Neuronal Networks - MaxWell Biosystems

Primary Cell Cultures on MaxOne MEA

Dissociated cell cultures can be plated, grown, and imaged on MaxOne MEAs. The figure shows an overlay of multiple confocal stack images: cell bodies and neurites are visible on the left side and the electrode array is focused on the right side.

What You Can Do

Single Cell Level Analysis

Isolate extracellular action potentials from individual cells easily.

Select electrodes with the best signals from each cell and improve your spike sorting.

Analyze subcellular features, such as full axonal arbors in single neurons.

Electrical signals tracked along neurites enable to investigate novel parameters, difficult to obtain with previous technologies.

High-resolution axonal action potential propagation tracking

The video shows the propagation of an AP through the axonal arbor of a single neuron. Electrical signals tracked along neurites enable to investigate novel parameters, difficult to obtain with previous technologies.

Axonal branch signals tracking

The video shows the propagation of a stimulation-induced action potential through a branching segment of an axon. To reduce noise and better reveal the action potential, 300 trials have been averaged.

Network Level Analysis

Record and/or stimulate every cell on the MEA.

MaxOne allows simultaneous recording from thousands of cells yields rich datasets for studying neuronal networks. Stimulation experiments can be designed with high flexibility to manipulate network dynamics.

Electrically image active cells on the MEA.

Localize active cells on the MEA during experiments. The optical image from fluorescence microscopy matches the electrical image obtained using MaxOne.

Study cells and networks across different spatial and temporal scales.

Action potentials and local field potentials can be simultaneously recorded by MaxOne over time scales of microseconds to months. The raster plot shows the dynamics of network activity using 1,024 active electrode sites.

