikt; Doran, Ciara Giles; Jelitto, Robert; Küchler, Joël; Ihle, Stephan J; Ruff, Tobias; John, Robert; Genocchi, Barbara; Vörös, János Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays Journal Article Biosensors and Bioelectronics, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, MaxOne, Stimulation @article{Duru2023b, title = {Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays}, author = {Jens Duru and Benedikt Maurer and Ciara Giles Doran and Robert Jelitto and Joël Küchler and Stephan J. Ihle and Tobias Ruff and Robert John and Barbara Genocchi and János Vörös }, url = {https://www.sciencedirect.com/science/article/pii/S095656632300533X?via%3Dihub}, doi = {https://doi.org/10.1016/j.bios.2023.115591}, year = {2023}, date = {2023-08-18}, journal = {Biosensors and Bioelectronics}, abstract = {Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks' early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.}, keywords = {2D Neuronal Culture, HD-MEA, MaxOne, Stimulation}, pubstate = {published}, tppubtype = {article} } Close Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks' early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation. Close https://www.sciencedirect.com/science/article/pii/S095656632300533X?via%3Dihub doi:https://doi.org/10.1016/j.bios.2023.115591 Close
	Ulusan, Hasan; Diggelmann, Roland; Bartram, Julian; Magnan, Chloe; Kumar, Sreedhar; Hierlemann, Andreas Multi-Functional HD-MEA Platform for High-Resolution Impedance Imaging and Electrophysiological Recordings of Brain Slices Conference 2023 IEEE BioSensors Conference (BioSensors), IEEE, 2023, ISBN: 9798350346046. Abstract \| Links \| BibTeX \| Tags: ETH-CMOS-MEA, MEA Technology @conference{Ulusan2023, title = {Multi-Functional HD-MEA Platform for High-Resolution Impedance Imaging and Electrophysiological Recordings of Brain Slices}, author = {Hasan Ulusan and Roland Diggelmann and Julian Bartram and Chloe Magnan and Sreedhar Kumar and Andreas Hierlemann}, url = {https://ieeexplore.ieee.org/document/10280868/}, doi = {10.1109/BioSensors58001.2023.10280868}, isbn = {9798350346046}, year = {2023}, date = {2023-07-30}, booktitle = {2023 IEEE BioSensors Conference (BioSensors)}, pages = {1-4}, publisher = {IEEE}, abstract = {We present a high-resolution impedance imaging and electrophysiological recording platform and demonstrate its capabilities with brain slices. The platform is easy to operate featuring an efficient data acquisition system and user-friendly software that runs on a host computer. The data acquisi tion platform relies on an FPGA system that enable s bidirectional communication between the host computer and the high-density microelectrode array (HD-MEA). The software on the host computer helps to record and online visuali ze the HD -MEA data. Moreover, online filtering (and spike detection ) features rapid visual feedback t hat enables the experimenter to reconfigure the HD -MEA. The platform includes a custom designed pressing device to affix the brain slice on the HD-MEA and maintain good electrode-tissue contact. We validated the system with mouse acute cerebellar brain slices; high-resolution impedance imaging and electrophysiological recordings yielded data that were consistent with optical imaging. Moreover, the platform enabled the selection of highly active regions for recordings with high-density configuration s and monitor multiple neurons in the same area at single-cell resolution.}, keywords = {ETH-CMOS-MEA, MEA Technology}, pubstate = {published}, tppubtype = {conference} } Close We present a high-resolution impedance imaging and electrophysiological recording platform and demonstrate its capabilities with brain slices. The platform is easy to operate featuring an efficient data acquisition system and user-friendly software that runs on a host computer. The data acquisi tion platform relies on an FPGA system that enable s bidirectional communication between the host computer and the high-density microelectrode array (HD-MEA). The software on the host computer helps to record and online visuali ze the HD -MEA data. Moreover, online filtering (and spike detection ) features rapid visual feedback t hat enables the experimenter to reconfigure the HD -MEA. The platform includes a custom designed pressing device to affix the brain slice on the HD-MEA and maintain good electrode-tissue contact. We validated the system with mouse acute cerebellar brain slices; high-resolution impedance imaging and electrophysiological recordings yielded data that were consistent with optical imaging. Moreover, the platform enabled the selection of highly active regions for recordings with high-density configuration s and monitor multiple neurons in the same area at single-cell resolution. Close https://ieeexplore.ieee.org/document/10280868/ doi:10.1109/BioSensors58001.2023.10280868 Close
