@article{Wang2022,
title = {P97/VCP ATPase inhibitors can rescue p97 mutation-linked motor neuron degeneration},
author = {F. Wang and S. Li and T. Y. Wang and G. A. Lopez and I. Antoshechkin and T.F. Chou},
url = {https://academic.oup.com/braincomms/article/4/4/fcac176/6632805},
doi = {https://doi.org/10.1093/braincomms/fcac176},
year = {2022},
date = {2022-07-06},
journal = {Brain Communications},
abstract = {Mutations in p97/VCP cause two motor neuron diseases: inclusion body myopathy associated with Paget disease of bone and frontotemporal dementia and familial amyotrophic lateral sclerosis. How p97 mutations lead to motor neuron degeneration is, however, unknown. Here we used patient-derived induced pluripotent stem cells to generate p97 mutant motor neurons. We reduced the genetic background variation by comparing mutant motor neurons to its isogenic wild type lines. Proteomic analysis reveals that p97R155H/+ motor neurons upregulate several cell cycle proteins at Day 14, but this effect diminishes by Day 20. Molecular changes linked to delayed cell cycle exit are observed in p97 mutant motor neurons. We also find that two p97 inhibitors, CB-5083 and NMS-873, restore some dysregulated protein levels. In addition, two p97 inhibitors and a food and drug administration-approved cyclin-dependent kinase 4/6 inhibitor, Abemaciclib, can rescue motor neuron death. Overall, we successfully used iPSC-derived motor neurons, identified dysregulated proteome and transcriptome and showed that p97 inhibitors rescue phenotypes in this disease model.},
keywords = {MaxTwo},
pubstate = {published},
tppubtype = {article}
}
Mutations in p97/VCP cause two motor neuron diseases: inclusion body myopathy associated with Paget disease of bone and frontotemporal dementia and familial amyotrophic lateral sclerosis. How p97 mutations lead to motor neuron degeneration is, however, unknown. Here we used patient-derived induced pluripotent stem cells to generate p97 mutant motor neurons. We reduced the genetic background variation by comparing mutant motor neurons to its isogenic wild type lines. Proteomic analysis reveals that p97R155H/+ motor neurons upregulate several cell cycle proteins at Day 14, but this effect diminishes by Day 20. Molecular changes linked to delayed cell cycle exit are observed in p97 mutant motor neurons. We also find that two p97 inhibitors, CB-5083 and NMS-873, restore some dysregulated protein levels. In addition, two p97 inhibitors and a food and drug administration-approved cyclin-dependent kinase 4/6 inhibitor, Abemaciclib, can rescue motor neuron death. Overall, we successfully used iPSC-derived motor neurons, identified dysregulated proteome and transcriptome and showed that p97 inhibitors rescue phenotypes in this disease model.
@article{Schroter2022,
title = {Functional imaging of brain organoids using high-density microelectrode arrays},
author = {Schröter, Manuel; Wang, Congwei; Terrigno, Marco; Hornauer, Philipp; Huang, Ziqiang; Jagasia, Ravi; Hierlemann, Andreas},
url = {https://link.springer.com/article/10.1557/s43577-022-00282-w},
year = {2022},
date = {2022-06-30},
journal = {MRS Bulletin},
abstract = {Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization.},
keywords = {HD-MEA, MaxOne, MaxTwo, Organoids},
pubstate = {published},
tppubtype = {article}
}
Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization.
@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 = {2D Neuronal Culture, CMOS, HD-MEA, IPSC, MaxOne},
pubstate = {published},
tppubtype = {article}
}
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.
@article{Sommer2022,
title = {Aging-Dependent Altered Transcriptional Programs Underlie Activity Impairments in Human C9orf72-Mutant Motor Neurons},
author = {Sommer, Daniel ; Rajkumar, Sandeep; Seidel, Mira; Aly, Amr; Ludolph, Albert; Ho, Ritchie; Boeckers, Tobias; Catanese, Alberto.},
url = {https://www.frontiersin.org/articles/10.3389/fnmol.2022.894230/full},
year = {2022},
date = {2022-06-14},
journal = {Frontiers in Molecular Neuroscience},
abstract = {Amyotrophic Lateral Sclerosis (ALS) is an incurable neurodegenerative disease characterized by dysfunction and loss of upper and lower motor neurons (MN). Despite several studies identifying drastic alterations affecting synaptic composition and functionality in different experimental models, the specific contribution of impaired activity to the neurodegenerative processes observed in ALS-related MN remains controversial. In particular, contrasting lines of evidence have shown both hyper- as well as hypoexcitability as driving pathomechanisms characterizing this specific neuronal population. In this study, we combined high definition multielectrode array (HD-MEA) techniques with transcriptomic analysis to longitudinally monitor and untangle the activity-dependent alterations arising in human C9orf72-mutant MN. We found a time-dependent reduction of neuronal activity in ALSC9orf72 cultures occurring as synaptic contacts undergo maturation and matched by a significant loss of mutant MN upon aging. Notably, ALS-related neurons displayed reduced network synchronicity most pronounced at later stages of culture, suggesting synaptic imbalance. In concordance with the HD-MEA data, transcriptomic analysis revealed an early up-regulation of synaptic terms in ALSC9orf72 MN, whose expression was decreased in aged cultures. In addition, treatment of older mutant cells with Apamin, a K+ channel blocker previously shown to be neuroprotective in ALS, rescued the time-dependent loss of firing properties observed in ALSC9orf72 MN as well as the expression of maturity-related synaptic genes. All in all, this study broadens the understanding of how impaired synaptic activity contributes to MN degeneration in ALS by correlating electrophysiological alterations to aging-dependent transcriptional programs.
},
keywords = {HD-MEA, MaxOne, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Amyotrophic Lateral Sclerosis (ALS) is an incurable neurodegenerative disease characterized by dysfunction and loss of upper and lower motor neurons (MN). Despite several studies identifying drastic alterations affecting synaptic composition and functionality in different experimental models, the specific contribution of impaired activity to the neurodegenerative processes observed in ALS-related MN remains controversial. In particular, contrasting lines of evidence have shown both hyper- as well as hypoexcitability as driving pathomechanisms characterizing this specific neuronal population. In this study, we combined high definition multielectrode array (HD-MEA) techniques with transcriptomic analysis to longitudinally monitor and untangle the activity-dependent alterations arising in human C9orf72-mutant MN. We found a time-dependent reduction of neuronal activity in ALSC9orf72 cultures occurring as synaptic contacts undergo maturation and matched by a significant loss of mutant MN upon aging. Notably, ALS-related neurons displayed reduced network synchronicity most pronounced at later stages of culture, suggesting synaptic imbalance. In concordance with the HD-MEA data, transcriptomic analysis revealed an early up-regulation of synaptic terms in ALSC9orf72 MN, whose expression was decreased in aged cultures. In addition, treatment of older mutant cells with Apamin, a K+ channel blocker previously shown to be neuroprotective in ALS, rescued the time-dependent loss of firing properties observed in ALSC9orf72 MN as well as the expression of maturity-related synaptic genes. All in all, this study broadens the understanding of how impaired synaptic activity contributes to MN degeneration in ALS by correlating electrophysiological alterations to aging-dependent transcriptional programs.
@article{Cheng2023,
title = {Automated detection of extracellular action potentials from single neurons},
author = {Zhuowei Cheng and Elmer Guzman and Tjitse van der Molen and Tal Sharf and Paul K. Hansma and Kenneth S Kosik and Linda Petzold and Kenneth R Tovar},
url = {https://www.biorxiv.org/content/10.1101/2022.06.06.494896v1.abstract},
doi = {https://doi.org/10.1101/2022.06.06.494896},
year = {2022},
date = {2022-06-06},
journal = {bioRxiv},
abstract = {Multi-electrode arrays (MEAs) non-invasively record extracellular action potentials (eAPs, also known as spikes) from hundreds of neurons simultaneously. However, because extracellular electrodes sample from the local electrical field, each electrode can detect eAPs from multiple nearby neurons. Interpreting spike trains at individual electrodes of high-density arrays requires spike sorting, a computational process which groups eAPs from single ’units’ based on assumptions of how spike waveforms correlate with different neuronal sources. Additionally, when experimental conditions result in changes to eAP waveforms, spike sorting routines may have difficulty correlating eAPs from multiple neurons at single electrodes before and after such waveform changes. We present here a novel, empirical method for unambiguously isolating eAPs from individual, uniquely identifiable neurons, based on automated multi- point detection of action potential propagation. This method is insensitive to changes in eAP waveform morphology because it makes no assumptions about the relationship between spike waveform and neuronal source. Our algorithm for automated detection of action potential propagation produces a ’fingerprint’ that uniquely identifies those spikes from each neuron. By unambiguously isolating eAPs from multiple neurons in each recording, on a range of platforms and experimental preparations, our method now enables high-content screening with contemporary MEAs. We outline the limitations and strengths of propagation-based isolation of eAPs from single neurons and propose how our automated method complements spike sorting and could be adapted to in vivo use.},
keywords = {Action Potential, HD-MEA, MaxOne},
pubstate = {published},
tppubtype = {article}
}
Multi-electrode arrays (MEAs) non-invasively record extracellular action potentials (eAPs, also known as spikes) from hundreds of neurons simultaneously. However, because extracellular electrodes sample from the local electrical field, each electrode can detect eAPs from multiple nearby neurons. Interpreting spike trains at individual electrodes of high-density arrays requires spike sorting, a computational process which groups eAPs from single ’units’ based on assumptions of how spike waveforms correlate with different neuronal sources. Additionally, when experimental conditions result in changes to eAP waveforms, spike sorting routines may have difficulty correlating eAPs from multiple neurons at single electrodes before and after such waveform changes. We present here a novel, empirical method for unambiguously isolating eAPs from individual, uniquely identifiable neurons, based on automated multi- point detection of action potential propagation. This method is insensitive to changes in eAP waveform morphology because it makes no assumptions about the relationship between spike waveform and neuronal source. Our algorithm for automated detection of action potential propagation produces a ’fingerprint’ that uniquely identifies those spikes from each neuron. By unambiguously isolating eAPs from multiple neurons in each recording, on a range of platforms and experimental preparations, our method now enables high-content screening with contemporary MEAs. We outline the limitations and strengths of propagation-based isolation of eAPs from single neurons and propose how our automated method complements spike sorting and could be adapted to in vivo use.