Selected Publications

	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 @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 = {}, 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
	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 @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 = {}, 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 @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 = {}, 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
	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 @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 = {}, 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
	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 @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 = {}, 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 @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 = {}, 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
	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 @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 = {}, 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
	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 @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 = {}, 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 @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 = {}, 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 @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 = {}, 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 @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 = {}, 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
	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 @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 = {}, 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 @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 = {}, 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 @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 = {}, 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 @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 = {}, 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
	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 @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 = {}, 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
	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 @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 = {}, 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 @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 = {}, 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
	Qian, Junming; Guan, Xiaonan; Xie, Bing; Xu, Chuanyun; Niu, Jacqueline; Tang, Xin; Li, Charles H; Colecraft, Henry M; Jaenisch, Rudolf; Liu, Shawn X Multiplex epigenome editing of MECP2 to rescue Rett syndrome neurons Journal Article Science Translational Medicine, 2023. Abstract \| Links \| BibTeX @article{Qian2023, title = {Multiplex epigenome editing of MECP2 to rescue Rett syndrome neurons}, author = {Junming Qian and Xiaonan Guan and Bing Xie and Chuanyun Xu and Jacqueline Niu and Xin Tang and Charles H. Li and Henry M. Colecraft and Rudolf Jaenisch and X. Shawn Liu}, url = {https://www.science.org/doi/10.1126/scitranslmed.add4666}, doi = {10.1126/scitranslmed.add4666}, year = {2023}, date = {2023-01-18}, journal = {Science Translational Medicine}, abstract = {Rettsyndrome(RTT)isanX-linkedneurodevelopmental disorder caused byloss-of-function heterozygous mutationsofmethyl CpG-binding protein2(MECP2) ontheXchromosome inyoungfemales. Reactivationofthe silent wild-type MECP2 allelefromtheinactiveXchromosome (Xi)represents apromising therapeutic opportunity forfemale patients withRTT.Here,weapplied amultiple xepigenome editing approachtoreactivate MECP2 fromXiinRTThuman embryonicstemcells(hESCs) andderivedneurons.Demethyla tionofthe MECP2 promoter bydCas9-T et1withtarget single-guide RNAreactivatedMECP2 fromXiinRTThESCs without detectable off-target effects atthetranscriptional level.Neuronsderivedfrommethyla tion-edited RTThESCs maintained MECP2 reactivationandreversedthesmaller somasizeandelectrophysiological abnormalities, twohallmarks ofRTT.InRTTneurons,insulationofthemethyla tion-edited MECP2 locusbydCpf1-CT CF (acatalytically deadCpf1fusedwithCCCTC-binding factor)withtarget CRISPR RNAenhanced MECP2 reactivationandrescued RTT-relatedneuronaldefects, providing aproof-of-concept studyforepigenome editing to treatRTTandpotentially otherdominant X-linkeddiseases.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close Rettsyndrome(RTT)isanX-linkedneurodevelopmental disorder caused byloss-of-function heterozygous mutationsofmethyl CpG-binding protein2(MECP2) ontheXchromosome inyoungfemales. Reactivationofthe silent wild-type MECP2 allelefromtheinactiveXchromosome (Xi)represents apromising therapeutic opportunity forfemale patients withRTT.Here,weapplied amultiple xepigenome editing approachtoreactivate MECP2 fromXiinRTThuman embryonicstemcells(hESCs) andderivedneurons.Demethyla tionofthe MECP2 promoter bydCas9-T et1withtarget single-guide RNAreactivatedMECP2 fromXiinRTThESCs without detectable off-target effects atthetranscriptional level.Neuronsderivedfrommethyla tion-edited RTThESCs maintained MECP2 reactivationandreversedthesmaller somasizeandelectrophysiological abnormalities, twohallmarks ofRTT.InRTTneurons,insulationofthemethyla tion-edited MECP2 locusbydCpf1-CT CF (acatalytically deadCpf1fusedwithCCCTC-binding factor)withtarget CRISPR RNAenhanced MECP2 reactivationandrescued RTT-relatedneuronaldefects, providing aproof-of-concept studyforepigenome editing to treatRTTandpotentially otherdominant X-linkeddiseases. Close https://www.science.org/doi/10.1126/scitranslmed.add4666 doi:10.1126/scitranslmed.add4666 Close
	McSweeney, Danny; Gabriel, Rafael; Jin, Kang; Pang, Zhiping P; Aronow, Bruce; and Pak, ChangHui CASK loss of function differentially regulates neuronal maturation and synaptic function in human induced cortical excitatory neurons Journal Article iScience, 2022. Abstract \| Links \| BibTeX @article{McSweeney2022b, title = {CASK loss of function differentially regulates neuronal maturation and synaptic function in human induced cortical excitatory neurons}, author = {Danny McSweeney and Rafael Gabriel and Kang Jin and Zhiping P. Pang and Bruce Aronow and and ChangHui Pak}, url = {https://www.cell.com/iscience/fulltext/S2589-0042(22)01459-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2589004222014596%3Fshowall%3Dtrue}, doi = {https://doi.org/10.1016/j.isci.2022.105187}, year = {2022}, date = {2022-10-21}, journal = {iScience}, abstract = {Loss-of-function (LOF) mutations in CASK cause severe developmental pheno- types, including microcephaly with pontine and cerebellar hypoplasia, X-linked in- tellectual disability, and autism. Unraveling the pathological mechanisms of CASK-related disorders has been challenging owing to limited human cellular models to study the dynamic roles of this molecule during neuronal maturation and synapse development. Here, we investigate cell-autonomous functions of CASK in cortical excitatory induced neurons (iNs) generated from CASK knockout (KO) isogenic human embryonic stem cells (hESCs) using gene expression, mor- phometrics, and electrophysiology. While immature CASK KO iNs show robust neuronal outgrowth, mature CASK KO iNs display severe defects in syn- aptic transmission and synchronized network activity without compromising neuronal morphology and synapse numbers. In the developing human cortical excitatory neurons, CASK functions to promote both structural integrity and establishment of cortical excitatory neuronal networks. These results lay the foundation for future studies identifying suppressors of such phenotypes rele- vant to human patients.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close Loss-of-function (LOF) mutations in CASK cause severe developmental pheno- types, including microcephaly with pontine and cerebellar hypoplasia, X-linked in- tellectual disability, and autism. Unraveling the pathological mechanisms of CASK-related disorders has been challenging owing to limited human cellular models to study the dynamic roles of this molecule during neuronal maturation and synapse development. Here, we investigate cell-autonomous functions of CASK in cortical excitatory induced neurons (iNs) generated from CASK knockout (KO) isogenic human embryonic stem cells (hESCs) using gene expression, mor- phometrics, and electrophysiology. While immature CASK KO iNs show robust neuronal outgrowth, mature CASK KO iNs display severe defects in syn- aptic transmission and synchronized network activity without compromising neuronal morphology and synapse numbers. In the developing human cortical excitatory neurons, CASK functions to promote both structural integrity and establishment of cortical excitatory neuronal networks. These results lay the foundation for future studies identifying suppressors of such phenotypes rele- vant to human patients. Close https://www.cell.com/iscience/fulltext/S2589-0042(22)01459-6?_returnURL=https%3A[...] doi:https://doi.org/10.1016/j.isci.2022.105187 Close