	Miyahara, Yuki; Shimba, Kenta; Kotani, Kiyoshi; Jimbo, Yasuhiko Development of a Hypersensitivity Evaluation Method for Cultured Sensory Neurons Using Electrical Activity Recording Conference IEEE EMBC 2023 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, Activity Scan Assay, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture @conference{Miyahara2023, title = {Development of a Hypersensitivity Evaluation Method for Cultured Sensory Neurons Using Electrical Activity Recording}, author = {Yuki Miyahara and Kenta Shimba and Kiyoshi Kotani and Yasuhiko Jimbo}, url = {https://arinex.com.au/EMBC/pdf/full-paper_363.pdf}, year = {2023}, date = {2023-07-27}, organization = {IEEE EMBC 2023}, abstract = {Investigation of hypersensitivity caused by peripheral sensitization progression is important for developing novel pain treatments. Existing methods cannot record plastic changes in neuronal activity because they occur over a few days. We aimed to establish an efficient method to evaluate neuronal activity alterations caused by peripheral sensitization on highdensity microelectrode arrays (HD-MEAs) which can record neuronal activity for a long time. Rat dorsal root ganglion (DRG) neurons were dissected from rat embryos and cultured on HDMEAs. DRG neurons were labeled with NeuO, live staining dye. Neurons were detected with the fluorescence signal and electrodes were selected with the fluorescence images. The number of DRG neurons, whose activity were recorded, detected based on fluorescence observation was five times greater than that based on neuronal activity. Analysis of changes in neuronal activity observed in pharmacological stimulation experiments suggested that substance P induced peripheral sensitization and enhanced capsaicin sensitivity. In addition, results of immunofluorescence staining suggested that peripheral sensitization occurred mostly in neurons that co-expressed transient receptor potential vanilloid 1 (TRPV1) and neurokinin 1 receptor (NK1R). In conclusion, we established an efficient method for assessing the effects of peripheral sensitization on DRG neurons cultured on HD-MEAs.}, keywords = {2D Neuronal Culture, Activity Scan Assay, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {conference} } Close Investigation of hypersensitivity caused by peripheral sensitization progression is important for developing novel pain treatments. Existing methods cannot record plastic changes in neuronal activity because they occur over a few days. We aimed to establish an efficient method to evaluate neuronal activity alterations caused by peripheral sensitization on highdensity microelectrode arrays (HD-MEAs) which can record neuronal activity for a long time. Rat dorsal root ganglion (DRG) neurons were dissected from rat embryos and cultured on HDMEAs. DRG neurons were labeled with NeuO, live staining dye. Neurons were detected with the fluorescence signal and electrodes were selected with the fluorescence images. The number of DRG neurons, whose activity were recorded, detected based on fluorescence observation was five times greater than that based on neuronal activity. Analysis of changes in neuronal activity observed in pharmacological stimulation experiments suggested that substance P induced peripheral sensitization and enhanced capsaicin sensitivity. In addition, results of immunofluorescence staining suggested that peripheral sensitization occurred mostly in neurons that co-expressed transient receptor potential vanilloid 1 (TRPV1) and neurokinin 1 receptor (NK1R). In conclusion, we established an efficient method for assessing the effects of peripheral sensitization on DRG neurons cultured on HD-MEAs. Close https://arinex.com.au/EMBC/pdf/full-paper_363.pdf Close
	Akita, Dai; Suwa, Eisuke; Ikeda, Narumitsu; Takahashi, Hirokazu Neural Activity and Information Processing Capacity of Neuronal Culture Conference IEEE EMBC 2023 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Stimulation @conference{Akita2023, title = {Neural Activity and Information Processing Capacity of Neuronal Culture}, author = {Dai Akita and Eisuke Suwa and Narumitsu Ikeda and Hirokazu Takahashi}, url = {https://arinex.com.au/EMBC/pdf/full-paper_654.pdf}, year = {2023}, date = {2023-07-27}, organization = {IEEE EMBC 2023}, abstract = {Whether artificial or living, neural networks perform tremendously diverse kinds of information processing, such as visual feature extraction, speech recognition, motor control, and so on. Some studies have evaluated the computational ability of living neural networks based on the performances of specific tasks, yet could not comprehensively grasp the versatile ability. In this study, we investigated dissociated culture of neurons as a physical reservoir, which generates diverse outputs through linear regression, or readout, of the dynamical states. Based on the theory of reservoir computing, the potential computational capabilities of neuronal culture were evaluated by the information processing capacity (IPC), which indicates how a target function can be achieved from the given dynamics. As a result, we found that the neuronal culture exhibited significant IPC and that IPC varied with the inter-step interval (ISI), the time step of reservoir computing. The cultures exhibited a memory capacity of 10 time steps for computation, and this memory capacity decayed at an ISI of 5 ms or shorter. In addition, the IPC had a significant positive correlation with the intensity of the evoked response relative to spontaneous activity. The multiple regression model with evoked response and ISI showed the positive effect of evoked response and 30 ms as the best ISI for IPC. These results suggest that the distinct evoked response and the optimal time step to interact with the neuronal culture are key factors to uncover computational resources from the neuronal system.