Noh Seungmin ; Jeon, Sungwoong; Kim Eunhee; Oh Untaek; Park Danbi; Park Sun Hwa; Kim Sung Won; Pané Salvador; Nelson Bradley; Kim Jin-young; Choi Hongsoo;
@article{Noh2022,
title = {A Biodegradable Magnetic Microrobot Based on Gelatin Methacrylate for Precise Delivery of Stem Cells with Mass Production Capability},
author = {Noh, Seungmin ; Jeon, Sungwoong; Kim, Eunhee; Oh, Untaek; Park, Danbi; Park, Sun Hwa; Kim, Sung Won; Pané, Salvador; Nelson, Bradley; Kim, Jin-young; Choi, Hongsoo;},
url = {https://onlinelibrary.wiley.com/doi/10.1002/smll.202107888},
doi = {10.1002/smll.202107888},
year = {2022},
date = {2022-05-23},
journal = {Small},
abstract = {A great deal of research has focused on small-scale robots for biomedical applications and minimally invasive delivery of therapeutics (e.g., cells, drugs, and genes) to a target area. Conventional fabrication methods, such as two-photon polymerization, can be used to build sophisticated micro- and nanorobots, but the long fabrication cycle for a single microrobot has limited its practical use. This study proposes a biodegradable spherical gelatin methacrylate (GelMA) microrobot for mass production in a microfluidic channel. The proposed microrobot is fabricated in a flow-focusing droplet generator by shearing a mixture of GelMA, photoinitiator, and superparamagnetic iron oxide nanoparticles (SPIONs) with a mixture of oil and surfactant. Human nasal turbinate stem cells (hNTSCs) are loaded on the GelMA microrobot, and the hNTSC-loaded microrobot shows precise rolling motion in response to an external rotating magnetic field. The microrobot is enzymatically degraded by collagenase, and released hNTSCs are proliferated and differentiated into neuronal cells. In addition, the feasibility of the GelMA microrobot as a cell therapeutic delivery system is investigated by measuring electrophysiological activity on a multielectrode array. Such a versatile and fully biodegradable microrobot has the potential for targeted stem cell delivery, proliferation, and differentiation for stem cell-based therapy.},
keywords = {MaxOne},
pubstate = {published},
tppubtype = {article}
}
A great deal of research has focused on small-scale robots for biomedical applications and minimally invasive delivery of therapeutics (e.g., cells, drugs, and genes) to a target area. Conventional fabrication methods, such as two-photon polymerization, can be used to build sophisticated micro- and nanorobots, but the long fabrication cycle for a single microrobot has limited its practical use. This study proposes a biodegradable spherical gelatin methacrylate (GelMA) microrobot for mass production in a microfluidic channel. The proposed microrobot is fabricated in a flow-focusing droplet generator by shearing a mixture of GelMA, photoinitiator, and superparamagnetic iron oxide nanoparticles (SPIONs) with a mixture of oil and surfactant. Human nasal turbinate stem cells (hNTSCs) are loaded on the GelMA microrobot, and the hNTSC-loaded microrobot shows precise rolling motion in response to an external rotating magnetic field. The microrobot is enzymatically degraded by collagenase, and released hNTSCs are proliferated and differentiated into neuronal cells. In addition, the feasibility of the GelMA microrobot as a cell therapeutic delivery system is investigated by measuring electrophysiological activity on a multielectrode array. Such a versatile and fully biodegradable microrobot has the potential for targeted stem cell delivery, proliferation, and differentiation for stem cell-based therapy.
@article{Sato2022,
title = {Microfluidic cell engineering on high-density microelectrode arrays for assessing structure-function relationships in living neuronal networks},
author = {Sato, Yuya; Yamamoto, Hideaki; Kato, Hideyuki; Tanii, Takashi; Sato, Shigeo; Hirano-Iwata, Ayumi},
url = {https://arxiv.org/abs/2205.04342},
year = {2022},
date = {2022-05-11},
abstract = {Neuronal networks in dissociated culture combined with cell engineering technology offer a pivotal platform to constructively explore the relationship between structure and function in living neuronal networks. Here, we fabricated defined neuronal networks possessing a modular architecture on high-density microelectrode arrays (HD-MEAs), a state-of-the-art electrophysiological tool for recording neural activity with high spatial and temporal resolutions. We first established a surface coating protocol using a cell-permissive hydrogel to stably attach polydimethylsiloxane microfluidic film on the HD-MEA. We then recorded the spontaneous neural activity of the engineered neuronal network, which revealed an important portrait of the engineered neuronal network--modular architecture enhances functional complexity by reducing the excessive neural correlation between spatially segregated modules. The results of this study highlight the impact of HD-MEA recordings combined with cell engineering technologies as a novel tool in neuroscience to constructively assess the structure-function relationships in neuronal networks.},
keywords = {HD-MEA, MaxOne, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Neuronal networks in dissociated culture combined with cell engineering technology offer a pivotal platform to constructively explore the relationship between structure and function in living neuronal networks. Here, we fabricated defined neuronal networks possessing a modular architecture on high-density microelectrode arrays (HD-MEAs), a state-of-the-art electrophysiological tool for recording neural activity with high spatial and temporal resolutions. We first established a surface coating protocol using a cell-permissive hydrogel to stably attach polydimethylsiloxane microfluidic film on the HD-MEA. We then recorded the spontaneous neural activity of the engineered neuronal network, which revealed an important portrait of the engineered neuronal network--modular architecture enhances functional complexity by reducing the excessive neural correlation between spatially segregated modules. The results of this study highlight the impact of HD-MEA recordings combined with cell engineering technologies as a novel tool in neuroscience to constructively assess the structure-function relationships in neuronal networks.
@article{Shimba2022,
title = {Recording Saltatory Conduction Along Sensory Axons Using a High-Density Microelectrode Array},
author = {Shimba, Kenta; Asahina, Takahiro; Sakai, Koji; Kotani, Kiyoshi; Jimbo, Yasuhiko},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2022.854637/full},
year = {2022},
date = {2022-04-18},
journal = {Frontiers in Neuroscience},
abstract = {In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network topology can be controlled by culturing neurons within polydimethylsiloxane (PDMS) microstructures that are combined with microelectrode arrays (MEAs) for electric access to the network. However, currently used glass MEAs are limited to 256 electrodes and pose a limitation to the spatial resolution as well as the design of more complex microstructures. The use of high density complementary metal-oxide-semiconductor (CMOS) MEAs greatly increases the spatial resolution, enabling sub-cellular readout and stimulation of neurons in defined neural networks. Unfortunately, the non-planar surface of CMOS MEAs complicates the attachment of PDMS microstructures. To overcome the problem of axons escaping the microstructures through the ridges of the CMOS MEA, we stamp-transferred a thin film of hexane-diluted PDMS onto the array such that the PDMS filled the ridges at the contact surface of the microstructures without clogging the axon guidance channels. This method resulted in 23 % of structurally fully connected but sealed networks on the CMOS MEA of which about 45 % showed spiking activity in all channels. Moreover, we provide an impedance-based method to visualize the exact location of the microstructures on the MEA and show that our method can confine axonal growth within the PDMS microstructures. Finally, the high spatial resolution of the CMOS MEA enabled us to show that action potentials follow the unidirectional topology of our circular multi-node microstructure.},
keywords = {HD-MEA, MaxOne, Neuronal cell culture},
pubstate = {published},
tppubtype = {article}
}
In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network topology can be controlled by culturing neurons within polydimethylsiloxane (PDMS) microstructures that are combined with microelectrode arrays (MEAs) for electric access to the network. However, currently used glass MEAs are limited to 256 electrodes and pose a limitation to the spatial resolution as well as the design of more complex microstructures. The use of high density complementary metal-oxide-semiconductor (CMOS) MEAs greatly increases the spatial resolution, enabling sub-cellular readout and stimulation of neurons in defined neural networks. Unfortunately, the non-planar surface of CMOS MEAs complicates the attachment of PDMS microstructures. To overcome the problem of axons escaping the microstructures through the ridges of the CMOS MEA, we stamp-transferred a thin film of hexane-diluted PDMS onto the array such that the PDMS filled the ridges at the contact surface of the microstructures without clogging the axon guidance channels. This method resulted in 23 % of structurally fully connected but sealed networks on the CMOS MEA of which about 45 % showed spiking activity in all channels. Moreover, we provide an impedance-based method to visualize the exact location of the microstructures on the MEA and show that our method can confine axonal growth within the PDMS microstructures. Finally, the high spatial resolution of the CMOS MEA enabled us to show that action potentials follow the unidirectional topology of our circular multi-node microstructure.
@article{Hornauer2022,
title = {Downregulating α-synuclein in iPSC-derived dopaminergic neurons mimics 2 electrophysiological phenotype of the A53T mutation},
author = {Hornauer, Philipp; Prack, Gustavo; Anastasi, Nadia; Ronchi, Silvia; Kim, Taehoon; Donner, Christian; Fiscella, Michele; Borgwardt, Karsten; Taylor, Verdon; Jagasia, Ravi; Roqueiro, Damian; Hierlemann, Andreas;},
url = {https://www.biorxiv.org/content/10.1101/2022.03.31.486582v1.full},
year = {2022},
date = {2022-04-01},
journal = {bioRxiv},
abstract = {Parkinson’s disease (PD) is a common debilitating neurodegenerative disorder, characterized by a progressive loss of dopaminergic (DA) neurons. Mutations, gene dosage increase, and single nucleotide polymorphisms in the α-synuclein-encoding gene SNCA either cause or increase the risk for PD. However, neither the function of α-synuclein in health and disease, nor its role throughout development is fully understood. Here, we introduce DeePhys, a new tool that allows for data-driven functional phenotyping of neuronal cell lines by combining electrophysiological features inferred from high-density microelectrode array (HD-MEA) recordings with a robust machine learning workflow. We apply DeePhys to human induced pluripotent stem cell (iPSC)-derived DA neuron-astrocyte co-cultures harboring the prominent SNCA mutation A53T and an isogenic control line. Moreover, we demonstrate how DeePhys can facilitate the assessment of cellular and network-level electrophysiological features to build functional phenotypes and to evaluate potential treatment interventions. We find that electrophysiological features across all scales proved to be highly specific for the A53T phenotype, enabled to predict the genotype and age of individual cultures with high accuracy, and revealed a mutant-like phenotype after downregulation of α-synuclein.},
keywords = {HD-MEA, MaxOne, Neuronal cell culture},
pubstate = {published},
tppubtype = {article}
}
Parkinson’s disease (PD) is a common debilitating neurodegenerative disorder, characterized by a progressive loss of dopaminergic (DA) neurons. Mutations, gene dosage increase, and single nucleotide polymorphisms in the α-synuclein-encoding gene SNCA either cause or increase the risk for PD. However, neither the function of α-synuclein in health and disease, nor its role throughout development is fully understood. Here, we introduce DeePhys, a new tool that allows for data-driven functional phenotyping of neuronal cell lines by combining electrophysiological features inferred from high-density microelectrode array (HD-MEA) recordings with a robust machine learning workflow. We apply DeePhys to human induced pluripotent stem cell (iPSC)-derived DA neuron-astrocyte co-cultures harboring the prominent SNCA mutation A53T and an isogenic control line. Moreover, we demonstrate how DeePhys can facilitate the assessment of cellular and network-level electrophysiological features to build functional phenotypes and to evaluate potential treatment interventions. We find that electrophysiological features across all scales proved to be highly specific for the A53T phenotype, enabled to predict the genotype and age of individual cultures with high accuracy, and revealed a mutant-like phenotype after downregulation of α-synuclein.