	Kagan, Brett J; Kitchen, Andy C; Tran, Nhi T; Habibollahi, Forough; Khajehnejad, Moein; Parker, Bradyn J; Bhat, Anjali; Rollo, Ben; Razi, Adeel; Friston, Karl J In vitro neurons learn and exhibit sentience when embodied in a simulated game-world Journal Article Neuron, 2022. Abstract \| Links \| BibTeX @article{Kagan2022, title = {In vitro neurons learn and exhibit sentience when embodied in a simulated game-world}, author = {Brett J. Kagan and Andy C. Kitchen and Nhi T. Tran and Forough Habibollahi and Moein Khajehnejad and Bradyn J. Parker and Anjali Bhat and Ben Rollo and Adeel Razi and Karl J Friston }, url = {https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627322008066%3Fshowall%3Dtrue}, doi = {https://doi.org/10.1016/j.neuron.2022.09.001}, year = {2022}, date = {2022-10-12}, journal = {Neuron}, abstract = {Integrating neurons into digital systems may enable performance infeasible with silicon alone. Here, we develop DishBrain, a system that harnesses the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins are integrated with in silico computing via a high-density multielectrode array. Through electrophysiological stimulation and recording, cultures are embedded in a simulated game-world, mimicking the arcade game “Pong.” Applying implications from the theory of active inference via the free energy principle, we find apparent learning within five minutes of real-time gameplay not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organize activity in a goal-directed manner in response to sparse sensory information about the consequences of their actions, which we term synthetic biological intelligence. Future applications may provide further insights into the cellular correlates of intelligence.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close Integrating neurons into digital systems may enable performance infeasible with silicon alone. Here, we develop DishBrain, a system that harnesses the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins are integrated with in silico computing via a high-density multielectrode array. Through electrophysiological stimulation and recording, cultures are embedded in a simulated game-world, mimicking the arcade game “Pong.” Applying implications from the theory of active inference via the free energy principle, we find apparent learning within five minutes of real-time gameplay not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organize activity in a goal-directed manner in response to sparse sensory information about the consequences of their actions, which we term synthetic biological intelligence. Future applications may provide further insights into the cellular correlates of intelligence. Close https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6?_returnURL=https%3A%2[...] doi:https://doi.org/10.1016/j.neuron.2022.09.001 Close
	Habibey, Rouhollah; Striebel, Johannes; Schmieder, Felix; Czarske, Jürgen; Busskamp, Volker Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays Journal Article Frontiers in Neuroscience, 2022. Abstract \| Links \| BibTeX @article{Habibey2022, title = {Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays}, author = {Rouhollah Habibey and Johannes Striebel and Felix Schmieder and Jürgen Czarske and Volker Busskamp}, url = {https://www.frontiersin.org/articles/10.3389/fnins.2022.951964/full}, doi = {10.3389/fnins.2022.951964}, year = {2022}, date = {2022-10-04}, journal = {Frontiers in Neuroscience}, abstract = {Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications. Close https://www.frontiersin.org/articles/10.3389/fnins.2022.951964/full doi:10.3389/fnins.2022.951964 Close
	Buccino Alessio Paolo; Damart, Tanguy; Bartram Julian; Mandge Darshan; Xue Xiaohan; Zbili Mickael; Gänswein Tobias; Jaquier Aurélien; Emmenegger Vishalini; Markram Henry; Hierlemann Andreas; Van Geit Werner. A multi-modal fitting approach to construct single-neuron models with patch clamp and high-density microelectrode arrays Journal Article bioRxiv, 2022. Abstract \| Links \| BibTeX @article{Buccino2022, title = {A multi-modal fitting approach to construct single-neuron models with patch clamp and high-density microelectrode arrays}, author = {Buccino, Alessio Paolo; Damart, Tanguy; Bartram, Julian; Mandge, Darshan; Xue, Xiaohan; Zbili, Mickael; Gänswein, Tobias; Jaquier, Aurélien; Emmenegger, Vishalini; Markram, Henry; Hierlemann, Andreas; Van Geit, Werner.}, doi = {https://doi.org/10.1101/2022.08.03.502468}, year = {2022}, date = {2022-08-11}, journal = {bioRxiv}, 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 non-somatic 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 micro-electrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at sub-cellular 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 multi-modal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and to provide the field with neuronal models that are more realistic and can be better validated. Author Summary Multicompartment models are one of the most biophysically detailed representations of single neurons. The vast majority of these models are built using experimental data from somatic recordings. However, neurons are much more than just their soma and one needs recordings from distal neurites to build an accurate model. In this article, we combine the patch-clamp technique with extracellular high-density microelectrode arrays (HD-MEAs) to compensate this shortcoming. In fact, HD-MEAs readouts allow one to record the neuronal signal in the entire axonal arbor. We show that the proposed multi-modal strategy is superior to the use of patch clamp alone using an existing model as ground-truth. Finally, we show an application of this strategy on experimental data from cultured neurons.}, keywords = {}, 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 non-somatic 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 micro-electrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at sub-cellular 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 multi-modal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and to provide the field with neuronal models that are more realistic and can be better validated. Author Summary Multicompartment models are one of the most biophysically detailed representations of single neurons. The vast majority of these models are built using experimental data from somatic recordings. However, neurons are much more than just their soma and one needs recordings from distal neurites to build an accurate model. In this article, we combine the patch-clamp technique with extracellular high-density microelectrode arrays (HD-MEAs) to compensate this shortcoming. In fact, HD-MEAs readouts allow one to record the neuronal signal in the entire axonal arbor. We show that the proposed multi-modal strategy is superior to the use of patch clamp alone using an existing model as ground-truth. Finally, we show an application of this strategy on experimental data from cultured neurons. Close doi:https://doi.org/10.1101/2022.08.03.502468 Close
	Xue, Xiaohan; Buccino, Alessio Paolo; Kumar, Sreedhar Saseendran; Hierlemann, Andreas; Bartram, Julian Inferring monosynaptic connections from paired dendritic spine Ca2+ imaging and large-scale recording of extracellular spiking Journal Article Journal of Neural Engineering, 2022. Abstract \| Links \| BibTeX @article{Xue2022b, title = {Inferring monosynaptic connections from paired dendritic spine Ca2+ imaging and large-scale recording of extracellular spiking}, author = {Xiaohan Xue and Alessio Paolo Buccino and Sreedhar Saseendran Kumar and Andreas Hierlemann and Julian Bartram}, doi = {https://doi.org/10.1088/1741-2552/ac8765}, year = {2022}, date = {2022-08-11}, journal = {Journal of Neural Engineering}, abstract = {Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+ imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays (HD-MEAs). We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it on in vitro recordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+ transients based on measured spike trains in order to obtain simulated ground-truth connections. The proposed approach offers unique advantages as i) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, ii) it provides precise information of presynaptic spiking, and iii) postsynaptic spine Ca2+ signals and, finally, iv) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+ imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays (HD-MEAs). We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it on in vitro recordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+ transients based on measured spike trains in order to obtain simulated ground-truth connections. The proposed approach offers unique advantages as i) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, ii) it provides precise information of presynaptic spiking, and iii) postsynaptic spine Ca2+ signals and, finally, iv) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community. Close doi:https://doi.org/10.1088/1741-2552/ac8765 Close
	Xu, Jax H; Yao, Yao; Yao, Fenyong; Chen, Jiehui; Li, Meishi; Xianfa, ; Yang, ; 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 BioRxiv, 2022. Abstract \| Links \| BibTeX @article{Xu2022, title = {Generation of functional posterior spinal motor neurons from hPSCs-derived human spinal cord neural progenitor cells}, author = {Jax H. Xu and Yao Yao and Fenyong Yao and Jiehui Chen and Meishi Li and Xianfa and Yang and Sheng Li and Fangru Lu and Ping Hu and Shuijin He and Guangdun Peng and Naihe Jing}, url = {https://www.biorxiv.org/content/10.1101/2022.06.26.495599v1}, doi = {https://doi.org/10.1101/2022.06.26.495599}, year = {2022}, date = {2022-06-27}, journal = {BioRxiv}, 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 low-efficiency, functional immaturity and lacks of posterior cellular identity. 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 = {}, 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 low-efficiency, functional immaturity and lacks of posterior cellular identity. 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://www.biorxiv.org/content/10.1101/2022.06.26.495599v1 doi:https://doi.org/10.1101/2022.06.26.495599 Close