}, keywords = {2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Stimulation}, pubstate = {published}, tppubtype = {conference} } Close Whether artificial or living, neural networks perform tremendously diverse kinds of information processing, such as visual feature extraction, speech recognition, motor control, and so on. Some studies have evaluated the computational ability of living neural networks based on the performances of specific tasks, yet could not comprehensively grasp the versatile ability. In this study, we investigated dissociated culture of neurons as a physical reservoir, which generates diverse outputs through linear regression, or readout, of the dynamical states. Based on the theory of reservoir computing, the potential computational capabilities of neuronal culture were evaluated by the information processing capacity (IPC), which indicates how a target function can be achieved from the given dynamics. As a result, we found that the neuronal culture exhibited significant IPC and that IPC varied with the inter-step interval (ISI), the time step of reservoir computing. The cultures exhibited a memory capacity of 10 time steps for computation, and this memory capacity decayed at an ISI of 5 ms or shorter. In addition, the IPC had a significant positive correlation with the intensity of the evoked response relative to spontaneous activity. The multiple regression model with evoked response and ISI showed the positive effect of evoked response and 30 ms as the best ISI for IPC. These results suggest that the distinct evoked response and the optimal time step to interact with the neuronal culture are key factors to uncover computational resources from the neuronal system. Close https://arinex.com.au/EMBC/pdf/full-paper_654.pdf Close
	Yamamoto, Hideaki; Hirano-Iwata, Ayumi; Sato, Shigeo Microfluidic technologies for reconstituting neuronal network functions in vitro Journal Article JSAP Review, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Microfluidics @article{Yamamoto2023, title = {Microfluidic technologies for reconstituting neuronal network functions in vitro}, author = {Hideaki Yamamoto and Ayumi Hirano-Iwata and Shigeo Sato}, url = {https://www.jstage.jst.go.jp/article/oubutsu/92/5/92_278/_article/-char/en}, doi = {10.11470/oubutsu.92.5_278}, year = {2023}, date = {2023-07-06}, journal = {JSAP Review}, abstract = {The structure and function of complex neuronal networks in the brain can be partially reconstituted in vitro by integrating cell culture and microfluidic device technologies. In this report, we review our recent studies on developing microfluidic devices to reconstitute small neuronal networks bearing a modular structure, which is a canonical structure found in the nervous systems of animals. We also describe the process of recording functional activity from the reconstituted neuronal networks. These fundamental technologies offer novel tools for investigating structure–function relationships in living neuronal networks and exploring the physical basis of biological computing in the brain.}, keywords = {2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Microfluidics}, pubstate = {published}, tppubtype = {article} } Close The structure and function of complex neuronal networks in the brain can be partially reconstituted in vitro by integrating cell culture and microfluidic device technologies. In this report, we review our recent studies on developing microfluidic devices to reconstitute small neuronal networks bearing a modular structure, which is a canonical structure found in the nervous systems of animals. We also describe the process of recording functional activity from the reconstituted neuronal networks. These fundamental technologies offer novel tools for investigating structure–function relationships in living neuronal networks and exploring the physical basis of biological computing in the brain. Close https://www.jstage.jst.go.jp/article/oubutsu/92/5/92_278/_article/-char/en doi:10.11470/oubutsu.92.5_278 Close