@article{Sawada2022,
title = {Design strategies for controlling neuron-connected robots using reinforcement learning},
author = {Haruto Sawada and Naoki Wake and Kazuhiro Sasabuchi and Jun Takamatsu and Hirokazu Takahashi and Katsushi Ikeuchi},
url = {https://arxiv.org/abs/2203.15290},
doi = {https://doi.org/10.48550/arXiv.2203.15290},
year = {2022},
date = {2022-03-29},
journal = {arXiv},
abstract = {Despite the growing interest in robot control utilizing the computation of biological neurons, context-dependent behavior by neuron-connected robots remains a challenge. Context-dependent behavior here is defined as behavior that is not the result of a simple sensory-motor coupling, but rather based on an understanding of the task goal. This paper proposes design principles for training neuron-connected robots based on task goals to achieve context-dependent behavior. First, we employ deep reinforcement learning (RL) to enable training that accounts for goal achievements. Second, we propose a neuron simulator as a probability distribution based on recorded neural data, aiming to represent physiologically valid neural dynamics while avoiding complex modeling with high computational costs. Furthermore, we propose to update the simulators during the training to bridge the gap between the simulation and the real settings. The experiments showed that the robot gradually learned context-dependent behaviors in pole balancing and robot navigation tasks. Moreover, the learned policies were valid for neural simulators based on novel neural data, and the task performance increased by updating the simulators during training. These results suggest the effectiveness of the proposed design principle for the context-dependent behavior of neuron-connected robots.},
keywords = {Machine Learning, MaxOne, Stimulation},
pubstate = {published},
tppubtype = {article}
}
Despite the growing interest in robot control utilizing the computation of biological neurons, context-dependent behavior by neuron-connected robots remains a challenge. Context-dependent behavior here is defined as behavior that is not the result of a simple sensory-motor coupling, but rather based on an understanding of the task goal. This paper proposes design principles for training neuron-connected robots based on task goals to achieve context-dependent behavior. First, we employ deep reinforcement learning (RL) to enable training that accounts for goal achievements. Second, we propose a neuron simulator as a probability distribution based on recorded neural data, aiming to represent physiologically valid neural dynamics while avoiding complex modeling with high computational costs. Furthermore, we propose to update the simulators during the training to bridge the gap between the simulation and the real settings. The experiments showed that the robot gradually learned context-dependent behaviors in pole balancing and robot navigation tasks. Moreover, the learned policies were valid for neural simulators based on novel neural data, and the task performance increased by updating the simulators during training. These results suggest the effectiveness of the proposed design principle for the context-dependent behavior of neuron-connected robots.
@article{Duru2022,
title = {Engineered Biological Neural Networks on High Density CMOS Microelectrode Arrays},
author = {Duru, Jens; Küchler, Joël; Ihle, Stephan J.;, Forró, Csaba; Bernardi, Aeneas; Girardin, Sophie; Hengsteler, Julian; Wheeler, Stephen; Vörös, János; Ruff, Tobias;},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2022.829884/full},
year = {2022},
date = {2022-02-21},
abstract = {In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network topology can be controlled by culturing neurons within polydimethylsiloxane (PDMS) microstructures that are combined with microelectrode arrays (MEAs) for electric access to the network. However, currently used glass MEAs are limited to 256 electrodes and pose a limitation to the spatial resolution as well as the design of more complex microstructures. The use of high density complementary metal-oxide-semiconductor (CMOS) MEAs greatly increases the spatial resolution, enabling sub-cellular readout and stimulation of neurons in defined neural networks. Unfortunately, the non-planar surface of CMOS MEAs complicates the attachment of PDMS microstructures. To overcome the problem of axons escaping the microstructures through the ridges of the CMOS MEA, we stamp-transferred a thin film of hexane-diluted PDMS onto the array such that the PDMS filled the ridges at the contact surface of the microstructures without clogging the axon guidance channels. This method resulted in 23 % of structurally fully connected but sealed networks on the CMOS MEA of which about 45 % showed spiking activity in all channels. Moreover, we provide an impedance-based method to visualize the exact location of the microstructures on the MEA and show that our method can confine axonal growth within the PDMS microstructures. Finally, the high spatial resolution of the CMOS MEA enabled us to show that action potentials follow the unidirectional topology of our circular multi-node microstructure.},
keywords = {HD-MEA, MaxOne, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network topology can be controlled by culturing neurons within polydimethylsiloxane (PDMS) microstructures that are combined with microelectrode arrays (MEAs) for electric access to the network. However, currently used glass MEAs are limited to 256 electrodes and pose a limitation to the spatial resolution as well as the design of more complex microstructures. The use of high density complementary metal-oxide-semiconductor (CMOS) MEAs greatly increases the spatial resolution, enabling sub-cellular readout and stimulation of neurons in defined neural networks. Unfortunately, the non-planar surface of CMOS MEAs complicates the attachment of PDMS microstructures. To overcome the problem of axons escaping the microstructures through the ridges of the CMOS MEA, we stamp-transferred a thin film of hexane-diluted PDMS onto the array such that the PDMS filled the ridges at the contact surface of the microstructures without clogging the axon guidance channels. This method resulted in 23 % of structurally fully connected but sealed networks on the CMOS MEA of which about 45 % showed spiking activity in all channels. Moreover, we provide an impedance-based method to visualize the exact location of the microstructures on the MEA and show that our method can confine axonal growth within the PDMS microstructures. Finally, the high spatial resolution of the CMOS MEA enabled us to show that action potentials follow the unidirectional topology of our circular multi-node microstructure.
@article{Xue2022,
title = {Inferring monosynaptic connections from paired dendritic spine Ca2+ imaging and large-scale recording of extracellular spiking},
author = {Xue, Xiaohan and Buccino, Alessio Paolo and Kumar, Sreedhar Saseendran and Hierlemann, Andreas and Bartram, Julian},
doi = {10.1101/2022.02.16.480643},
year = {2022},
date = {2022-02-16},
journal = {bioRxiv},
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 = {ETH-CMOS-MEA, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
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.
@article{McSweeney2022,
title = {Loss of Neurodevelopmental Gene CASK Disrupts Neural Connectivity in Human Cortical Excitatory Neurons},
author = {Danny McSweeney and Rafael Gabriel and Kang Jin and Zhiping P. Pang and Bruce Aronow and ChangHui Pak},
url = {https://doi.org/10.1101/2022.02.14.480404},
doi = {10.1101/2022.02.14.480404},
year = {2022},
date = {2022-02-15},
journal = {BioRxiv},
abstract = {Loss-of-function (LOF) mutations in CASK cause severe developmental phenotypes, including microcephaly with pontine and cerebellar hypoplasia, X-linked intellectual disability, and autism. Unraveling the pathogenesis of CASK-related disorders has been challenging due to limited human cellular models to study the dynamic roles of this molecule during neuronal and synapse development. Here, we generated CASK knockout (KO) isogenic cell lines from human embryonic stem cells (hESCs) using CRISPR/Cas9 and examined gene expression, morphometrics and synaptic function of induced neuronal cells during development. While young (immature) CASK KO neurons show robust neuronal outgrowth, mature CASK KO neurons displayed severe defects in synaptic transmission and synchronized burst activity without compromising neuronal morphology and synapse numbers. In developing human cortical 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 relevant to human patients.},
keywords = {IPSC, MaxOne, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Loss-of-function (LOF) mutations in CASK cause severe developmental phenotypes, including microcephaly with pontine and cerebellar hypoplasia, X-linked intellectual disability, and autism. Unraveling the pathogenesis of CASK-related disorders has been challenging due to limited human cellular models to study the dynamic roles of this molecule during neuronal and synapse development. Here, we generated CASK knockout (KO) isogenic cell lines from human embryonic stem cells (hESCs) using CRISPR/Cas9 and examined gene expression, morphometrics and synaptic function of induced neuronal cells during development. While young (immature) CASK KO neurons show robust neuronal outgrowth, mature CASK KO neurons displayed severe defects in synaptic transmission and synchronized burst activity without compromising neuronal morphology and synapse numbers. In developing human cortical 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 relevant to human patients.
@article{Paulsen2022,
title = {Autism genes converge on asynchronous development of shared neuron classes},
author = {Bruna Paulsen and Silvia Velasco and Amanda J. Kedaigle and Martina Pigoni and Giorgia Quadrato and Anthony J. Deo and Xian Adiconis and Ana Uzquiano and Rafaela Sartore and Sung Min Yang and Sean K. Simmons and Panagiotis Symvoulidis and Kwanho Kim and Kalliopi Tsafou and Archana Podury and Catherine Abbate and Ashley Tucewicz and Samantha N. Smith and Alexandre Albanese and Lindy Barrett and Neville E. Sanjana and Xi Shi and Kwanghun Chung and Kasper Lage and Edward S. Boyden and Aviv Regev andJoshua Z. Levin and Paola Arlotta },
url = {https://www.nature.com/articles/s41586-021-04358-6},
doi = {10.1038/s41586-021-04358-6},
year = {2022},
date = {2022-02-02},
journal = {Nature},
volume = {602},
pages = {268–273},
abstract = {Genetic risk for autism spectrum disorder (ASD) is associated with hundreds of genes spanning a wide range of biological functions1,2,3,4,5,6. The alterations in the human brain resulting from mutations in these genes remain unclear. Furthermore, their phenotypic manifestation varies across individuals7,8. Here we used organoid models of the human cerebral cortex to identify cell-type-specific developmental abnormalities that result from haploinsufficiency in three ASD risk genes—SUV420H1 (also known as KMT5B), ARID1B and CHD8—in multiple cell lines from different donors, using single-cell RNA-sequencing (scRNA-seq) analysis of more than 745,000 cells and proteomic analysis of individual organoids, to identify phenotypic convergence. Each of the three mutations confers asynchronous development of two main cortical neuronal lineages—γ-aminobutyric-acid-releasing (GABAergic) neurons and deep-layer excitatory projection neurons—but acts through largely distinct molecular pathways. Although these phenotypes are consistent across cell lines, their expressivity is influenced by the individual genomic context, in a manner that is dependent on both the risk gene and the developmental defect. Calcium imaging in intact organoids shows that these early-stage developmental changes are followed by abnormal circuit activity. This research uncovers cell-type-specific neurodevelopmental abnormalities that are shared across ASD risk genes and are finely modulated by human genomic context, finding convergence in the neurobiological basis of how different risk genes contribute to ASD pathology.},
keywords = {HD-MEA, MaxOne, Organoids},
pubstate = {published},
tppubtype = {article}
}
Genetic risk for autism spectrum disorder (ASD) is associated with hundreds of genes spanning a wide range of biological functions1,2,3,4,5,6. The alterations in the human brain resulting from mutations in these genes remain unclear. Furthermore, their phenotypic manifestation varies across individuals7,8. Here we used organoid models of the human cerebral cortex to identify cell-type-specific developmental abnormalities that result from haploinsufficiency in three ASD risk genes—SUV420H1 (also known as KMT5B), ARID1B and CHD8—in multiple cell lines from different donors, using single-cell RNA-sequencing (scRNA-seq) analysis of more than 745,000 cells and proteomic analysis of individual organoids, to identify phenotypic convergence. Each of the three mutations confers asynchronous development of two main cortical neuronal lineages—γ-aminobutyric-acid-releasing (GABAergic) neurons and deep-layer excitatory projection neurons—but acts through largely distinct molecular pathways. Although these phenotypes are consistent across cell lines, their expressivity is influenced by the individual genomic context, in a manner that is dependent on both the risk gene and the developmental defect. Calcium imaging in intact organoids shows that these early-stage developmental changes are followed by abnormal circuit activity. This research uncovers cell-type-specific neurodevelopmental abnormalities that are shared across ASD risk genes and are finely modulated by human genomic context, finding convergence in the neurobiological basis of how different risk genes contribute to ASD pathology.