	Kagan, Brett J; Kitchen, Andy C; Tran, Nhi T; Parker, Bradyn J; Bhat, Anjali; Rollo, Ben; Razi, Adeel; Friston, Karl J In vitro neurons learn and exhibit sentience when embodied in a simulated game-world Journal Article bioRxiv, 2021. Abstract \| Links \| BibTeX @article{Kagan2021b, title = {In vitro neurons learn and exhibit sentience when embodied in a simulated game-world}, author = {Brett J. Kagan and Andy C. Kitchen and Nhi T. Tran and Bradyn J. Parker and Anjali Bhat and Ben Rollo and Adeel Razi and Karl J. Friston}, url = {https://www.biorxiv.org/content/10.1101/2021.12.02.471005v2}, doi = {10.1101/2021.12.02.471005}, year = {2021}, date = {2021-12-03}, journal = {bioRxiv}, abstract = {Integrating neurons into digital systems to leverage their innate intelligence may enable performance infeasible with silicon alone, along with providing insight into the cellular origin of intelligence. We developed DishBrain, a system which exhibits natural intelligence by harnessing the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins, are integrated with in silico computing via high-density multielectrode array. Through electrophysiological stimulation and recording, cultures were embedded in a simulated game-world, mimicking the arcade game ‘Pong’. Applying a previously untestable theory of active inference via the Free Energy Principle, we found that learning was apparent within five minutes of real-time gameplay, not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organise in a goal-directed manner in response to sparse sensory information about the consequences of their actions.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close Integrating neurons into digital systems to leverage their innate intelligence may enable performance infeasible with silicon alone, along with providing insight into the cellular origin of intelligence. We developed DishBrain, a system which exhibits natural intelligence by harnessing the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins, are integrated with in silico computing via high-density multielectrode array. Through electrophysiological stimulation and recording, cultures were embedded in a simulated game-world, mimicking the arcade game ‘Pong’. Applying a previously untestable theory of active inference via the Free Energy Principle, we found that learning was apparent within five minutes of real-time gameplay, not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organise in a goal-directed manner in response to sparse sensory information about the consequences of their actions. Close https://www.biorxiv.org/content/10.1101/2021.12.02.471005v2 doi:10.1101/2021.12.02.471005 Close
	Kubota, Tomoyuki; Takahashi, Hirokazu; and Nakajima, Kohei Unifying framework for information processing in stochastically driven dynamical systems Journal Article Physical Review Research, 2021. Abstract \| Links \| BibTeX @article{Kubota2023, title = {Unifying framework for information processing in stochastically driven dynamical systems}, author = {Tomoyuki Kubota and Hirokazu Takahashi and and Kohei Nakajima}, url = {https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.3.043135}, doi = {https://doi.org/10.1103/PhysRevResearch.3.043135}, year = {2021}, date = {2021-11-23}, journal = {Physical Review Research}, abstract = {A dynamical system is an information processing apparatus that encodes input streams from the external environment to its state and processes them through state transitions. The information processing capacity (IPC) is an excellent tool that comprehensively evaluates these processed inputs, providing details of unknown information processing in black box systems; however, this measure can be applied only to time-invariant systems. This paper extends the applicable range to time-variant systems and further reveals that the IPC is equivalent to coefficients of polynomial chaos (PC) expansion in more general dynamical systems. To achieve this objective, we tackle three issues. First, we establish a connection between the IPC for time-invariant systems and PC expansion, which is a type of polynomial expansion using orthogonal functions of input history as bases. We prove that the IPC corresponds to the squared norm of the coefficient vector of the basis in the PC expansion. Second, we show that an input following an arbitrary distribution can be used for the IPC, removing previous restrictions to specific input distributions. Third, we extend the conventional orthogonal bases to functions of both time and input history and propose the IPC for time-variant systems. To show the significance of our approach, we demonstrate that our measure can reveal information representations in not only machine learning networks but also a real, cultured neural network. Our generalized measure paves the way for unveiling the information processing capabilities of a wide variety of physical dynamics which have been left behind in nature.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close A dynamical system is an information processing apparatus that encodes input streams from the external environment to its state and processes them through state transitions. The information processing capacity (IPC) is an excellent tool that comprehensively evaluates these processed inputs, providing details of unknown information processing in black box systems; however, this measure can be applied only to time-invariant systems. This paper extends the applicable range to time-variant systems and further reveals that the IPC is equivalent to coefficients of polynomial chaos (PC) expansion in more general dynamical systems. To achieve this objective, we tackle three issues. First, we establish a connection between the IPC for time-invariant systems and PC expansion, which is a type of polynomial expansion using orthogonal functions of input history as bases. We prove that the IPC corresponds to the squared norm of the coefficient vector of the basis in the PC expansion. Second, we show that an input following an arbitrary distribution can be used for the IPC, removing previous restrictions to specific input distributions. Third, we extend the conventional orthogonal bases to functions of both time and input history and propose the IPC for time-variant systems. To show the significance of our approach, we demonstrate that our measure can reveal information representations in not only machine learning networks but also a real, cultured neural network. Our generalized measure paves the way for unveiling the information processing capabilities of a wide variety of physical dynamics which have been left behind in nature. Close https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.3.043135 doi:https://doi.org/10.1103/PhysRevResearch.3.043135 Close
	Frey, U; Egert, U; Jäckel, D; Sedivy, J; Ballini, M; Livi, P; Faraci, F; F. Heer, Hafizovic S; Roscic, B; Hierlemann, A Depth Recording Capabilities of Planar High-Density Microelectrode Arrays Conference 2009 4th International IEEE/EMBS Conference on Neural Engineering 2009. Abstract \| Links \| BibTeX @conference{Frey2009b, title = {Depth Recording Capabilities of Planar High-Density Microelectrode Arrays}, author = {U. Frey and U. Egert and D. Jäckel and J. Sedivy and M. Ballini and P. Livi and F. Faraci and F. Heer, S. Hafizovic and B. Roscic and A. Hierlemann}, url = {https://ieeexplore.ieee.org/document/5109270}, doi = {10.1109/NER.2009.5109270}, year = {2009}, date = {2009-04-01}, organization = {2009 4th International IEEE/EMBS Conference on Neural Engineering}, abstract = {We use a planar, CMOS-based microelectrode array (MEA) featuring 3,150 metal electrodes per mm2 and 126 recording channels to record spatially highly resolved extracellular action potentials (EAPs) from Purkinje cells (PCs) in acute cerebellar slices. An IndependentComponent-Analysis-based (ICA) spike sorter is used to reveal EAPs of single cells at subcellular resolution. Those EAPs are then used to set up a compartment model of a PC. The model is used to make and finetune estimations of the distance between MEA surface and PC soma. This distance is estimated using the amplitude-independent part of the shape of the EAPs obtained from recordings. The estimation shows that, in our preparations, we can record from PCs with the center of their soma at approximately 35 μm and 90 μm vertical distance to the chip surface.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } Close We use a planar, CMOS-based microelectrode array (MEA) featuring 3,150 metal electrodes per mm2 and 126 recording channels to record spatially highly resolved extracellular action potentials (EAPs) from Purkinje cells (PCs) in acute cerebellar slices. An IndependentComponent-Analysis-based (ICA) spike sorter is used to reveal EAPs of single cells at subcellular resolution. Those EAPs are then used to set up a compartment model of a PC. The model is used to make and finetune estimations of the distance between MEA surface and PC soma. This distance is estimated using the amplitude-independent part of the shape of the EAPs obtained from recordings. The estimation shows that, in our preparations, we can record from PCs with the center of their soma at approximately 35 μm and 90 μm vertical distance to the chip surface. Close https://ieeexplore.ieee.org/document/5109270 doi:10.1109/NER.2009.5109270 Close