	McSweeney, Danny; English, Jay; Howell, Ethan; Ribbe, Fumiko; Pak, ChangHui Measuring Neuronal Network Activity Using Human Induced Neuronal Cells - Stem Cell-Based Neural Model Systems for Brain Disorders Book Chapter Methods in Molecular Biology, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Metrics, MEA Technology, Network Assay @inbook{McSweeney2023, title = {Measuring Neuronal Network Activity Using Human Induced Neuronal Cells - Stem Cell-Based Neural Model Systems for Brain Disorders}, author = {Danny McSweeney and Jay English and Ethan Howell and Fumiko Ribbe and ChangHui Pak}, url = {https://link.springer.com/protocol/10.1007/978-1-0716-3287-1_19}, year = {2023}, date = {2023-06-11}, publisher = {Methods in Molecular Biology}, abstract = {Synchronous firing of neurons, often referred to as “network activity” or “network bursting,” is an indication of a mature and synaptically connected network of neurons. We previously reported this phenomenon in 2D human neuronal in vitro models (McSweeney et al. iScience 25:105187, 2022). Using induced neurons (iNs) differentiated from human pluripotent stem cells (hPSCs) coupled with high-density microelectrodes arrays (HD-MEAs), we probed the underlying patterns of neuronal activity and found irregularities in network signaling across mutant states (McSweeney et al. iScience 25:105187, 2022). Here, we describe methods for plating cortical excitatory iNs differentiated from hPSCs on top of HD-MEAs and culturing iNs to maturity, examples of representative human wild-type Ngn2-iN data, and troubleshooting tips and tricks for the experimenter interested in integrating HD-MEAs into one’s research approach.}, keywords = {2D Neuronal Culture, Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Metrics, MEA Technology, Network Assay}, pubstate = {published}, tppubtype = {inbook} } Close Synchronous firing of neurons, often referred to as “network activity” or “network bursting,” is an indication of a mature and synaptically connected network of neurons. We previously reported this phenomenon in 2D human neuronal in vitro models (McSweeney et al. iScience 25:105187, 2022). Using induced neurons (iNs) differentiated from human pluripotent stem cells (hPSCs) coupled with high-density microelectrodes arrays (HD-MEAs), we probed the underlying patterns of neuronal activity and found irregularities in network signaling across mutant states (McSweeney et al. iScience 25:105187, 2022). Here, we describe methods for plating cortical excitatory iNs differentiated from hPSCs on top of HD-MEAs and culturing iNs to maturity, examples of representative human wild-type Ngn2-iN data, and troubleshooting tips and tricks for the experimenter interested in integrating HD-MEAs into one’s research approach. Close https://link.springer.com/protocol/10.1007/978-1-0716-3287-1_19 Close
	Zhao, Eric T; Hull, Jacob M; Hemed, Nofar Mintz; Ulusan, Hasan; Bartram, Julian; Zhang, Anqi; Wang, Pingyu; Pham, Albert; Silvia Ronchi, John Huguenard R; Hierlemann, Andreas; Melosh, Nicholas A A CMOS-based highly scalable flexible neural electrode interface Journal Article Science Advances, 2023. Abstract \| Links \| BibTeX \| Tags: 3D Culture, HD-MEA, MaxOne, Other Tissues, Slices @article{Zhao2023, title = {A CMOS-based highly scalable flexible neural electrode interface}, author = {Eric T. Zhao and Jacob M. Hull and Nofar Mintz Hemed and Hasan Ulusan and Julian Bartram and Anqi Zhang and Pingyu Wang and Albert Pham and Silvia Ronchi, John R. Huguenard and Andreas Hierlemann and Nicholas A. Melosh}, url = {https://www.science.org/doi/10.1126/sciadv.adf9524}, doi = {DOI: 10.1126/sciadv.adf9524}, year = {2023}, date = {2023-06-07}, journal = {Science Advances}, abstract = {Perception, thoughts, and actions are encoded by the coordinated activity of large neuronal populations spread over large areas. However, existing electrophysiological devices are limited by their scalability in capturing this cortex-wide activity. Here, we developed an electrode connector based on an ultra-conformable thin-film electrode array that self-assembles onto silicon microelectrode arrays enabling multithousand channel counts at a millimeter scale. The interconnects are formed using microfabricated electrode pads suspended by thin support arms, termed Flex2Chip. Capillary-assisted assembly drives the pads to deform toward the chip surface, and van der Waals forces maintain this deformation, establishing Ohmic contact. Flex2Chip arrays successfully measured extracellular action potentials ex vivo and resolved micrometer scale seizure propagation trajectories in epileptic mice. We find that seizure dynamics in absence epilepsy in the Scn8a+/− model do not have constant propagation trajectories.}, keywords = {3D Culture, HD-MEA, MaxOne, Other Tissues, Slices}, pubstate = {published}, tppubtype = {article} } Close Perception, thoughts, and actions are encoded by the coordinated activity of large neuronal populations spread over large areas. However, existing electrophysiological devices are limited by their scalability in capturing this cortex-wide activity. Here, we developed an electrode connector based on an ultra-conformable thin-film electrode array that self-assembles onto silicon microelectrode arrays enabling multithousand channel counts at a millimeter scale. The interconnects are formed using microfabricated electrode pads suspended by thin support arms, termed Flex2Chip. Capillary-assisted assembly drives the pads to deform toward the chip surface, and van der Waals forces maintain this deformation, establishing Ohmic contact. Flex2Chip arrays successfully measured extracellular action potentials ex vivo and resolved micrometer scale seizure propagation trajectories in epileptic mice. We find that seizure dynamics in absence epilepsy in the Scn8a+/− model do not have constant propagation trajectories. Close https://www.science.org/doi/10.1126/sciadv.adf9524 doi:DOI: 10.1126/sciadv.adf9524 Close