@article{Hruska-Plochan2021,
title = {Human neural networks with sparse TDP-43 pathology reveal NPTX2 misregulation in ALS/FTLD},
author = {Marian Hruska-Plochan and Katharina M. Betz and Silvia Ronchi and Vera I. Wiersma and Zuzanna Maniecka and Eva-Maria Hock and Florent Laferriere and Sonu Sahadevan and Vanessa Hoop and Igor Delvendahl and Martina Panatta and Alexander van der Bourg and Dasa Bohaciakova and Karl Frontzek and Adriano Aguzzi and Tammaryn Lashley and Mark D. Robinson and Theofanis Karayannis and Martin Mueller and Andreas Hierlemann and Magdalini Polymenidou},
url = {https://doi.org/10.1101/2021.12.08.471089},
doi = {10.1101/2021.12.08.471089},
year = {2021},
date = {2021-12-09},
journal = {BioRxiv},
abstract = {Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating these age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1,2, which involve human-specific mechanisms3–6 that cannot be directly studied in animal models. To explore the emergence and consequences of TDP-43 pathologies, we generated iPSC-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors7. Single-cell transcriptomics (scRNA-seq) and comparison to independent NSCs8, showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks. Neuronal and glial maturation in iCoMoNSC-derived cultures was similar to that of cortical organoids9. Overexpression of wild-type TDP-43 in a minority of iCoMoNSC-derived neurons led to progressive fragmentation and aggregation, resulting in loss of function and neurotoxicity. scRNA-seq revealed a novel set of misregulated RNA targets coinciding in both TDP-43 overexpressing neurons and patient brains exhibiting loss of nuclear TDP-43. The strongest misregulated target encoded for the synaptic protein NPTX2, which was consistently misaccumulated in ALS and FTLD patient neurons with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby highlighting a new pathway of neurotoxicity.},
keywords = {Inhibitory Neurons, MEA Technology, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating these age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1,2, which involve human-specific mechanisms3–6 that cannot be directly studied in animal models. To explore the emergence and consequences of TDP-43 pathologies, we generated iPSC-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors7. Single-cell transcriptomics (scRNA-seq) and comparison to independent NSCs8, showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks. Neuronal and glial maturation in iCoMoNSC-derived cultures was similar to that of cortical organoids9. Overexpression of wild-type TDP-43 in a minority of iCoMoNSC-derived neurons led to progressive fragmentation and aggregation, resulting in loss of function and neurotoxicity. scRNA-seq revealed a novel set of misregulated RNA targets coinciding in both TDP-43 overexpressing neurons and patient brains exhibiting loss of nuclear TDP-43. The strongest misregulated target encoded for the synaptic protein NPTX2, which was consistently misaccumulated in ALS and FTLD patient neurons with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby highlighting a new pathway of neurotoxicity.
@article{Kagan2021,
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/10.1101/2021.12.02.471005v1 },
doi = {10.1101/2021.12.02.471005},
year = {2021},
date = {2021-12-03},
journal = {BioRxiv},
abstract = {Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arrays (26,400 electrodes) and shank electrodes (960 electrodes), we probed broadband and three-dimensional extracellular field recordings generated by spontaneous activity of human brain organoids. These recordings simultaneously captured local field potentials (LFPs) and single-unit activity extracted through spike sorting. From spiking activity, we estimated a directed functional connectivity graph of synchronous neural network activity, which showed a large number of weak functional connections enmeshed within a network skeleton of significantly fewer strong connections. Treatment of the organoid with a benzodiazepine induced a reproducible signature response that shortened the inter-burst intervals, increased the uniformity of the firing pattern within each burst and decreased the population of weakly connected edges. Simultaneously examining the spontaneous LFPs and their phase alignment to spiking showed that spike bursts were coherent with theta oscillations in the LFPs. Our results demonstrate that human brain organoids have self-organized neuronal assemblies of sufficient size, cellular orientation, and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug mechanisms, and the effects of external stimuli upon neuronal networks.},
keywords = {ETH-CMOS-MEA, In-Vitro, MaxOne},
pubstate = {published},
tppubtype = {article}
}
Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arrays (26,400 electrodes) and shank electrodes (960 electrodes), we probed broadband and three-dimensional extracellular field recordings generated by spontaneous activity of human brain organoids. These recordings simultaneously captured local field potentials (LFPs) and single-unit activity extracted through spike sorting. From spiking activity, we estimated a directed functional connectivity graph of synchronous neural network activity, which showed a large number of weak functional connections enmeshed within a network skeleton of significantly fewer strong connections. Treatment of the organoid with a benzodiazepine induced a reproducible signature response that shortened the inter-burst intervals, increased the uniformity of the firing pattern within each burst and decreased the population of weakly connected edges. Simultaneously examining the spontaneous LFPs and their phase alignment to spiking showed that spike bursts were coherent with theta oscillations in the LFPs. Our results demonstrate that human brain organoids have self-organized neuronal assemblies of sufficient size, cellular orientation, and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug mechanisms, and the effects of external stimuli upon neuronal networks.
@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 = {2D Neuronal Culture, HD-MEA, MaxOne, Primary Neuronal Cell Culture, Stimulation},
pubstate = {published},
tppubtype = {article}
}
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.
@article{Schenke2021,
title = {Human-Relevant Sensitivity of iPSC-Derived Human Motor Neurons to BoNT/A1 and B1},
author = {Maren Schenke and Hélène-Christine Prause and Wiebke Bergforth and Adina Przykopanski},
url = {https://www.mdpi.com/2072-6651/13/8/585},
doi = {https://doi.org/10.3390/toxins13080585},
year = {2021},
date = {2021-08-22},
journal = {toxins},
abstract = {The application of botulinum neurotoxins (BoNTs) for medical treatments necessitates a potency quantification of these lethal bacterial toxins, resulting in the use of a large number of test animals. Available alternative methods are limited in their relevance, as they are based on rodent cells or neuroblastoma cell lines or applicable for single toxin serotypes only. Here, human motor neurons (MNs), which are the physiological target of BoNTs, were generated from induced pluripotent stem cells (iPSCs) and compared to the neuroblastoma cell line SiMa, which is often used in cell-based assays for BoNT potency determination. In comparison with the mouse bioassay, human MNs exhibit a superior sensitivity to the BoNT serotypes A1 and B1 at levels that are reflective of human sensitivity. SiMa cells were able to detect BoNT/A1, but with much lower sensitivity than human MNs and appear unsuitable to detect any BoNT/B1 activity. The MNs used for these experiments were generated according to three differentiation protocols, which resulted in distinct sensitivity levels. Molecular parameters such as receptor protein concentration and electrical activity of the MNs were analyzed, but are not predictive for BoNT sensitivity. These results show that human MNs from several sources should be considered in BoNT testing and that human MNs are a physiologically relevant model, which could be used to optimize current BoNT potency testing.},
keywords = {MaxOne},
pubstate = {published},
tppubtype = {article}
}
The application of botulinum neurotoxins (BoNTs) for medical treatments necessitates a potency quantification of these lethal bacterial toxins, resulting in the use of a large number of test animals. Available alternative methods are limited in their relevance, as they are based on rodent cells or neuroblastoma cell lines or applicable for single toxin serotypes only. Here, human motor neurons (MNs), which are the physiological target of BoNTs, were generated from induced pluripotent stem cells (iPSCs) and compared to the neuroblastoma cell line SiMa, which is often used in cell-based assays for BoNT potency determination. In comparison with the mouse bioassay, human MNs exhibit a superior sensitivity to the BoNT serotypes A1 and B1 at levels that are reflective of human sensitivity. SiMa cells were able to detect BoNT/A1, but with much lower sensitivity than human MNs and appear unsuitable to detect any BoNT/B1 activity. The MNs used for these experiments were generated according to three differentiation protocols, which resulted in distinct sensitivity levels. Molecular parameters such as receptor protein concentration and electrical activity of the MNs were analyzed, but are not predictive for BoNT sensitivity. These results show that human MNs from several sources should be considered in BoNT testing and that human MNs are a physiologically relevant model, which could be used to optimize current BoNT potency testing.
Sundberg, Maria; Pinson, Hannah; Smith, Richard S; Winden, Kellen D; Venugopal, Pooja; Tai, Derek J C; Gusella, James F; Talkowski, Michael E; Walsh, Christopher A; Tegmark, Max; Sahin, Mustafa
@article{Sundberg2021,
title = {16p11.2 deletion is associated with hyperactivation of human iPSC-derived dopaminergic neuron networks and is rescued by RHOA inhibition in vitro},
author = {Maria Sundberg and Hannah Pinson and Richard S. Smith and Kellen D. Winden and Pooja Venugopal and Derek J. C. Tai and James F. Gusella and Michael E. Talkowski and Christopher A. Walsh and Max Tegmark and Mustafa Sahin },
url = {https://www.nature.com/articles/s41467-021-23113-z},
doi = {10.1038/s41467-021-23113-z},
year = {2021},
date = {2021-05-18},
journal = {Nature Communications},
volume = {12},
number = {2897 },
abstract = {Reciprocal copy number variations (CNVs) of 16p11.2 are associated with a wide spectrum of neuropsychiatric and neurodevelopmental disorders. Here, we use human induced pluripotent stem cells (iPSCs)-derived dopaminergic (DA) neurons carrying CNVs of 16p11.2 duplication (16pdup) and 16p11.2 deletion (16pdel), engineered using CRISPR-Cas9. We show that 16pdel iPSC-derived DA neurons have increased soma size and synaptic marker expression compared to isogenic control lines, while 16pdup iPSC-derived DA neurons show deficits in neuronal differentiation and reduced synaptic marker expression. The 16pdel iPSC-derived DA neurons have impaired neurophysiological properties. The 16pdel iPSC-derived DA neuronal networks are hyperactive and have increased bursting in culture compared to controls. We also show that the expression of RHOA is increased in the 16pdel iPSC-derived DA neurons and that treatment with a specific RHOA-inhibitor, Rhosin, rescues the network activity of the 16pdel iPSC-derived DA neurons. Our data suggest that 16p11.2 deletion-associated iPSC-derived DA neuron hyperactivation can be rescued by RHOA inhibition.},
keywords = {ETH-CMOS-MEA, IPSC, MaxOne},
pubstate = {published},
tppubtype = {article}
}
Reciprocal copy number variations (CNVs) of 16p11.2 are associated with a wide spectrum of neuropsychiatric and neurodevelopmental disorders. Here, we use human induced pluripotent stem cells (iPSCs)-derived dopaminergic (DA) neurons carrying CNVs of 16p11.2 duplication (16pdup) and 16p11.2 deletion (16pdel), engineered using CRISPR-Cas9. We show that 16pdel iPSC-derived DA neurons have increased soma size and synaptic marker expression compared to isogenic control lines, while 16pdup iPSC-derived DA neurons show deficits in neuronal differentiation and reduced synaptic marker expression. The 16pdel iPSC-derived DA neurons have impaired neurophysiological properties. The 16pdel iPSC-derived DA neuronal networks are hyperactive and have increased bursting in culture compared to controls. We also show that the expression of RHOA is increased in the 16pdel iPSC-derived DA neurons and that treatment with a specific RHOA-inhibitor, Rhosin, rescues the network activity of the 16pdel iPSC-derived DA neurons. Our data suggest that 16p11.2 deletion-associated iPSC-derived DA neuron hyperactivation can be rescued by RHOA inhibition.