	Greve, Frauke; Lichtenberg, Jan; Kirstein, Kay Uwe; Frey, Urs; Perriard, Jean Claude; Hierlemann, Andreas A perforated CMOS microchip platform for immobilization and activity monitoring of electrogenic cells Journal Article Journal of Micromechanics and Microengineering, 17 (3), pp. 462-471, 2007, ISSN: 0960-1317. Abstract \| Links \| BibTeX @article{Greve2007, title = {A perforated CMOS microchip platform for immobilization and activity monitoring of electrogenic cells}, author = {Frauke Greve and Jan Lichtenberg and Kay Uwe Kirstein and Urs Frey and Jean Claude Perriard and Andreas Hierlemann}, url = {http://iopscience.iop.org/article/10.1088/0960-1317/17/3/007/}, doi = {10.1088/0960-1317/17/3/007}, issn = {0960-1317}, year = {2007}, date = {2007-01-30}, journal = {Journal of Micromechanics and Microengineering}, volume = {17}, number = {3}, pages = {462-471}, abstract = {CMOS-based microelectrode systems offer decisive advantages over conventional micro-electrode arrays, which include the possibility to perform on-chip signal conditioning or to efficiently use larger numbers of electrodes to obtain statistically relevant data, e.g., in pharmacological drug screening. A larger number of electrodes can only be realized with the help of on-chip multiplexing and readout schemes, which require integrated electronics. Another fundamental issue in performing high-fidelity recordings from electrogenic cells is a good electrical coupling between the cells and the microelectrodes, in particular, since the recorded extracellular signals are in the range of only 10–1000 µV. In this paper we present the first CMOS microelectrode system with integrated micromechanical cell-placement features fabricated in a commercial CMOS process with subsequent post-CMOS bulk micromachining. This new microdevice aims at enabling the precise placement of single cells in the center of the electrodes to ensure an efficient use of the available electrodes, even for low-density cell cultures. Small through-chip holes have been generated at the metal-electrode sites by using a combination of bulk micromachining and reactive-ion etching. These holes act as orifices so that cell immobilization can be achieved by means of pneumatic anchoring. The chip additionally hosts integrated circuitry, i.e., multiplexers to select the respective readout electrodes, an amplifier with selectable gain (2×, 10×, 100×), and a high-pass filter (100 Hz cut-off). In this paper we show that electrical signals from most of the electrodes can be recorded, even in low-density cultures of neonatal rat cardiomyocytes, by using perforated metal electrodes and by applying a small underpressure from the backside of the chip. The measurements evidenced that, in most cases, about 90% of the electrodes were covered with single cells, approximately 4% were covered with more than one cell due to clustering and approximately 6% were not covered with any cell, mostly as a consequence of orifice clogging. After 4 days of culturing, the cells were still in place on the electrodes so that the cell electrical activity could be measured using the on-chip circuitry. Measured signal amplitudes were in the range of 500–700 µV, while the input-referred noise of the readout was below 15 µVrms (100 Hz–4 kHz bandwidth). We report on the development and fabrication of this new cell-biological tool and present first results collected during the characterization and evaluation of the chip. The recordings of electrical potentials of neonatal rat cardiomyocytes after several days in vitro, which, on the one hand, were conventionally cultured (no pneumatic anchoring) and, on the other hand, were anchored and immobilized, will be detailed.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close CMOS-based microelectrode systems offer decisive advantages over conventional micro-electrode arrays, which include the possibility to perform on-chip signal conditioning or to efficiently use larger numbers of electrodes to obtain statistically relevant data, e.g., in pharmacological drug screening. A larger number of electrodes can only be realized with the help of on-chip multiplexing and readout schemes, which require integrated electronics. Another fundamental issue in performing high-fidelity recordings from electrogenic cells is a good electrical coupling between the cells and the microelectrodes, in particular, since the recorded extracellular signals are in the range of only 10–1000 µV. In this paper we present the first CMOS microelectrode system with integrated micromechanical cell-placement features fabricated in a commercial CMOS process with subsequent post-CMOS bulk micromachining. This new microdevice aims at enabling the precise placement of single cells in the center of the electrodes to ensure an efficient use of the available electrodes, even for low-density cell cultures. Small through-chip holes have been generated at the metal-electrode sites by using a combination of bulk micromachining and reactive-ion etching. These holes act as orifices so that cell immobilization can be achieved by means of pneumatic anchoring. The chip additionally hosts integrated circuitry, i.e., multiplexers to select the respective readout electrodes, an amplifier with selectable gain (2×, 10×, 100×), and a high-pass filter (100 Hz cut-off). In this paper we show that electrical signals from most of the electrodes can be recorded, even in low-density cultures of neonatal rat cardiomyocytes, by using perforated metal electrodes and by applying a small underpressure from the backside of the chip. The measurements evidenced that, in most cases, about 90% of the electrodes were covered with single cells, approximately 4% were covered with more than one cell due to clustering and approximately 6% were not covered with any cell, mostly as a consequence of orifice clogging. After 4 days of culturing, the cells were still in place on the electrodes so that the cell electrical activity could be measured using the on-chip circuitry. Measured signal amplitudes were in the range of 500–700 µV, while the input-referred noise of the readout was below 15 µVrms (100 Hz–4 kHz bandwidth). We report on the development and fabrication of this new cell-biological tool and present first results collected during the characterization and evaluation of the chip. The recordings of electrical potentials of neonatal rat cardiomyocytes after several days in vitro, which, on the one hand, were conventionally cultured (no pneumatic anchoring) and, on the other hand, were anchored and immobilized, will be detailed. Close http://iopscience.iop.org/article/10.1088/0960-1317/17/3/007/ doi:10.1088/0960-1317/17/3/007 Close
	Heer, Flavio; Hafizovic, Sadik; Franks, Wendy; Blau, Axel; Ziegler, Christiane; Hierlemann, Andreas CMOS microelectrode array for bidirectional interaction with neuronal networks Journal Article IEEE Journal of Solid-State Circuits, 41 (7), pp. 1620-1629, 2006, ISSN: 0018-9200. Abstract \| Links \| BibTeX @article{Heer2006, title = {CMOS microelectrode array for bidirectional interaction with neuronal networks}, author = {Flavio Heer and Sadik Hafizovic and Wendy Franks and Axel Blau and Christiane Ziegler and Andreas Hierlemann}, url = {http://ieeexplore.ieee.org/document/1644873/}, doi = {10.1109/JSSC.2006.873677}, issn = {0018-9200}, year = {2006}, date = {2006-07-07}, journal = {IEEE Journal of Solid-State Circuits}, volume = {41}, number = {7}, pages = {1620-1629}, abstract = {A CMOS metal-electrode-based micro system for bidirectional communication (stimulation and recording) with neuronal cells in vitro is presented. The chip overcomes the interconnect challenge that limits today's bidirectional microelectrode arrays. The microsystem has been fabricated in an industrial CMOS technology with several post-CMOS processing steps to realize 128 biocompatible electrodes and to ensure chip stability in physiological saline. The system comprises all necessary control circuitry and on-chip A/D and D/A conversion. A modular design has been implemented, where individual stimulation- and signal-conditioning circuitry units are associated with each electrode. Stimulation signals with a resolution of 8 bits can be sent to any subset of electrodes at a rate of 60 kHz, while all electrodes of the chip are continuously sampled at a rate of 20 kHz. The circuitry at each electrode can be individually reset to its operating point in order to suppress artifacts evoked by the stimulation pulses. Biological measurements from cultured neuronal networks originating from dissociated cortical tissue of fertilized chicken eggs with amplitudes of up to 500 muVpp are presented.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close A CMOS metal-electrode-based micro system for bidirectional communication (stimulation and recording) with neuronal cells in vitro is presented. The chip overcomes the interconnect challenge that limits today's bidirectional microelectrode arrays. The microsystem has been fabricated in an industrial CMOS technology with several post-CMOS processing steps to realize 128 biocompatible electrodes and to ensure chip stability in physiological saline. The system comprises all necessary control circuitry and on-chip A/D and D/A conversion. A modular design has been implemented, where individual stimulation- and signal-conditioning circuitry units are associated with each electrode. Stimulation signals with a resolution of 8 bits can be sent to any subset of electrodes at a rate of 60 kHz, while all electrodes of the chip are continuously sampled at a rate of 20 kHz. The circuitry at each electrode can be individually reset to its operating point in order to suppress artifacts evoked by the stimulation pulses. Biological measurements from cultured neuronal networks originating from dissociated cortical tissue of fertilized chicken eggs with amplitudes of up to 500 muVpp are presented. Close http://ieeexplore.ieee.org/document/1644873/ doi:10.1109/JSSC.2006.873677 Close