	Girardi, Gregory; Zumpano, Danielle; Goshi, Noah; Raybould, Helen; Seker, Erkin Cultured Vagal Afferent Neurons as Sensors for Intestinal Effector Molecules Journal Article biosensors, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture @article{Girardi2023, title = {Cultured Vagal Afferent Neurons as Sensors for Intestinal Effector Molecules}, author = {Gregory Girardi and Danielle Zumpano and Noah Goshi and Helen Raybould and Erkin Seker}, url = {https://www.mdpi.com/2079-6374/13/6/601}, doi = {10.3390/bios13060601}, year = {2023}, date = {2023-05-31}, journal = {biosensors}, abstract = {The gut–brain axis embodies the bi-directional communication between the gastrointestinal tract and the central nervous system (CNS), where vagal afferent neurons (VANs) serve as sensors for a variety of gut-derived signals. The gut is colonized by a large and diverse population of microorganisms that communicate via small (effector) molecules, which also act on the VAN terminals situated in the gut viscera and consequently influence many CNS processes. However, the convoluted in vivo environment makes it difficult to study the causative impact of the effector molecules on VAN activation or desensitization. Here, we report on a VAN culture and its proof-of-principle demonstration as a cell-based sensor to monitor the influence of gastrointestinal effector molecules on neuronal behavior. We initially compared the effect of surface coatings (poly-L-lysine vs. Matrigel) and culture media composition (serum vs. growth factor supplement) on neurite growth as a surrogate of VAN regeneration following tissue harvesting, where the Matrigel coating, but not the media composition, played a significant role in the increased neurite growth. We then used both live-cell calcium imaging and extracellular electrophysiological recordings to show that the VANs responded to classical effector molecules of endogenous and exogenous origin (cholecystokinin serotonin and capsaicin) in a complex fashion. We expect this study to enable platforms for screening various effector molecules and their influence on VAN activity, assessed by their information-rich electrophysiological fingerprints.}, keywords = {2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close The gut–brain axis embodies the bi-directional communication between the gastrointestinal tract and the central nervous system (CNS), where vagal afferent neurons (VANs) serve as sensors for a variety of gut-derived signals. The gut is colonized by a large and diverse population of microorganisms that communicate via small (effector) molecules, which also act on the VAN terminals situated in the gut viscera and consequently influence many CNS processes. However, the convoluted in vivo environment makes it difficult to study the causative impact of the effector molecules on VAN activation or desensitization. Here, we report on a VAN culture and its proof-of-principle demonstration as a cell-based sensor to monitor the influence of gastrointestinal effector molecules on neuronal behavior. We initially compared the effect of surface coatings (poly-L-lysine vs. Matrigel) and culture media composition (serum vs. growth factor supplement) on neurite growth as a surrogate of VAN regeneration following tissue harvesting, where the Matrigel coating, but not the media composition, played a significant role in the increased neurite growth. We then used both live-cell calcium imaging and extracellular electrophysiological recordings to show that the VANs responded to classical effector molecules of endogenous and exogenous origin (cholecystokinin serotonin and capsaicin) in a complex fashion. We expect this study to enable platforms for screening various effector molecules and their influence on VAN activity, assessed by their information-rich electrophysiological fingerprints. Close https://www.mdpi.com/2079-6374/13/6/601 doi:10.3390/bios13060601 Close