@article{Kajiwara2021,
title = {Inhibitory neurons exhibit high controlling ability in the cortical microconnectome},
author = {Kajiwara, Motoki; Nomura, Ritsuki; Goetze, Felix; Kawabata, Masanori; Isomura, Yoshikazu; Akutsu, Tatsuya; Shimono, Masanori; },
url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008846},
year = {2021},
date = {2021-04-08},
journal = {PLOS Computational Biology},
abstract = {The brain is a network system in which excitatory and inhibitory neurons keep activity bal- anced in the highly non-random connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neu- rons in the cortex. So, in general, how inhibitory neurons can keep the balance with the sur- rounding excitatory neurons is an important question. There is much accumulated knowledge about this fundamental question. This study quantitatively evaluated the rela- tively higher functional contribution of inhibitory neurons in terms of not only properties of individual neurons, such as firing rate, but also in terms of topological mechanisms and con- trolling ability on other excitatory neurons. We combined simultaneous electrical recording (~2.5 hours) of ~1000 neurons in vitro, and quantitative evaluation of neuronal interactions including excitatory-inhibitory categorization. This study accurately defined recording brain anatomical targets, such as brain regions and cortical layers, by inter-referring MRI and immunostaining recordings. The interaction networks enabled us to quantify topological influence of individual neurons, in terms of controlling ability to other neurons. Especially, the result indicated that highly influential inhibitory neurons show higher controlling ability of other neurons than excitatory neurons, and are relatively often distributed in deeper layers of the cortex. Furthermore, the neurons having high controlling ability are more effectively limited in number than central nodes of k-cores, and these neurons also participate in more clustered motifs. In summary, this study suggested that the high controlling ability of inhibi- tory neurons is a key mechanism to keep balance with a large number of other excitatory neurons beyond simple higher firing rate. Application of the selection method of limited important neurons would be also applicable for the ability to effectively and selectively stimu- late E/I imbalanced disease states.},
keywords = {Brain Slice, MaxOne},
pubstate = {published},
tppubtype = {article}
}
The brain is a network system in which excitatory and inhibitory neurons keep activity bal- anced in the highly non-random connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neu- rons in the cortex. So, in general, how inhibitory neurons can keep the balance with the sur- rounding excitatory neurons is an important question. There is much accumulated knowledge about this fundamental question. This study quantitatively evaluated the rela- tively higher functional contribution of inhibitory neurons in terms of not only properties of individual neurons, such as firing rate, but also in terms of topological mechanisms and con- trolling ability on other excitatory neurons. We combined simultaneous electrical recording (~2.5 hours) of ~1000 neurons in vitro, and quantitative evaluation of neuronal interactions including excitatory-inhibitory categorization. This study accurately defined recording brain anatomical targets, such as brain regions and cortical layers, by inter-referring MRI and immunostaining recordings. The interaction networks enabled us to quantify topological influence of individual neurons, in terms of controlling ability to other neurons. Especially, the result indicated that highly influential inhibitory neurons show higher controlling ability of other neurons than excitatory neurons, and are relatively often distributed in deeper layers of the cortex. Furthermore, the neurons having high controlling ability are more effectively limited in number than central nodes of k-cores, and these neurons also participate in more clustered motifs. In summary, this study suggested that the high controlling ability of inhibi- tory neurons is a key mechanism to keep balance with a large number of other excitatory neurons beyond simple higher firing rate. Application of the selection method of limited important neurons would be also applicable for the ability to effectively and selectively stimu- late E/I imbalanced disease states.
@article{Yuan2021,
title = {Extracellular Recording of Entire Neural Networks Using a Dual-Mode Microelectrode Array With 19,584 Electrodes and High SNR},
author = {Xinyue Yuan and Andreas Hierlemann and Urs Frey},
url = {https://ieeexplore.ieee.org/document/9385387},
doi = {10.1109/JSSC.2021.3066043},
year = {2021},
date = {2021-03-24},
journal = {IEEE},
abstract = {Electrophysiological research on neural networks and their activity focuses on the recording and analysis of large data sets that include information of thousands of neurons. CMOS microelectrode arrays (MEAs) feature thousands of electrodes at a spatial resolution on the scale of single cells and are, therefore, ideal tools to support neural-network research. Moreover, they offer high spatio-temporal resolution and signal-to-noise ratio (SNR) to capture all features and subcellular-resolution details of neuronal signaling. Here, we present a dual-mode (DM) MEA, which enables simultaneous: 1) full-frame readout from all electrodes and 2) high-SNR readout from an arbitrarily selectable subset of electrodes. The DM-MEA includes 19,584 electrodes, 19,584 full-frame recording channels with noise levels of 10.4 μVrms in the action potential (AP) frequency band (300 Hz-5 kHz), 246 low-noise recording channels with noise levels of 3.0 μVrms in the AP band and eight stimulation units. The capacity to simultaneously perform full-frame and high-SNR recordings endows the presented DM-MEA with great flexibility for various applications in neuroscience and pharmacology.},
keywords = {ETH-CMOS-MEA, MEA Technology},
pubstate = {published},
tppubtype = {article}
}
Electrophysiological research on neural networks and their activity focuses on the recording and analysis of large data sets that include information of thousands of neurons. CMOS microelectrode arrays (MEAs) feature thousands of electrodes at a spatial resolution on the scale of single cells and are, therefore, ideal tools to support neural-network research. Moreover, they offer high spatio-temporal resolution and signal-to-noise ratio (SNR) to capture all features and subcellular-resolution details of neuronal signaling. Here, we present a dual-mode (DM) MEA, which enables simultaneous: 1) full-frame readout from all electrodes and 2) high-SNR readout from an arbitrarily selectable subset of electrodes. The DM-MEA includes 19,584 electrodes, 19,584 full-frame recording channels with noise levels of 10.4 μVrms in the action potential (AP) frequency band (300 Hz-5 kHz), 246 low-noise recording channels with noise levels of 3.0 μVrms in the AP band and eight stimulation units. The capacity to simultaneously perform full-frame and high-SNR recordings endows the presented DM-MEA with great flexibility for various applications in neuroscience and pharmacology.
@article{Ronchi2021,
title = {Microelectrode Arrays: Electrophysiological Phenotype Characterization of Human iPSC-Derived Neuronal Cell Lines by Means of High-Density Microelectrode Arrays},
author = {Silvia Ronchi and Alessio Paolo Buccino and Gustavo Prack and Sreedhar Saseendran Kumar and Manuel Schröter and Michele Fiscella and Andreas Hierlemann},
url = {https://onlinelibrary.wiley.com/doi/10.1002/adbi.202000223},
doi = {10.1002/adbi.202000223},
year = {2021},
date = {2021-03-17},
journal = {Advanced Biology},
volume = {5},
number = {3},
abstract = {In article number 2000223, Silvia Ronchi, Michele Fiscella, and co-workers show neurons plated on a high-density microelectrode array. The small electrode size and the tight spacing between the 26 400 electrodes enable functional extracellular electrophysiological characterization of neurons across scales, from subcellular-resolution features, like axons and dendrites, through individual neuronal cells to entire networks.},
keywords = {ETH-CMOS-MEA, IPSC},
pubstate = {published},
tppubtype = {article}
}
In article number 2000223, Silvia Ronchi, Michele Fiscella, and co-workers show neurons plated on a high-density microelectrode array. The small electrode size and the tight spacing between the 26 400 electrodes enable functional extracellular electrophysiological characterization of neurons across scales, from subcellular-resolution features, like axons and dendrites, through individual neuronal cells to entire networks.
@article{Sharf2021,
title = {Intrinsic network activity in human brain organoids},
author = {Tal Sharf and Tjitse van der Molen and Elmer Guzman and Stella M.K. Glasauer and Gabriel Luna and Zhouwei Cheng and Morgane Audouard and Kamalini G. Ranasinghe and Kiwamu Kudo and Srikantan S. Nagarajan and Kenneth R. Tovar and Linda R. Petzold and Paul K. Hansma and Kenneth S. Kosik},
url = {https://www.biorxiv.org/content/10.1101/2021.01.28.428643v1},
doi = {10.1101/2021.01.28.428643},
year = {2021},
date = {2021-01-28},
journal = {BioRxiv},
abstract = {Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we probed broadband and three-dimensional spontaneous activity of human brain organoids. These recordings simultaneously captured local field potentials (LFPs) and single unit activity. From spiking activity, we estimated a directed functional connectivity graph of synchronous neural network activity which showed a large number of weak functional connections enmeshed within a network skeleton of significantly fewer strong connections. Increasing the intrinsic inhibitory tone with a benzodiazepine altered the functional network graph of the organoid by suppressing the network skeleton. Simultaneously examining the spontaneous LFPs and their phase alignment to spiking showed that spike bursts were coherent with theta oscillations in the LFPs. An ensemble of spikes phase-locked to theta frequency oscillations were strongly interconnected as a sub-network within the larger network in which they were embedded. Our results demonstrate that human brain organoids have self-organized neuronal assemblies of sufficient size, cellular orientation, and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug mechanisms, and the effects of external stimuli upon neuronal networks.},
keywords = {ETH-CMOS-MEA, Neuronal Networks, Organoids},
pubstate = {published},
tppubtype = {article}
}
Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we probed broadband and three-dimensional spontaneous activity of human brain organoids. These recordings simultaneously captured local field potentials (LFPs) and single unit activity. From spiking activity, we estimated a directed functional connectivity graph of synchronous neural network activity which showed a large number of weak functional connections enmeshed within a network skeleton of significantly fewer strong connections. Increasing the intrinsic inhibitory tone with a benzodiazepine altered the functional network graph of the organoid by suppressing the network skeleton. Simultaneously examining the spontaneous LFPs and their phase alignment to spiking showed that spike bursts were coherent with theta oscillations in the LFPs. An ensemble of spikes phase-locked to theta frequency oscillations were strongly interconnected as a sub-network within the larger network in which they were embedded. Our results demonstrate that human brain organoids have self-organized neuronal assemblies of sufficient size, cellular orientation, and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug mechanisms, and the effects of external stimuli upon neuronal networks.