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	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 @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 = {}, 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
	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 @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 = {}, 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 @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 = {}, 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
	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 @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 = {}, 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
	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 @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 = {}, 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 @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 = {}, 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
	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 @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 = {}, 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
	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 @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 = {}, 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 @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 = {}, 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 @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 = {}, 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 @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 = {}, 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
	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 @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 = {}, 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 @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 = {}, 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 @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 = {}, 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 @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 = {}, 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
	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 @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 = {}, 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
	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 @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 = {}, 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 @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 = {}, 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
	Qian, Junming; Guan, Xiaonan; Xie, Bing; Xu, Chuanyun; Niu, Jacqueline; Tang, Xin; Li, Charles H; Colecraft, Henry M; Jaenisch, Rudolf; Liu, Shawn X Multiplex epigenome editing of MECP2 to rescue Rett syndrome neurons Journal Article Science Translational Medicine, 2023. Abstract \| Links \| BibTeX @article{Qian2023, title = {Multiplex epigenome editing of MECP2 to rescue Rett syndrome neurons}, author = {Junming Qian and Xiaonan Guan and Bing Xie and Chuanyun Xu and Jacqueline Niu and Xin Tang and Charles H. Li and Henry M. Colecraft and Rudolf Jaenisch and X. Shawn Liu}, url = {https://www.science.org/doi/10.1126/scitranslmed.add4666}, doi = {10.1126/scitranslmed.add4666}, year = {2023}, date = {2023-01-18}, journal = {Science Translational Medicine}, abstract = {Rettsyndrome(RTT)isanX-linkedneurodevelopmental disorder caused byloss-of-function heterozygous mutationsofmethyl CpG-binding protein2(MECP2) ontheXchromosome inyoungfemales. Reactivationofthe silent wild-type MECP2 allelefromtheinactiveXchromosome (Xi)represents apromising therapeutic opportunity forfemale patients withRTT.Here,weapplied amultiple xepigenome editing approachtoreactivate MECP2 fromXiinRTThuman embryonicstemcells(hESCs) andderivedneurons.Demethyla tionofthe MECP2 promoter bydCas9-T et1withtarget single-guide RNAreactivatedMECP2 fromXiinRTThESCs without detectable off-target effects atthetranscriptional level.Neuronsderivedfrommethyla tion-edited RTThESCs maintained MECP2 reactivationandreversedthesmaller somasizeandelectrophysiological abnormalities, twohallmarks ofRTT.InRTTneurons,insulationofthemethyla tion-edited MECP2 locusbydCpf1-CT CF (acatalytically deadCpf1fusedwithCCCTC-binding factor)withtarget CRISPR RNAenhanced MECP2 reactivationandrescued RTT-relatedneuronaldefects, providing aproof-of-concept studyforepigenome editing to treatRTTandpotentially otherdominant X-linkeddiseases.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close Rettsyndrome(RTT)isanX-linkedneurodevelopmental disorder caused byloss-of-function heterozygous mutationsofmethyl CpG-binding protein2(MECP2) ontheXchromosome inyoungfemales. Reactivationofthe silent wild-type MECP2 allelefromtheinactiveXchromosome (Xi)represents apromising therapeutic opportunity forfemale patients withRTT.Here,weapplied amultiple xepigenome editing approachtoreactivate MECP2 fromXiinRTThuman embryonicstemcells(hESCs) andderivedneurons.Demethyla tionofthe MECP2 promoter bydCas9-T et1withtarget single-guide RNAreactivatedMECP2 fromXiinRTThESCs without detectable off-target effects atthetranscriptional level.Neuronsderivedfrommethyla tion-edited RTThESCs maintained MECP2 reactivationandreversedthesmaller somasizeandelectrophysiological abnormalities, twohallmarks ofRTT.InRTTneurons,insulationofthemethyla tion-edited MECP2 locusbydCpf1-CT CF (acatalytically deadCpf1fusedwithCCCTC-binding factor)withtarget CRISPR RNAenhanced MECP2 reactivationandrescued RTT-relatedneuronaldefects, providing aproof-of-concept studyforepigenome editing to treatRTTandpotentially otherdominant X-linkeddiseases. Close https://www.science.org/doi/10.1126/scitranslmed.add4666 doi:10.1126/scitranslmed.add4666 Close
	McSweeney, Danny; Gabriel, Rafael; Jin, Kang; Pang, Zhiping P; Aronow, Bruce; and Pak, ChangHui CASK loss of function differentially regulates neuronal maturation and synaptic function in human induced cortical excitatory neurons Journal Article iScience, 2022. Abstract \| Links \| BibTeX @article{McSweeney2022b, title = {CASK loss of function differentially regulates neuronal maturation and synaptic function in human induced cortical excitatory neurons}, author = {Danny McSweeney and Rafael Gabriel and Kang Jin and Zhiping P. Pang and Bruce Aronow and and ChangHui Pak}, url = {https://www.cell.com/iscience/fulltext/S2589-0042(22)01459-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2589004222014596%3Fshowall%3Dtrue}, doi = {https://doi.org/10.1016/j.isci.2022.105187}, year = {2022}, date = {2022-10-21}, journal = {iScience}, abstract = {Loss-of-function (LOF) mutations in CASK cause severe developmental pheno- types, including microcephaly with pontine and cerebellar hypoplasia, X-linked in- tellectual disability, and autism. Unraveling the pathological mechanisms of CASK-related disorders has been challenging owing to limited human cellular models to study the dynamic roles of this molecule during neuronal maturation and synapse development. Here, we investigate cell-autonomous functions of CASK in cortical excitatory induced neurons (iNs) generated from CASK knockout (KO) isogenic human embryonic stem cells (hESCs) using gene expression, mor- phometrics, and electrophysiology. While immature CASK KO iNs show robust neuronal outgrowth, mature CASK KO iNs display severe defects in syn- aptic transmission and synchronized network activity without compromising neuronal morphology and synapse numbers. In the developing human cortical excitatory neurons, CASK functions to promote both structural integrity and establishment of cortical excitatory neuronal networks. These results lay the foundation for future studies identifying suppressors of such phenotypes rele- vant to human patients.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close Loss-of-function (LOF) mutations in CASK cause severe developmental pheno- types, including microcephaly with pontine and cerebellar hypoplasia, X-linked in- tellectual disability, and autism. Unraveling the pathological mechanisms of CASK-related disorders has been challenging owing to limited human cellular models to study the dynamic roles of this molecule during neuronal maturation and synapse development. Here, we investigate cell-autonomous functions of CASK in cortical excitatory induced neurons (iNs) generated from CASK knockout (KO) isogenic human embryonic stem cells (hESCs) using gene expression, mor- phometrics, and electrophysiology. While immature CASK KO iNs show robust neuronal outgrowth, mature CASK KO iNs display severe defects in syn- aptic transmission and synchronized network activity without compromising neuronal morphology and synapse numbers. In the developing human cortical excitatory neurons, CASK functions to promote both structural integrity and establishment of cortical excitatory neuronal networks. These results lay the foundation for future studies identifying suppressors of such phenotypes rele- vant to human patients. Close https://www.cell.com/iscience/fulltext/S2589-0042(22)01459-6?_returnURL=https%3A[...] doi:https://doi.org/10.1016/j.isci.2022.105187 Close
	Kagan, Brett J; Kitchen, Andy C; Tran, Nhi T; Habibollahi, Forough; Khajehnejad, Moein; Parker, Bradyn J; Bhat, Anjali; Rollo, Ben; Razi, Adeel; Friston, Karl J In vitro neurons learn and exhibit sentience when embodied in a simulated game-world Journal Article Neuron, 2022. Abstract \| Links \| BibTeX @article{Kagan2022, title = {In vitro neurons learn and exhibit sentience when embodied in a simulated game-world}, author = {Brett J. Kagan and Andy C. Kitchen and Nhi T. Tran and Forough Habibollahi and Moein Khajehnejad and Bradyn J. Parker and Anjali Bhat and Ben Rollo and Adeel Razi and Karl J Friston }, url = {https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627322008066%3Fshowall%3Dtrue}, doi = {https://doi.org/10.1016/j.neuron.2022.09.001}, year = {2022}, date = {2022-10-12}, journal = {Neuron}, abstract = {Integrating neurons into digital systems may enable performance infeasible with silicon alone. Here, we develop DishBrain, a system that harnesses the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins are integrated with in silico computing via a high-density multielectrode array. Through electrophysiological stimulation and recording, cultures are embedded in a simulated game-world, mimicking the arcade game “Pong.” Applying implications from the theory of active inference via the free energy principle, we find apparent learning within five minutes of real-time gameplay not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organize activity in a goal-directed manner in response to sparse sensory information about the consequences of their actions, which we term synthetic biological intelligence. Future applications may provide further insights into the cellular correlates of intelligence.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close Integrating neurons into digital systems may enable performance infeasible with silicon alone. Here, we develop DishBrain, a system that harnesses the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins are integrated with in silico computing via a high-density multielectrode array. Through electrophysiological stimulation and recording, cultures are embedded in a simulated game-world, mimicking the arcade game “Pong.” Applying implications from the theory of active inference via the free energy principle, we find apparent learning within five minutes of real-time gameplay not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organize activity in a goal-directed manner in response to sparse sensory information about the consequences of their actions, which we term synthetic biological intelligence. Future applications may provide further insights into the cellular correlates of intelligence. Close https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6?_returnURL=https%3A%2[...] doi:https://doi.org/10.1016/j.neuron.2022.09.001 Close
	Habibey, Rouhollah; Striebel, Johannes; Schmieder, Felix; Czarske, Jürgen; Busskamp, Volker Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays Journal Article Frontiers in Neuroscience, 2022. Abstract \| Links \| BibTeX @article{Habibey2022, title = {Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays}, author = {Rouhollah Habibey and Johannes Striebel and Felix Schmieder and Jürgen Czarske and Volker Busskamp}, url = {https://www.frontiersin.org/articles/10.3389/fnins.2022.951964/full}, doi = {10.3389/fnins.2022.951964}, year = {2022}, date = {2022-10-04}, journal = {Frontiers in Neuroscience}, abstract = {Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications. Close https://www.frontiersin.org/articles/10.3389/fnins.2022.951964/full doi:10.3389/fnins.2022.951964 Close