	Bartram, Julian; Franke, Felix; Kumar, Sreedhar Saseendran; Buccino, Alessio Paolo; Xue, Xiaohan; Gänswein, Tobias; Schröter, Manuel; Kim, Taehoon; Kasuba, Krishna Chaitanya; Hierlemann, Andreas Parallel reconstruction of the excitatory and inhibitory inputs received by single neurons reveals the synaptic basis of recurrent spiking Journal Article eLife, 2023. Abstract \| Links \| BibTeX \| Tags: HD-MEA, MaxOne, MEA Metrics, MEA Technology, Modeling, Primary Neuronal Cell Culture, Spike Sorting @article{Bartram2023b, title = {Parallel reconstruction of the excitatory and inhibitory inputs received by single neurons reveals the synaptic basis of recurrent spiking}, author = {Julian Bartram and Felix Franke and Sreedhar Saseendran Kumar and Alessio Paolo Buccino and Xiaohan Xue and Tobias Gänswein and Manuel Schröter and Taehoon Kim and Krishna Chaitanya Kasuba and Andreas Hierlemann}, url = {https://elifesciences.org/reviewed-preprints/86820}, doi = {10.7554/eLife.86820}, year = {2023}, date = {2023-05-17}, journal = {eLife}, abstract = {Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between the synaptic input patterns and the spiking output of individual neurons remains largely unresolved. Here, we developed, validated and applied a novel in vitro experimental platform and analytical procedures that provide – for individual neurons – simultaneous excitatory and inhibitory synaptic activity estimates during recurrent network activity. Our approach combines whole-network high-density microelectrode array (HD-MEA) recordings from rat neuronal cultures with patch clamping and enables a comprehensive mapping and characterization of active incoming connections to single postsynaptic neurons. We found that, during network states with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided precisely with the maxima of fast fluctuations in the input E/I ratio. These spike-associated E/I ratio escalations were largely due to a rapid bidirectional change in synaptic inhibition that was modulated by the network-activity level. Our approach also uncovered the underlying circuit architecture and we show that individual neurons received a few key inhibitory connections – often from special hub neurons – that were instrumental in controlling postsynaptic spiking. Balanced network theory predicts dynamical regimes governed by small and rapid input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of cortical networks in general.}, keywords = {HD-MEA, MaxOne, MEA Metrics, MEA Technology, Modeling, Primary Neuronal Cell Culture, Spike Sorting}, pubstate = {published}, tppubtype = {article} } Close Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between the synaptic input patterns and the spiking output of individual neurons remains largely unresolved. Here, we developed, validated and applied a novel in vitro experimental platform and analytical procedures that provide – for individual neurons – simultaneous excitatory and inhibitory synaptic activity estimates during recurrent network activity. Our approach combines whole-network high-density microelectrode array (HD-MEA) recordings from rat neuronal cultures with patch clamping and enables a comprehensive mapping and characterization of active incoming connections to single postsynaptic neurons. We found that, during network states with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided precisely with the maxima of fast fluctuations in the input E/I ratio. These spike-associated E/I ratio escalations were largely due to a rapid bidirectional change in synaptic inhibition that was modulated by the network-activity level. Our approach also uncovered the underlying circuit architecture and we show that individual neurons received a few key inhibitory connections – often from special hub neurons – that were instrumental in controlling postsynaptic spiking. Balanced network theory predicts dynamical regimes governed by small and rapid input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of cortical networks in general. Close https://elifesciences.org/reviewed-preprints/86820 doi:10.7554/eLife.86820 Close
	Duru, Jens; Maurer, Benedikt; Doran, Ciara Giles; Jelitto, Robert; Küchler, Joël; Ihle, Stephan J; Ruff, Tobias; John, Robert; Genocchi, Barbara; Vörös, János Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays Journal Article SSRN, 2023. Abstract \| Links \| BibTeX \| Tags: HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Spike Sorting, Stimulation @article{Duru2023, title = {Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays}, author = {Jens Duru and Benedikt Maurer and Ciara Giles Doran and Robert Jelitto and Joël Küchler and Stephan J. Ihle and Tobias Ruff and Robert John and Barbara Genocchi and János Vörös}, url = {https://www.ssrn.com/abstract=4427959}, doi = {DOI: 10.2139/ssrn.4427959}, year = {2023}, date = {2023-04-24}, journal = {SSRN}, abstract = {Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks’ early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.}, keywords = {HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Spike Sorting, Stimulation}, pubstate = {published}, tppubtype = {article} } Close Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks’ early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation. Close https://www.ssrn.com/abstract=4427959 doi:DOI: 10.2139/ssrn.4427959 Close