@article{Idrees2020b,
title = {Different contrast encoding in ON and OFF visual pathways},
author = {Saad Idrees and Thomas A. Münch },
url = {https://www.biorxiv.org/content/10.1101/2020.11.25.398230v1},
doi = {10.1101/2020.11.25.398230},
year = {2020},
date = {2020-11-26},
journal = {BioRxiv},
abstract = {Subjective visual experience builds on sensory encoding of light reflected by different objects in our environment. Most retinal ganglion cells encode changes in light intensity, quantified as contrast, rather than the absolute intensity. Mathematically, contrast is often defined as a relative change in light intensity. Activity in the visual system and perceptual responses are usually explained with such definitions of contrast. Here, for the first time, we explicitly explored how contrast is actually represented in the visual system. Using mouse retina electrophysiology, we show that response strength of OFF retinal ganglion cells does not represent relative, but absolute changes in light intensity. ON RGC response strength is governed by a combination of absolute and relative change in light intensity. This is true for a wide range of ambient light levels, at least from scotopic to high mesopic regimes. Consequently, light decrements and increments are represented asymmetrically in the retina, which may explain the asymmetries in responses to negative and positive contrast observed throughout the visual system. These findings may help to more thoroughly design and interpret vision science studies where responses are driven by contrast of the visual stimuli.},
keywords = {MaxOne, Retina},
pubstate = {published},
tppubtype = {article}
}
Subjective visual experience builds on sensory encoding of light reflected by different objects in our environment. Most retinal ganglion cells encode changes in light intensity, quantified as contrast, rather than the absolute intensity. Mathematically, contrast is often defined as a relative change in light intensity. Activity in the visual system and perceptual responses are usually explained with such definitions of contrast. Here, for the first time, we explicitly explored how contrast is actually represented in the visual system. Using mouse retina electrophysiology, we show that response strength of OFF retinal ganglion cells does not represent relative, but absolute changes in light intensity. ON RGC response strength is governed by a combination of absolute and relative change in light intensity. This is true for a wide range of ambient light levels, at least from scotopic to high mesopic regimes. Consequently, light decrements and increments are represented asymmetrically in the retina, which may explain the asymmetries in responses to negative and positive contrast observed throughout the visual system. These findings may help to more thoroughly design and interpret vision science studies where responses are driven by contrast of the visual stimuli.
@article{Battaglia2020,
title = {Corticotropin-releasing hormone (CRH) alters mitochondrial morphology and function by activating the NF-kB-DRP1 axis in hippocampal neurons},
author = {Chiara R. Battaglia and Silvia Cursano and Enrico Calzia and Alberto Catanese and Tobias M. Boeckers },
url = {https://www.nature.com/articles/s41419-020-03204-3},
doi = {https://doi.org/10.1038/s41419-020-03204-3},
year = {2020},
date = {2020-11-23},
journal = {Cell Death & Disease},
abstract = {Neuronal stress-adaptation combines multiple molecular responses. We have previously reported that thorax trauma induces a transient loss of hippocampal excitatory synapses mediated by the local release of the stress-related hormone corticotropin-releasing hormone (CRH). Since a physiological synaptic activity relies also on mitochondrial functionality, we investigated the direct involvement of mitochondria in the (mal)-adaptive changes induced by the activation of neuronal CRH receptors 1 (CRHR1). We observed, in vivo and in vitro, a significant shift of mitochondrial dynamics towards fission, which correlated with increased swollen mitochondria and aberrant cristae. These morphological changes, which are associated with increased NF-kB activity and nitric oxide concentrations, correlated with a pronounced reduction of mitochondrial activity. However, ATP availability was unaltered, suggesting that neurons maintain a physiological energy metabolism to preserve them from apoptosis under CRH exposure. Our findings demonstrate that stress-induced CRHR1 activation leads to strong, but reversible, modifications of mitochondrial dynamics and morphology. These alterations are accompanied by bioenergetic defects and the reduction of neuronal activity, which are linked to increased intracellular oxidative stress, and to the activation of the NF-kB/c-Abl/DRP1 axis.
},
keywords = {MaxTwo},
pubstate = {published},
tppubtype = {article}
}
Neuronal stress-adaptation combines multiple molecular responses. We have previously reported that thorax trauma induces a transient loss of hippocampal excitatory synapses mediated by the local release of the stress-related hormone corticotropin-releasing hormone (CRH). Since a physiological synaptic activity relies also on mitochondrial functionality, we investigated the direct involvement of mitochondria in the (mal)-adaptive changes induced by the activation of neuronal CRH receptors 1 (CRHR1). We observed, in vivo and in vitro, a significant shift of mitochondrial dynamics towards fission, which correlated with increased swollen mitochondria and aberrant cristae. These morphological changes, which are associated with increased NF-kB activity and nitric oxide concentrations, correlated with a pronounced reduction of mitochondrial activity. However, ATP availability was unaltered, suggesting that neurons maintain a physiological energy metabolism to preserve them from apoptosis under CRH exposure. Our findings demonstrate that stress-induced CRHR1 activation leads to strong, but reversible, modifications of mitochondrial dynamics and morphology. These alterations are accompanied by bioenergetic defects and the reduction of neuronal activity, which are linked to increased intracellular oxidative stress, and to the activation of the NF-kB/c-Abl/DRP1 axis.
@article{Ricci2020,
title = {MAPSYNE: Miniaturized micropipette system combined with high-density microelectrode arrays for automated manipulation of neuronal networks in-vitro},
author = {Chiara Ricci and Urs Frey and Marie Engelene J. Obien},
url = {https://ieeexplore.ieee.org/document/9175797/},
doi = {10.1109/EMBC44109.2020.9175797},
year = {2020},
date = {2020-10-08},
journal = {IEEE},
abstract = {We present MAPSYNE, a miniaturized and automated system combining a high-density microelectrode array (HD-MEA) and a movable micropipette for studying, monitoring, and perturbing neurons in vitro. The system involves an all-electrical approach to automatically move a glass micropipette towards a target location on the HD-MEA surface, without the need for a microscope. Two methods of performing blind navigation are employed, (i) stop-measure-go approach wherein the pipette moves for a predefined distance before measuring its location then the process is repeated until the pipette reaches its destination, and (ii) predictive approach wherein the pipette is continuously tracked and moved. This automated system can be applied for unsupervised single-cell manipulation of neurons in a network, such as electroporation and local delivery of compounds.},
keywords = {Activity Scan Assay, HD-MEA, MaxOne, MEA Technology},
pubstate = {published},
tppubtype = {article}
}
We present MAPSYNE, a miniaturized and automated system combining a high-density microelectrode array (HD-MEA) and a movable micropipette for studying, monitoring, and perturbing neurons in vitro. The system involves an all-electrical approach to automatically move a glass micropipette towards a target location on the HD-MEA surface, without the need for a microscope. Two methods of performing blind navigation are employed, (i) stop-measure-go approach wherein the pipette moves for a predefined distance before measuring its location then the process is repeated until the pipette reaches its destination, and (ii) predictive approach wherein the pipette is continuously tracked and moved. This automated system can be applied for unsupervised single-cell manipulation of neurons in a network, such as electroporation and local delivery of compounds.
@article{Yuan2020,
title = {Versatile live-cell activity analysis platform for characterization of neuronal dynamics at single-cell and network level},
author = {Xinyue Yuan and Manuel Schröter and Marie Engelene J. Obien and Michele Fiscella and Wei Gong and Tetsuhiro Kikuchi and Aoi Odawara and Shuhei Noji and Ikuro Suzuki and Jun Takahashi and Andreas Hierlemann and Urs Frey},
url = {https://www.nature.com/articles/s41467-020-18620-4#citeas},
doi = {10.1038/s41467-020-18620-4},
year = {2020},
date = {2020-09-25},
journal = {Nature Communications},
volume = {11},
number = {4854},
abstract = {Chronic imaging of neuronal networks in vitro has provided fundamental insights into mechanisms underlying neuronal function. Current labeling and optical imaging methods, however, cannot be used for continuous and long-term recordings of the dynamics and evolution of neuronal networks, as fluorescent indicators can cause phototoxicity. Here, we introduce a versatile platform for label-free, comprehensive and detailed electrophysiological live-cell imaging of various neurogenic cells and tissues over extended time scales. We report on a dual-mode high-density microelectrode array, which can simultaneously record in (i) full-frame mode with 19,584 recording sites and (ii) high-signal-to-noise mode with 246 channels. We set out to demonstrate the capabilities of this platform with recordings from primary and iPSC-derived neuronal cultures and tissue preparations over several weeks, providing detailed morpho-electrical phenotypic parameters at subcellular, cellular and network level. Moreover, we develop reliable analysis tools, which drastically increase the throughput to infer axonal morphology and conduction speed.},
keywords = {ETH-CMOS-MEA, MEA Technology},
pubstate = {published},
tppubtype = {article}
}
Chronic imaging of neuronal networks in vitro has provided fundamental insights into mechanisms underlying neuronal function. Current labeling and optical imaging methods, however, cannot be used for continuous and long-term recordings of the dynamics and evolution of neuronal networks, as fluorescent indicators can cause phototoxicity. Here, we introduce a versatile platform for label-free, comprehensive and detailed electrophysiological live-cell imaging of various neurogenic cells and tissues over extended time scales. We report on a dual-mode high-density microelectrode array, which can simultaneously record in (i) full-frame mode with 19,584 recording sites and (ii) high-signal-to-noise mode with 246 channels. We set out to demonstrate the capabilities of this platform with recordings from primary and iPSC-derived neuronal cultures and tissue preparations over several weeks, providing detailed morpho-electrical phenotypic parameters at subcellular, cellular and network level. Moreover, we develop reliable analysis tools, which drastically increase the throughput to infer axonal morphology and conduction speed.
@article{Kim2020,
title = {A magnetically actuated microrobot for targeted neural cell delivery and selective connection of neural networks},
author = {Eunhee Kim and Sungwoong Jeon and Hyun-Kyu An and Mehrnoosh Kianpour, Seong-Woon Yu and Jin-young Kim and Jong-Cheol Rah and Hongsoo Choi},
url = {https://advances.sciencemag.org/content/6/39/eabb5696},
doi = {10.1126/sciadv.abb5696},
year = {2020},
date = {2020-09-25},
journal = {Science Advances},
volume = {6},
number = {39},
abstract = {There has been a great deal of interest in the development of technologies for actively manipulating neural networks in vitro, providing natural but simplified environments in a highly reproducible manner in which to study brain function and related diseases. Platforms for these in vitro neural networks require precise and selective neural connections at the target location, with minimal external influences, and measurement of neural activity to determine how neurons communicate. Here, we report a neuron-loaded microrobot for selective connection of neural networks via precise delivery to a gap between two neural clusters by an external magnetic field. In addition, the extracellular action potential was propagated from one cluster to the other through the neurons on the microrobot. The proposed technique shows the potential for use in experiments to understand how neurons communicate in the neural network by actively connecting neural clusters.},
keywords = {microrobot, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
There has been a great deal of interest in the development of technologies for actively manipulating neural networks in vitro, providing natural but simplified environments in a highly reproducible manner in which to study brain function and related diseases. Platforms for these in vitro neural networks require precise and selective neural connections at the target location, with minimal external influences, and measurement of neural activity to determine how neurons communicate. Here, we report a neuron-loaded microrobot for selective connection of neural networks via precise delivery to a gap between two neural clusters by an external magnetic field. In addition, the extracellular action potential was propagated from one cluster to the other through the neurons on the microrobot. The proposed technique shows the potential for use in experiments to understand how neurons communicate in the neural network by actively connecting neural clusters.