	Buccino Alessio Paolo; Damart, Tanguy; Bartram Julian; Mandge Darshan; Xue Xiaohan; Zbili Mickael; Gänswein Tobias; Jaquier Aurélien; Emmenegger Vishalini; Markram Henry; Hierlemann Andreas; Van Geit Werner. A multi-modal fitting approach to construct single-neuron models with patch clamp and high-density microelectrode arrays Journal Article bioRxiv, 2022. Abstract \| Links \| BibTeX @article{Buccino2022, title = {A multi-modal fitting approach to construct single-neuron models with patch clamp and high-density microelectrode arrays}, author = {Buccino, Alessio Paolo; Damart, Tanguy; Bartram, Julian; Mandge, Darshan; Xue, Xiaohan; Zbili, Mickael; Gänswein, Tobias; Jaquier, Aurélien; Emmenegger, Vishalini; Markram, Henry; Hierlemann, Andreas; Van Geit, Werner.}, doi = {https://doi.org/10.1101/2022.08.03.502468}, year = {2022}, date = {2022-08-11}, journal = {bioRxiv}, 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 non-somatic 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 micro-electrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at sub-cellular 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 multi-modal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and to provide the field with neuronal models that are more realistic and can be better validated. Author Summary Multicompartment models are one of the most biophysically detailed representations of single neurons. The vast majority of these models are built using experimental data from somatic recordings. However, neurons are much more than just their soma and one needs recordings from distal neurites to build an accurate model. In this article, we combine the patch-clamp technique with extracellular high-density microelectrode arrays (HD-MEAs) to compensate this shortcoming. In fact, HD-MEAs readouts allow one to record the neuronal signal in the entire axonal arbor. We show that the proposed multi-modal strategy is superior to the use of patch clamp alone using an existing model as ground-truth. Finally, we show an application of this strategy on experimental data from cultured neurons.}, keywords = {}, 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 non-somatic 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 micro-electrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at sub-cellular 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 multi-modal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and to provide the field with neuronal models that are more realistic and can be better validated. Author Summary Multicompartment models are one of the most biophysically detailed representations of single neurons. The vast majority of these models are built using experimental data from somatic recordings. However, neurons are much more than just their soma and one needs recordings from distal neurites to build an accurate model. In this article, we combine the patch-clamp technique with extracellular high-density microelectrode arrays (HD-MEAs) to compensate this shortcoming. In fact, HD-MEAs readouts allow one to record the neuronal signal in the entire axonal arbor. We show that the proposed multi-modal strategy is superior to the use of patch clamp alone using an existing model as ground-truth. Finally, we show an application of this strategy on experimental data from cultured neurons. Close doi:https://doi.org/10.1101/2022.08.03.502468 Close
	Xue, Xiaohan; Buccino, Alessio Paolo; Kumar, Sreedhar Saseendran; Hierlemann, Andreas; Bartram, Julian Inferring monosynaptic connections from paired dendritic spine Ca2+ imaging and large-scale recording of extracellular spiking Journal Article Journal of Neural Engineering, 2022. Abstract \| Links \| BibTeX @article{Xue2022b, title = {Inferring monosynaptic connections from paired dendritic spine Ca2+ imaging and large-scale recording of extracellular spiking}, author = {Xiaohan Xue and Alessio Paolo Buccino and Sreedhar Saseendran Kumar and Andreas Hierlemann and Julian Bartram}, doi = {https://doi.org/10.1088/1741-2552/ac8765}, year = {2022}, date = {2022-08-11}, journal = {Journal of Neural Engineering}, abstract = {Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+ imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays (HD-MEAs). We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it on in vitro recordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+ transients based on measured spike trains in order to obtain simulated ground-truth connections. The proposed approach offers unique advantages as i) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, ii) it provides precise information of presynaptic spiking, and iii) postsynaptic spine Ca2+ signals and, finally, iv) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+ imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays (HD-MEAs). We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it on in vitro recordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+ transients based on measured spike trains in order to obtain simulated ground-truth connections. The proposed approach offers unique advantages as i) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, ii) it provides precise information of presynaptic spiking, and iii) postsynaptic spine Ca2+ signals and, finally, iv) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community. Close doi:https://doi.org/10.1088/1741-2552/ac8765 Close
	Xu, Jax H; Yao, Yao; Yao, Fenyong; Chen, Jiehui; Li, Meishi; Xianfa, ; Yang, ; 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 BioRxiv, 2022. Abstract \| Links \| BibTeX @article{Xu2022, title = {Generation of functional posterior spinal motor neurons from hPSCs-derived human spinal cord neural progenitor cells}, author = {Jax H. Xu and Yao Yao and Fenyong Yao and Jiehui Chen and Meishi Li and Xianfa and Yang and Sheng Li and Fangru Lu and Ping Hu and Shuijin He and Guangdun Peng and Naihe Jing}, url = {https://www.biorxiv.org/content/10.1101/2022.06.26.495599v1}, doi = {https://doi.org/10.1101/2022.06.26.495599}, year = {2022}, date = {2022-06-27}, journal = {BioRxiv}, 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 low-efficiency, functional immaturity and lacks of posterior cellular identity. 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 = {}, 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 low-efficiency, functional immaturity and lacks of posterior cellular identity. 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://www.biorxiv.org/content/10.1101/2022.06.26.495599v1 doi:https://doi.org/10.1101/2022.06.26.495599 Close
	Kagan, Brett J; Kitchen, Andy C; Tran, Nhi T; Parker, Bradyn J; Bhat, Anjali; Rollo, Ben; Razi, Adeel; Friston, Karl J In vitro neurons learn and exhibit sentience when embodied in a simulated game-world Journal Article bioRxiv, 2021. Abstract \| Links \| BibTeX @article{Kagan2021b, title = {In vitro neurons learn and exhibit sentience when embodied in a simulated game-world}, author = {Brett J. Kagan and Andy C. Kitchen and Nhi T. Tran and Bradyn J. Parker and Anjali Bhat and Ben Rollo and Adeel Razi and Karl J. Friston}, url = {https://www.biorxiv.org/content/10.1101/2021.12.02.471005v2}, doi = {10.1101/2021.12.02.471005}, year = {2021}, date = {2021-12-03}, journal = {bioRxiv}, abstract = {Integrating neurons into digital systems to leverage their innate intelligence may enable performance infeasible with silicon alone, along with providing insight into the cellular origin of intelligence. We developed DishBrain, a system which exhibits natural intelligence by harnessing the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins, are integrated with in silico computing via high-density multielectrode array. Through electrophysiological stimulation and recording, cultures were embedded in a simulated game-world, mimicking the arcade game ‘Pong’. Applying a previously untestable theory of active inference via the Free Energy Principle, we found that learning was apparent within five minutes of real-time gameplay, not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organise in a goal-directed manner in response to sparse sensory information about the consequences of their actions.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close Integrating neurons into digital systems to leverage their innate intelligence may enable performance infeasible with silicon alone, along with providing insight into the cellular origin of intelligence. We developed DishBrain, a system which exhibits natural intelligence by harnessing the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins, are integrated with in silico computing via high-density multielectrode array. Through electrophysiological stimulation and recording, cultures were embedded in a simulated game-world, mimicking the arcade game ‘Pong’. Applying a previously untestable theory of active inference via the Free Energy Principle, we found that learning was apparent within five minutes of real-time gameplay, not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organise in a goal-directed manner in response to sparse sensory information about the consequences of their actions. Close https://www.biorxiv.org/content/10.1101/2021.12.02.471005v2 doi:10.1101/2021.12.02.471005 Close
	Kubota, Tomoyuki; Takahashi, Hirokazu; and Nakajima, Kohei Unifying framework for information processing in stochastically driven dynamical systems Journal Article Physical Review Research, 2021. Abstract \| Links \| BibTeX @article{Kubota2023, title = {Unifying framework for information processing in stochastically driven dynamical systems}, author = {Tomoyuki Kubota and Hirokazu Takahashi and and Kohei Nakajima}, url = {https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.3.043135}, doi = {https://doi.org/10.1103/PhysRevResearch.3.043135}, year = {2021}, date = {2021-11-23}, journal = {Physical Review Research}, abstract = {A dynamical system is an information processing apparatus that encodes input streams from the external environment to its state and processes them through state transitions. The information processing capacity (IPC) is an excellent tool that comprehensively evaluates these processed inputs, providing details of unknown information processing in black box systems; however, this measure can be applied only to time-invariant systems. This paper extends the applicable range to time-variant systems and further reveals that the IPC is equivalent to coefficients of polynomial chaos (PC) expansion in more general dynamical systems. To achieve this objective, we tackle three issues. First, we establish a connection between the IPC for time-invariant systems and PC expansion, which is a type of polynomial expansion using orthogonal functions of input history as bases. We prove that the IPC corresponds to the squared norm of the coefficient vector of the basis in the PC expansion. Second, we show that an input following an arbitrary distribution can be used for the IPC, removing previous restrictions to specific input distributions. Third, we extend the conventional orthogonal bases to functions of both time and input history and propose the IPC for time-variant systems. To show the significance of our approach, we demonstrate that our measure can reveal information representations in not only machine learning networks but also a real, cultured neural network. Our generalized measure paves the way for unveiling the information processing capabilities of a wide variety of physical dynamics which have been left behind in nature.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close A dynamical system is an information processing apparatus that encodes input streams from the external environment to its state and processes them through state transitions. The information processing capacity (IPC) is an excellent tool that comprehensively evaluates these processed inputs, providing details of unknown information processing in black box systems; however, this measure can be applied only to time-invariant systems. This paper extends the applicable range to time-variant systems and further reveals that the IPC is equivalent to coefficients of polynomial chaos (PC) expansion in more general dynamical systems. To achieve this objective, we tackle three issues. First, we establish a connection between the IPC for time-invariant systems and PC expansion, which is a type of polynomial expansion using orthogonal functions of input history as bases. We prove that the IPC corresponds to the squared norm of the coefficient vector of the basis in the PC expansion. Second, we show that an input following an arbitrary distribution can be used for the IPC, removing previous restrictions to specific input distributions. Third, we extend the conventional orthogonal bases to functions of both time and input history and propose the IPC for time-variant systems. To show the significance of our approach, we demonstrate that our measure can reveal information representations in not only machine learning networks but also a real, cultured neural network. Our generalized measure paves the way for unveiling the information processing capabilities of a wide variety of physical dynamics which have been left behind in nature. Close https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.3.043135 doi:https://doi.org/10.1103/PhysRevResearch.3.043135 Close