	Cerina, Marta; Piastra, Maria Carla; Frega, Monica The potential of in vitro neuronal networks cultured on Micro Electrode Arrays for biomedical research Journal Article Progress in Biomedical Engineering, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, 3D Culture, Brain Slice, IPSC, MEA Technology, Organoids, Primary Neuronal Cell Culture @article{Cerina2023, title = {The potential of in vitro neuronal networks cultured on Micro Electrode Arrays for biomedical research}, author = {Marta Cerina and Maria Carla Piastra and Monica Frega}, url = {https://iopscience.iop.org/article/10.1088/2516-1091/acce12}, doi = {10.1088/2516-1091/acce12}, year = {2023}, date = {2023-04-18}, journal = {Progress in Biomedical Engineering}, abstract = {In vitro neuronal models have become an important tool to study healthy and diseased neuronal circuits. The growing interest of neuroscientists to explore the dynamics of neuronal systems and the increasing need to observe, measure and manipulate not only single neurons but populations of cells pushed for technological advancement. In this sense, Micro-Electrode Arrays (MEAs) emerged as a promising technique, made of cell culture dishes with embedded micro-electrodes allowing non-invasive and relatively simple measurement of the activity of neuronal cultures at the network level. In the past decade, MEAs popularity has rapidly grown. MEA devices have been extensively used to measure the activity of neuronal cultures mainly derived from rodents. Rodent neuronal cultures on MEAs have been employed to investigate physiological mechanisms, study the effect of chemicals in neurotoxicity screenings, and model the electrophysiological phenotype of neuronal networks in different pathological conditions. With the advancements in human induced pluripotent stem cells (hiPSCs) technology, the differentiation of human neurons from the cells of adult donors became possible. hiPSCsderived neuronal networks on MEAs have been employed to develop patient-specific in vitro platforms to characterize the pathophysiological phenotype and to test drugs, paving the way towards personalized medicine. In this review, we first describe MEA technology and the information that can be obtained from MEA recordings. Then, we give an overview of studies in which MEAs have been used in combination with different neuronal systems (i.e., rodent 2D and 3D neuronal cultures, organotypic brain slices, hiPSCs-derived 2D and 3D neuronal cultures, and brain organoids) for biomedical research, including physiology studies, neurotoxicity screenings, disease modeling, and drug testing. We end by discussing potential, challenges and future perspectives of MEA technology, and providing some guidance for the choice of the neuronal model and MEA device, experimental design, data analysis and reporting for scientific publications.}, keywords = {2D Neuronal Culture, 3D Culture, Brain Slice, IPSC, MEA Technology, Organoids, Primary Neuronal Cell Culture}, pubstate = {published}, tppubtype = {article} } Close In vitro neuronal models have become an important tool to study healthy and diseased neuronal circuits. The growing interest of neuroscientists to explore the dynamics of neuronal systems and the increasing need to observe, measure and manipulate not only single neurons but populations of cells pushed for technological advancement. In this sense, Micro-Electrode Arrays (MEAs) emerged as a promising technique, made of cell culture dishes with embedded micro-electrodes allowing non-invasive and relatively simple measurement of the activity of neuronal cultures at the network level. In the past decade, MEAs popularity has rapidly grown. MEA devices have been extensively used to measure the activity of neuronal cultures mainly derived from rodents. Rodent neuronal cultures on MEAs have been employed to investigate physiological mechanisms, study the effect of chemicals in neurotoxicity screenings, and model the electrophysiological phenotype of neuronal networks in different pathological conditions. With the advancements in human induced pluripotent stem cells (hiPSCs) technology, the differentiation of human neurons from the cells of adult donors became possible. hiPSCsderived neuronal networks on MEAs have been employed to develop patient-specific in vitro platforms to characterize the pathophysiological phenotype and to test drugs, paving the way towards personalized medicine. In this review, we first describe MEA technology and the information that can be obtained from MEA recordings. Then, we give an overview of studies in which MEAs have been used in combination with different neuronal systems (i.e., rodent 2D and 3D neuronal cultures, organotypic brain slices, hiPSCs-derived 2D and 3D neuronal cultures, and brain organoids) for biomedical research, including physiology studies, neurotoxicity screenings, disease modeling, and drug testing. We end by discussing potential, challenges and future perspectives of MEA technology, and providing some guidance for the choice of the neuronal model and MEA device, experimental design, data analysis and reporting for scientific publications. Close https://iopscience.iop.org/article/10.1088/2516-1091/acce12 doi:10.1088/2516-1091/acce12 Close