@article{Cowan2020,
title = {Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution},
author = {Cameron S. Cowan and Magdalena Renner and Martina De Gennaro and Brigitte Gross-Scherf and David Goldblum and Yanyan Hou and Martin Munz and Tiago M. Rodrigues and Jacek Krol and Tamas Szikra and Rachel Cuttat and Annick Waldt and Panagiotis Papasaikas and Roland Diggelmann and Claudia P. Patino-Alvarez and Patricia Galliker and Stefan E. Spirig and Dinko Pavlinic and Nadine Gerber-Hollbach and Sven Schuierer and Aldin Srdanovic and Marton Balogh and Riccardo Panero and Akos Kusnyerik and Arnold Szabo and Michael B. Stadler and Selim Orgül and Simone Picelli and Pascal W. Hasler and Andreas Hierlemann and Hendrik P.N. Scholl and Guglielmo Roma and Florian Nigsch and Botond Roska},
url = {https://www.cell.com/cell/fulltext/S0092-8674(20)31004-7?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0092867420310047%3Fshowall%3Dtrue},
doi = {10.1016/j.cell.2020.08.013},
year = {2020},
date = {2020-09-17},
journal = {CellPress},
volume = {182},
pages = { 1623–1640},
abstract = {Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas, and performed histochemistry. Cell types in organoids matured in vitro to a stable “developed” state at a rate similar to human retina development in vivo. Transcriptomes of organoid cell types converged toward the transcriptomes of adult peripheral retinal cell types. Expression of disease-associated genes was cell-type-specific in adult retina, and cell-type specificity was retained in organoids. We implicate unexpected cell types in diseases such as macular degeneration. This resource identifies cellular targets for studying disease mechanisms in organoids and for targeted repair in human retinas.},
keywords = {ETH-CMOS-MEA, Organoids},
pubstate = {published},
tppubtype = {article}
}
Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas, and performed histochemistry. Cell types in organoids matured in vitro to a stable “developed” state at a rate similar to human retina development in vivo. Transcriptomes of organoid cell types converged toward the transcriptomes of adult peripheral retinal cell types. Expression of disease-associated genes was cell-type-specific in adult retina, and cell-type specificity was retained in organoids. We implicate unexpected cell types in diseases such as macular degeneration. This resource identifies cellular targets for studying disease mechanisms in organoids and for targeted repair in human retinas.
@article{Ronchi2020,
title = {Electrophysiological Phenotype Characterization of Human iPSC-Derived Neuronal Cell Lines by Means of High-Density Microelectrode Arrays},
author = {Silvia Ronchi and Alessio Paolo Buccino and Gustavo Prack and Sreedhar Saseendran Kumar and Manuel Schröter and Michele Fiscella and Andreas Hierlemann },
url = {https://www.biorxiv.org/content/10.1101/2020.09.02.271403v1},
doi = {10.1101/2020.09.02.271403},
year = {2020},
date = {2020-09-02},
journal = {BioRxiv},
abstract = {Recent advances in the field of cellular reprogramming have opened a route to study the fundamental mechanisms underlying common neurological disorders. High-density microelectrode-arrays (HD-MEAs) provide unprecedented means to study neuronal physiology at different scales, ranging from network through single-neuron to subcellular features. In this work, we used HD-MEAs in vitro to characterize and compare human induced-pluripotent-stem-cell (iPSC)-derived dopaminergic and motor neurons, including isogenic neuronal lines modeling Parkinson’s disease and amyotrophic lateral sclerosis. We established reproducible electrophysiological network, single-cell and subcellular metrics, which were used for phenotype characterization and drug testing. Metrics such as burst shapes and axonal velocity enabled the distinction of healthy and diseased neurons. The HD-MEA metrics could also be used to detect the effects of dosing the drug retigabine to human motor neurons. Finally, we showed that the ability to detect drug effects and the observed culture-to-culture variability critically depend on the number of available recording electrodes},
keywords = {ETH-CMOS-MEA, IPSC},
pubstate = {published},
tppubtype = {article}
}
Recent advances in the field of cellular reprogramming have opened a route to study the fundamental mechanisms underlying common neurological disorders. High-density microelectrode-arrays (HD-MEAs) provide unprecedented means to study neuronal physiology at different scales, ranging from network through single-neuron to subcellular features. In this work, we used HD-MEAs in vitro to characterize and compare human induced-pluripotent-stem-cell (iPSC)-derived dopaminergic and motor neurons, including isogenic neuronal lines modeling Parkinson’s disease and amyotrophic lateral sclerosis. We established reproducible electrophysiological network, single-cell and subcellular metrics, which were used for phenotype characterization and drug testing. Metrics such as burst shapes and axonal velocity enabled the distinction of healthy and diseased neurons. The HD-MEA metrics could also be used to detect the effects of dosing the drug retigabine to human motor neurons. Finally, we showed that the ability to detect drug effects and the observed culture-to-culture variability critically depend on the number of available recording electrodes
@article{Al-Absi2020,
title = {Layers II/III of Prefrontal Cortex in Df(h22q11)/+ Mouse Model of the 22q11.2 Deletion Display Loss of Parvalbumin Interneurons and Modulation of Neuronal Morphology and Excitability},
author = {Abdel-Rahman Al-Absi and Per Qvist and Samora Okujeni and Ahmad Raza Khan and Simon Glerup and Connie Sanchez and Jens R. Nyengaard },
url = {https://link.springer.com/article/10.1007/s12035-020-02067-1},
doi = {https://doi.org/10.1007/s12035-020-02067-1},
year = {2020},
date = {2020-08-20},
journal = {Molecular Neurobiology},
abstract = {The 22q11.2 deletion has been identified as a risk factor for multiple neurodevelopmental disorders. Behavioral and cognitive impairments are common among carriers of the 22q11.2 deletion. Parvalbumin expressing (PV+) interneurons provide perisomatic inhibition of excitatory neuronal circuits through GABAA receptors, and a deficit of PV+ inhibitory circuits may underlie a multitude of the behavioral and functional deficits in the 22q11.2 deletion syndrome. We investigated putative deficits of PV+ inhibitory circuits and the associated molecular, morphological, and functional alterations in the prefrontal cortex (PFC) of the Df(h22q11)/+ mouse model of the 22q11.2 hemizygous deletion. We detected a significant decrease in the number of PV+ interneurons in layers II/III of PFC in Df(h22q11)/+ mice together with a reduction in the mRNA and protein levels of GABAA (α3), a PV+ putative postsynaptic receptor subunit. Pyramidal neurons from the same layers further experienced morphological reorganizations of spines and dendrites. Accordingly, a decrease in the levels of the postsynaptic density protein 95 (PSD95) and a higher neuronal activity in response to the GABAA antagonist bicuculline were measured in these layers in PFC of Df(h22q11)/+ mice compared with their wild-type littermates. Our study shows that a hemizygotic deletion of the 22q11.2 locus leads to deficit in the GABAergic control of network activity and involves molecular and morphological changes in both the inhibitory and excitatory synapses of parvalbumin interneurons and pyramidal neurons specifically in layers II/III PFC.},
keywords = {MaxOne, Slices},
pubstate = {published},
tppubtype = {article}
}
The 22q11.2 deletion has been identified as a risk factor for multiple neurodevelopmental disorders. Behavioral and cognitive impairments are common among carriers of the 22q11.2 deletion. Parvalbumin expressing (PV+) interneurons provide perisomatic inhibition of excitatory neuronal circuits through GABAA receptors, and a deficit of PV+ inhibitory circuits may underlie a multitude of the behavioral and functional deficits in the 22q11.2 deletion syndrome. We investigated putative deficits of PV+ inhibitory circuits and the associated molecular, morphological, and functional alterations in the prefrontal cortex (PFC) of the Df(h22q11)/+ mouse model of the 22q11.2 hemizygous deletion. We detected a significant decrease in the number of PV+ interneurons in layers II/III of PFC in Df(h22q11)/+ mice together with a reduction in the mRNA and protein levels of GABAA (α3), a PV+ putative postsynaptic receptor subunit. Pyramidal neurons from the same layers further experienced morphological reorganizations of spines and dendrites. Accordingly, a decrease in the levels of the postsynaptic density protein 95 (PSD95) and a higher neuronal activity in response to the GABAA antagonist bicuculline were measured in these layers in PFC of Df(h22q11)/+ mice compared with their wild-type littermates. Our study shows that a hemizygotic deletion of the 22q11.2 locus leads to deficit in the GABAergic control of network activity and involves molecular and morphological changes in both the inhibitory and excitatory synapses of parvalbumin interneurons and pyramidal neurons specifically in layers II/III PFC.
@article{Bandarabadi2020,
title = {Sleep as a default state of cortical and subcortical networks},
author = {Mojtaba Bandarabadi and Anne Vassalli and Mehdi Tafti},
url = {https://www.sciencedirect.com/science/article/pii/S2468867319301907?via%3Dihub},
doi = {10.1016/j.cophys.2019.12.004},
year = {2020},
date = {2020-06-20},
journal = {Current Opinion in Physiology},
volume = {15},
pages = {60-67},
abstract = {Sleep has been conceptualized as ‘activity-dependent’, hence a response to prior waking experience, and proposed to be ‘the price the brain pays for plasticity during wakefulness’. We here propose that at the level of neuronal networks, particularly those arising from isolated embryonic thalamocortical cells maintained in culture, it represents a default mode of functioning. We show that cell assemblies in ex vivo cultures express powerful sleep specific patterns of oscillatory activity, as well as metabolic and molecular signatures of the sleep state. We summarize recent evidences that support our hypothesis and discuss potential applications of developing ex vivo sleep models to answer open questions in the field.},
keywords = {Neuronal Networks, Review, Sleep},
pubstate = {published},
tppubtype = {article}
}
Sleep has been conceptualized as ‘activity-dependent’, hence a response to prior waking experience, and proposed to be ‘the price the brain pays for plasticity during wakefulness’. We here propose that at the level of neuronal networks, particularly those arising from isolated embryonic thalamocortical cells maintained in culture, it represents a default mode of functioning. We show that cell assemblies in ex vivo cultures express powerful sleep specific patterns of oscillatory activity, as well as metabolic and molecular signatures of the sleep state. We summarize recent evidences that support our hypothesis and discuss potential applications of developing ex vivo sleep models to answer open questions in the field.
@article{Masumori2020,
title = {Neural Autopoiesis: Organizing Self-Boundaries by Stimulus Avoidance in Biological and Artificial Neural Networks},
author = {Atsushi Masumori and Lana Sinapayen and Norihiro Maruyama and Takeshi Mita and Douglas J. Bakkum and Urs Frey and Hirokazu Takahashi and Takashi Ikegami},
url = {https://www.mitpressjournals.org/doi/full/10.1162/artl_a_00314},
doi = {10.1162/artl_a_00314},
issn = {1064-5462},
year = {2020},
date = {2020-04-28},
journal = {Artificial Life},
volume = {26},
number = {1},
pages = {130-151},
abstract = {Living organisms must actively maintain themselves in order to continue existing. Autopoiesis is a key concept in the study of living organisms, where the boundaries of the organism are not static but dynamically regulated by the system itself. To study the autonomous regulation of a self-boundary, we focus on neural homeodynamic responses to environmental changes using both biological and artificial neural networks. Previous studies showed that embodied cultured neural networks and spiking neural networks with spike-timing dependent plasticity (STDP) learn an action as they avoid stimulation from outside. In this article, as a result of our experiments using embodied cultured neurons, we find that there is also a second property allowing the network to avoid stimulation: If the agent cannot learn an action to avoid the external stimuli, it tends to decrease the stimulus-evoked spikes, as if to ignore the uncontrollable input. We also show such a behavior is reproduced by spiking neural networks with asymmetric STDP. We consider that these properties are to be regarded as autonomous regulation of self and nonself for the network, in which a controllable neuron is regarded as self, and an uncontrollable neuron is regarded as nonself. Finally, we introduce neural autopoiesis by proposing the principle of stimulus avoidance.},
keywords = {Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Living organisms must actively maintain themselves in order to continue existing. Autopoiesis is a key concept in the study of living organisms, where the boundaries of the organism are not static but dynamically regulated by the system itself. To study the autonomous regulation of a self-boundary, we focus on neural homeodynamic responses to environmental changes using both biological and artificial neural networks. Previous studies showed that embodied cultured neural networks and spiking neural networks with spike-timing dependent plasticity (STDP) learn an action as they avoid stimulation from outside. In this article, as a result of our experiments using embodied cultured neurons, we find that there is also a second property allowing the network to avoid stimulation: If the agent cannot learn an action to avoid the external stimuli, it tends to decrease the stimulus-evoked spikes, as if to ignore the uncontrollable input. We also show such a behavior is reproduced by spiking neural networks with asymmetric STDP. We consider that these properties are to be regarded as autonomous regulation of self and nonself for the network, in which a controllable neuron is regarded as self, and an uncontrollable neuron is regarded as nonself. Finally, we introduce neural autopoiesis by proposing the principle of stimulus avoidance.