	Frey, U; Egert, U; Jäckel, D; Sedivy, J; Ballini, M; Livi, P; Faraci, F; F. Heer, Hafizovic S; Roscic, B; Hierlemann, A Depth Recording Capabilities of Planar High-Density Microelectrode Arrays Conference 2009 4th International IEEE/EMBS Conference on Neural Engineering 2009. Abstract \| Links \| BibTeX @conference{Frey2009b, title = {Depth Recording Capabilities of Planar High-Density Microelectrode Arrays}, author = {U. Frey and U. Egert and D. Jäckel and J. Sedivy and M. Ballini and P. Livi and F. Faraci and F. Heer, S. Hafizovic and B. Roscic and A. Hierlemann}, url = {https://ieeexplore.ieee.org/document/5109270}, doi = {10.1109/NER.2009.5109270}, year = {2009}, date = {2009-04-01}, organization = {2009 4th International IEEE/EMBS Conference on Neural Engineering}, abstract = {We use a planar, CMOS-based microelectrode array (MEA) featuring 3,150 metal electrodes per mm2 and 126 recording channels to record spatially highly resolved extracellular action potentials (EAPs) from Purkinje cells (PCs) in acute cerebellar slices. An IndependentComponent-Analysis-based (ICA) spike sorter is used to reveal EAPs of single cells at subcellular resolution. Those EAPs are then used to set up a compartment model of a PC. The model is used to make and finetune estimations of the distance between MEA surface and PC soma. This distance is estimated using the amplitude-independent part of the shape of the EAPs obtained from recordings. The estimation shows that, in our preparations, we can record from PCs with the center of their soma at approximately 35 μm and 90 μm vertical distance to the chip surface.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } Close We use a planar, CMOS-based microelectrode array (MEA) featuring 3,150 metal electrodes per mm2 and 126 recording channels to record spatially highly resolved extracellular action potentials (EAPs) from Purkinje cells (PCs) in acute cerebellar slices. An IndependentComponent-Analysis-based (ICA) spike sorter is used to reveal EAPs of single cells at subcellular resolution. Those EAPs are then used to set up a compartment model of a PC. The model is used to make and finetune estimations of the distance between MEA surface and PC soma. This distance is estimated using the amplitude-independent part of the shape of the EAPs obtained from recordings. The estimation shows that, in our preparations, we can record from PCs with the center of their soma at approximately 35 μm and 90 μm vertical distance to the chip surface. Close https://ieeexplore.ieee.org/document/5109270 doi:10.1109/NER.2009.5109270 Close
	Greve, Frauke; Lichtenberg, Jan; Kirstein, Kay Uwe; Frey, Urs; Perriard, Jean Claude; Hierlemann, Andreas A perforated CMOS microchip platform for immobilization and activity monitoring of electrogenic cells Journal Article Journal of Micromechanics and Microengineering, 17 (3), pp. 462-471, 2007, ISSN: 0960-1317. Abstract \| Links \| BibTeX @article{Greve2007, title = {A perforated CMOS microchip platform for immobilization and activity monitoring of electrogenic cells}, author = {Frauke Greve and Jan Lichtenberg and Kay Uwe Kirstein and Urs Frey and Jean Claude Perriard and Andreas Hierlemann}, url = {http://iopscience.iop.org/article/10.1088/0960-1317/17/3/007/}, doi = {10.1088/0960-1317/17/3/007}, issn = {0960-1317}, year = {2007}, date = {2007-01-30}, journal = {Journal of Micromechanics and Microengineering}, volume = {17}, number = {3}, pages = {462-471}, abstract = {CMOS-based microelectrode systems offer decisive advantages over conventional micro-electrode arrays, which include the possibility to perform on-chip signal conditioning or to efficiently use larger numbers of electrodes to obtain statistically relevant data, e.g., in pharmacological drug screening. A larger number of electrodes can only be realized with the help of on-chip multiplexing and readout schemes, which require integrated electronics. Another fundamental issue in performing high-fidelity recordings from electrogenic cells is a good electrical coupling between the cells and the microelectrodes, in particular, since the recorded extracellular signals are in the range of only 10–1000 µV. In this paper we present the first CMOS microelectrode system with integrated micromechanical cell-placement features fabricated in a commercial CMOS process with subsequent post-CMOS bulk micromachining. This new microdevice aims at enabling the precise placement of single cells in the center of the electrodes to ensure an efficient use of the available electrodes, even for low-density cell cultures. Small through-chip holes have been generated at the metal-electrode sites by using a combination of bulk micromachining and reactive-ion etching. These holes act as orifices so that cell immobilization can be achieved by means of pneumatic anchoring. The chip additionally hosts integrated circuitry, i.e., multiplexers to select the respective readout electrodes, an amplifier with selectable gain (2×, 10×, 100×), and a high-pass filter (100 Hz cut-off). In this paper we show that electrical signals from most of the electrodes can be recorded, even in low-density cultures of neonatal rat cardiomyocytes, by using perforated metal electrodes and by applying a small underpressure from the backside of the chip. The measurements evidenced that, in most cases, about 90% of the electrodes were covered with single cells, approximately 4% were covered with more than one cell due to clustering and approximately 6% were not covered with any cell, mostly as a consequence of orifice clogging. After 4 days of culturing, the cells were still in place on the electrodes so that the cell electrical activity could be measured using the on-chip circuitry. Measured signal amplitudes were in the range of 500–700 µV, while the input-referred noise of the readout was below 15 µVrms (100 Hz–4 kHz bandwidth). We report on the development and fabrication of this new cell-biological tool and present first results collected during the characterization and evaluation of the chip. The recordings of electrical potentials of neonatal rat cardiomyocytes after several days in vitro, which, on the one hand, were conventionally cultured (no pneumatic anchoring) and, on the other hand, were anchored and immobilized, will be detailed.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close CMOS-based microelectrode systems offer decisive advantages over conventional micro-electrode arrays, which include the possibility to perform on-chip signal conditioning or to efficiently use larger numbers of electrodes to obtain statistically relevant data, e.g., in pharmacological drug screening. A larger number of electrodes can only be realized with the help of on-chip multiplexing and readout schemes, which require integrated electronics. Another fundamental issue in performing high-fidelity recordings from electrogenic cells is a good electrical coupling between the cells and the microelectrodes, in particular, since the recorded extracellular signals are in the range of only 10–1000 µV. In this paper we present the first CMOS microelectrode system with integrated micromechanical cell-placement features fabricated in a commercial CMOS process with subsequent post-CMOS bulk micromachining. This new microdevice aims at enabling the precise placement of single cells in the center of the electrodes to ensure an efficient use of the available electrodes, even for low-density cell cultures. Small through-chip holes have been generated at the metal-electrode sites by using a combination of bulk micromachining and reactive-ion etching. These holes act as orifices so that cell immobilization can be achieved by means of pneumatic anchoring. The chip additionally hosts integrated circuitry, i.e., multiplexers to select the respective readout electrodes, an amplifier with selectable gain (2×, 10×, 100×), and a high-pass filter (100 Hz cut-off). In this paper we show that electrical signals from most of the electrodes can be recorded, even in low-density cultures of neonatal rat cardiomyocytes, by using perforated metal electrodes and by applying a small underpressure from the backside of the chip. The measurements evidenced that, in most cases, about 90% of the electrodes were covered with single cells, approximately 4% were covered with more than one cell due to clustering and approximately 6% were not covered with any cell, mostly as a consequence of orifice clogging. After 4 days of culturing, the cells were still in place on the electrodes so that the cell electrical activity could be measured using the on-chip circuitry. Measured signal amplitudes were in the range of 500–700 µV, while the input-referred noise of the readout was below 15 µVrms (100 Hz–4 kHz bandwidth). We report on the development and fabrication of this new cell-biological tool and present first results collected during the characterization and evaluation of the chip. The recordings of electrical potentials of neonatal rat cardiomyocytes after several days in vitro, which, on the one hand, were conventionally cultured (no pneumatic anchoring) and, on the other hand, were anchored and immobilized, will be detailed. Close http://iopscience.iop.org/article/10.1088/0960-1317/17/3/007/ doi:10.1088/0960-1317/17/3/007 Close
	Heer, Flavio; Hafizovic, Sadik; Franks, Wendy; Blau, Axel; Ziegler, Christiane; Hierlemann, Andreas CMOS microelectrode array for bidirectional interaction with neuronal networks Journal Article IEEE Journal of Solid-State Circuits, 41 (7), pp. 1620-1629, 2006, ISSN: 0018-9200. Abstract \| Links \| BibTeX @article{Heer2006, title = {CMOS microelectrode array for bidirectional interaction with neuronal networks}, author = {Flavio Heer and Sadik Hafizovic and Wendy Franks and Axel Blau and Christiane Ziegler and Andreas Hierlemann}, url = {http://ieeexplore.ieee.org/document/1644873/}, doi = {10.1109/JSSC.2006.873677}, issn = {0018-9200}, year = {2006}, date = {2006-07-07}, journal = {IEEE Journal of Solid-State Circuits}, volume = {41}, number = {7}, pages = {1620-1629}, abstract = {A CMOS metal-electrode-based micro system for bidirectional communication (stimulation and recording) with neuronal cells in vitro is presented. The chip overcomes the interconnect challenge that limits today's bidirectional microelectrode arrays. The microsystem has been fabricated in an industrial CMOS technology with several post-CMOS processing steps to realize 128 biocompatible electrodes and to ensure chip stability in physiological saline. The system comprises all necessary control circuitry and on-chip A/D and D/A conversion. A modular design has been implemented, where individual stimulation- and signal-conditioning circuitry units are associated with each electrode. Stimulation signals with a resolution of 8 bits can be sent to any subset of electrodes at a rate of 60 kHz, while all electrodes of the chip are continuously sampled at a rate of 20 kHz. The circuitry at each electrode can be individually reset to its operating point in order to suppress artifacts evoked by the stimulation pulses. Biological measurements from cultured neuronal networks originating from dissociated cortical tissue of fertilized chicken eggs with amplitudes of up to 500 muVpp are presented.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close A CMOS metal-electrode-based micro system for bidirectional communication (stimulation and recording) with neuronal cells in vitro is presented. The chip overcomes the interconnect challenge that limits today's bidirectional microelectrode arrays. The microsystem has been fabricated in an industrial CMOS technology with several post-CMOS processing steps to realize 128 biocompatible electrodes and to ensure chip stability in physiological saline. The system comprises all necessary control circuitry and on-chip A/D and D/A conversion. A modular design has been implemented, where individual stimulation- and signal-conditioning circuitry units are associated with each electrode. Stimulation signals with a resolution of 8 bits can be sent to any subset of electrodes at a rate of 60 kHz, while all electrodes of the chip are continuously sampled at a rate of 20 kHz. The circuitry at each electrode can be individually reset to its operating point in order to suppress artifacts evoked by the stimulation pulses. Biological measurements from cultured neuronal networks originating from dissociated cortical tissue of fertilized chicken eggs with amplitudes of up to 500 muVpp are presented. Close http://ieeexplore.ieee.org/document/1644873/ doi:10.1109/JSSC.2006.873677 Close

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