	Xu, He Jax; Yao, Yao; Yao, Fenyong; Chen, Jiehui; Li, Meishi; Yang, Xianfa; Li, Sheng; Lu, Fangru; Hu, Ping; He, Shuijin; Peng, Guangdun; Jing, Naihe Generation of functional posterior spinal motor neurons from hPSCs-derived human spinal cord neural progenitor cells Journal Article Cell Regeneration, 2023. Abstract \| Links \| BibTeX \| Tags: 2D Neuronal Culture, Activity Scan Assay, Axon Tracking Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Network Assay, Organoids @article{Xu2023, title = {Generation of functional posterior spinal motor neurons from hPSCs-derived human spinal cord neural progenitor cells}, author = {He Jax Xu and Yao Yao and Fenyong Yao and Jiehui Chen and Meishi Li and Xianfa Yang and Sheng Li and Fangru Lu and Ping Hu and Shuijin He and Guangdun Peng and Naihe Jing}, url = {https://cellregeneration.springeropen.com/articles/10.1186/s13619-023-00159-6}, doi = {10.1186/s13619-023-00159-6}, year = {2023}, date = {2023-03-23}, journal = {Cell Regeneration}, abstract = {Spinal motor neurons deficiency results in a series of devastating disorders such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA) and spinal cord injury (SCI). These disorders are currently incurable, while human pluripotent stem cells (hPSCs)-derived spinal motor neurons are promising but suffered from inappropriate regional identity and functional immaturity for the study and treatment of posterior spinal cord related injuries. In this study, we have established human spinal cord neural progenitor cells (hSCNPCs) via hPSCs differentiated neuromesodermal progenitors (NMPs) and demonstrated the hSCNPCs can be continuously expanded up to 40 passages. hSCNPCs can be rapidly differentiated into posterior spinal motor neurons with high efficiency. The functional maturity has been examined in detail. Moreover, a co-culture scheme which is compatible for both neural and muscular differentiation is developed to mimic the neuromuscular junction (NMJ) formation in vitro. Together, these studies highlight the potential avenues for generating clinically relevant spinal motor neurons and modeling neuromuscular diseases through our defined hSCNPCs.}, keywords = {2D Neuronal Culture, Activity Scan Assay, Axon Tracking Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Network Assay, Organoids}, pubstate = {published}, tppubtype = {article} } Close Spinal motor neurons deficiency results in a series of devastating disorders such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA) and spinal cord injury (SCI). These disorders are currently incurable, while human pluripotent stem cells (hPSCs)-derived spinal motor neurons are promising but suffered from inappropriate regional identity and functional immaturity for the study and treatment of posterior spinal cord related injuries. In this study, we have established human spinal cord neural progenitor cells (hSCNPCs) via hPSCs differentiated neuromesodermal progenitors (NMPs) and demonstrated the hSCNPCs can be continuously expanded up to 40 passages. hSCNPCs can be rapidly differentiated into posterior spinal motor neurons with high efficiency. The functional maturity has been examined in detail. Moreover, a co-culture scheme which is compatible for both neural and muscular differentiation is developed to mimic the neuromuscular junction (NMJ) formation in vitro. Together, these studies highlight the potential avenues for generating clinically relevant spinal motor neurons and modeling neuromuscular diseases through our defined hSCNPCs. Close https://cellregeneration.springeropen.com/articles/10.1186/s13619-023-00159-6 doi:10.1186/s13619-023-00159-6 Close
	Radivojevic, Milos; Punga, Anna Rostedt Functional imaging of conduction dynamics in cortical and spinal axons Journal Article BioRxiv, 2023. Abstract \| Links \| BibTeX \| Tags: MaxOne @article{Radivojevic2023, title = {Functional imaging of conduction dynamics in cortical and spinal axons}, author = {Milos Radivojevic and Anna Rostedt Punga}, url = {https://www.biorxiv.org/content/10.1101/2023.02.28.530461v1}, doi = {https://doi.org/10.1101/2023.02.28.530461}, year = {2023}, date = {2023-03-01}, journal = {BioRxiv}, abstract = {Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-centimeter-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 meters of cortical and spinal axons in total and found specific features in their structure and function.}, keywords = {MaxOne}, pubstate = {published}, tppubtype = {article} } Close Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-centimeter-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 meters of cortical and spinal axons in total and found specific features in their structure and function. Close https://www.biorxiv.org/content/10.1101/2023.02.28.530461v1 doi:https://doi.org/10.1101/2023.02.28.530461 Close

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