@article{Idrees2020,
title = {Perceptual saccadic suppression starts in the retina},
author = {Saad Idrees and Matthias P. Baumann and Felix Franke and Thomas A. Münch and Ziad M. Hafed},
url = {https://www.nature.com/articles/s41467-020-15890-w},
doi = {10.1038/s41467-020-15890-w},
year = {2020},
date = {2020-04-24},
journal = {Nature Communications},
volume = {11},
number = {1977},
keywords = {ETH-CMOS-MEA, MaxOne, Retina},
pubstate = {published},
tppubtype = {article}
}
@article{Obaid2020,
title = {Massively parallel microwire arrays integrated withCMOS chips for neural recording},
author = {Abdulmalik Obaid and Mina-Elrahb Hanna and Yu-Wei Wu and Mihaly Kollo and Romeo Racz and Matthew R Angle and Jan Muller and Nora Brackbill and William Wray and Felix Franke and E J Chichilnski and Andreas Hierlemann and Jun B. Ding and Andreas T. Schaefer and Nicholas A. Melosh},
url = {https://advances.sciencemag.org/content/6/12/eaay2789},
doi = {10.1126/sciadv.aay2789},
year = {2020},
date = {2020-03-20},
journal = {Science Advances},
abstract = {Multi-channel electrical recordings of neural activity in the brain is an increasingly powerful method revealing new aspects of neural communication, computation, and prosthetics. However, while planar silicon-based CMOS devices in conventional electronics scale rapidly, neural interface devices have not kept pace. Here, we present a new strategy to interface silicon-based chips with three-dimensional microwire arrays, providing the link between rapidly-developing electronics and high density neural interfaces. The system consists of a bundle of microwires mated to large-scale microelectrode arrays, such as camera chips. This system has excellent recording performance, demonstrated via single unit and local-field potential recordings in isolated retina and in the motor cortex or striatum of awake moving mice. The modular design enables a variety of microwire types and sizes to be integrated with different types of pixel arrays, connecting the rapid progress of commercial multiplexing, digitisation and data acquisition hardware together with a three-dimensional neural interface.},
keywords = {Electrodes, ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
Multi-channel electrical recordings of neural activity in the brain is an increasingly powerful method revealing new aspects of neural communication, computation, and prosthetics. However, while planar silicon-based CMOS devices in conventional electronics scale rapidly, neural interface devices have not kept pace. Here, we present a new strategy to interface silicon-based chips with three-dimensional microwire arrays, providing the link between rapidly-developing electronics and high density neural interfaces. The system consists of a bundle of microwires mated to large-scale microelectrode arrays, such as camera chips. This system has excellent recording performance, demonstrated via single unit and local-field potential recordings in isolated retina and in the motor cortex or striatum of awake moving mice. The modular design enables a variety of microwire types and sizes to be integrated with different types of pixel arrays, connecting the rapid progress of commercial multiplexing, digitisation and data acquisition hardware together with a three-dimensional neural interface.
@article{Kajiwara2020,
title = {Inhibitory neurons are a Central Controlling regulator in the effective cortical microconnectome},
author = {Motoki Kajiwara and Ritsuki Nomura and Felix Goetze and Tatsuya Akutsu and Masanori Shimono},
url = {https://www.biorxiv.org/content/10.1101/2020.02.18.954016v1},
doi = {10.1101/2020.02.18.954016},
year = {2020},
date = {2020-02-18},
journal = {bioRxiv },
abstract = {The brain is a network system in which excitatory and inhibitory neurons keep the activity balanced in the highly non-uniform connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons. So, in general, how the inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question.
We observed effective networks, reflecting causal interactions, of ~1000 neurons in cortical acute slices. Surprisingly, we found that inhibitory neurons are not only located at more central positions than excitatory neurons but also have stronger controlling ability of other neurons than excitatory neurons. Besides, we found that the precedence in centrality and controlling ability of inhibitory neurons are well observed in deep cortical layers by comparing with distribution of neurons coloured by NeuN immunostaining data. Preceding the observation, we also found that inhibitory neurons show higher firing rate than excitatory neurons, and that their firing rate also closely obey a log-normal distribution as previously known about excitatory neurons. Additionally, their connectivity strengths also obeyed a log-normal distribution.
In summary, within the network interaction of huge numbers of neurons, inhibitory neurons seem to produce a central controlling system that sustains the homeostatic behavior of the brain. A similar evaluation in different life stages and in disease states etc. will not only provide deeper understandings in the homeostasis of the brain, but also will provide a selective and effective way to stimulate individual neurons to modulate neuropsychiatry or neurodegeneration disease states.},
keywords = {Inhibitory Neurons},
pubstate = {published},
tppubtype = {article}
}
The brain is a network system in which excitatory and inhibitory neurons keep the activity balanced in the highly non-uniform connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons. So, in general, how the inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question.
We observed effective networks, reflecting causal interactions, of ~1000 neurons in cortical acute slices. Surprisingly, we found that inhibitory neurons are not only located at more central positions than excitatory neurons but also have stronger controlling ability of other neurons than excitatory neurons. Besides, we found that the precedence in centrality and controlling ability of inhibitory neurons are well observed in deep cortical layers by comparing with distribution of neurons coloured by NeuN immunostaining data. Preceding the observation, we also found that inhibitory neurons show higher firing rate than excitatory neurons, and that their firing rate also closely obey a log-normal distribution as previously known about excitatory neurons. Additionally, their connectivity strengths also obeyed a log-normal distribution.
In summary, within the network interaction of huge numbers of neurons, inhibitory neurons seem to produce a central controlling system that sustains the homeostatic behavior of the brain. A similar evaluation in different life stages and in disease states etc. will not only provide deeper understandings in the homeostasis of the brain, but also will provide a selective and effective way to stimulate individual neurons to modulate neuropsychiatry or neurodegeneration disease states.
@conference{Shimba2019,
title = {Evaluation of Conduction Properties of Sensory Axons with High-Density Microelectrode Array},
author = {Kenta Shimba and Takahiro Asahina and Koji Sakai and Yasuhiko JImbo and Kiyoshi Kotani},
url = {https://ieeexplore.ieee.org/abstract/document/8990233},
doi = {10.1109/BMEiCON47515.2019.8990233},
year = {2019},
date = {2019-11-20},
abstract = {In vitro modeling of neurodegenerative disorder is a promising method for developing new treatment. However, little is known about myelination and subsequent increase of conduction velocity in vitro. Here, we aim to develop a new method for evaluating salutatory conduction from myelinated sensory axons. First, sensory neurons and Schwann cells were cultured on high-density microelectrode array chips. Myelin sheath formation was confirmed with immunocytochemistry. Axonal signal was detected, and instantaneous conduction velocity was evaluated. As a result, we observed that relatively fast conduction sites between slow conduction sites. Our method is suitable for evaluating conduction properties of sensory axons.},
keywords = {HD-MEA},
pubstate = {published},
tppubtype = {conference}
}
In vitro modeling of neurodegenerative disorder is a promising method for developing new treatment. However, little is known about myelination and subsequent increase of conduction velocity in vitro. Here, we aim to develop a new method for evaluating salutatory conduction from myelinated sensory axons. First, sensory neurons and Schwann cells were cultured on high-density microelectrode array chips. Myelin sheath formation was confirmed with immunocytochemistry. Axonal signal was detected, and instantaneous conduction velocity was evaluated. As a result, we observed that relatively fast conduction sites between slow conduction sites. Our method is suitable for evaluating conduction properties of sensory axons.
@inbook{Kubota2019b,
title = {Echo State Property of Neuronal Cell Cultures},
author = {Tomoyuki Kubota and Kohei Nakajima and Hirokazu Takahashi },
url = {https://link.springer.com/chapter/10.1007%2F978-3-030-30493-5_13},
doi = {10.1007/978-3-030-30493-5_13},
isbn = {978-3-030-30493-5},
year = {2019},
date = {2019-09-09},
volume = {11731},
publisher = {Springer},
abstract = {Physical reservoir computing (PRC) utilizes the nonlinear dynamics of physical systems, which is called a reservoir, as a computational resource. The prerequisite for physical dynamics to be a successful reservoir is to have the echo state property (ESP), asymptotic properties of transient trajectory to driving signals, with some memory held in the system. In this study, the prerequisites in dissociate cultures of cortical neuronal cells are estimated. With a state-of-the-art measuring system of high-dense CMOS array, our experiments demonstrated that each neuron exhibited reproducible spike trains in response to identical driving stimulus. Additionally, the memory function was estimated, which found that input information in the dynamics of neuronal activities in the culture up to at least 20 ms was retrieved. These results supported the notion that the cultures had ESP and could thereby serve as PRC.},
keywords = {Action Potential, MaxOne, Neuronal cell culture},
pubstate = {published},
tppubtype = {inbook}
}
Physical reservoir computing (PRC) utilizes the nonlinear dynamics of physical systems, which is called a reservoir, as a computational resource. The prerequisite for physical dynamics to be a successful reservoir is to have the echo state property (ESP), asymptotic properties of transient trajectory to driving signals, with some memory held in the system. In this study, the prerequisites in dissociate cultures of cortical neuronal cells are estimated. With a state-of-the-art measuring system of high-dense CMOS array, our experiments demonstrated that each neuron exhibited reproducible spike trains in response to identical driving stimulus. Additionally, the memory function was estimated, which found that input information in the dynamics of neuronal activities in the culture up to at least 20 ms was retrieved. These results supported the notion that the cultures had ESP and could thereby serve as PRC.
@article{Bullmann2019,
title = {Large-Scale Mapping of Axonal Arbors Using High-Density Microelectrode Arrays},
author = {Bullmann, Torsten; Radivojevic, Milos; Huber, Stefan T: Deligkaris, Kosmas; Hierlemann, Andreas; Frey, Urs},
url = {https://www.frontiersin.org/articles/10.3389/fncel.2019.00404/full},
doi = {10.3389/fncel.2019.00404},
issn = {1662-5102},
year = {2019},
date = {2019-09-06},
journal = {Frontiers in Cellular Neuroscience },
volume = {13},
abstract = {Understanding the role of axons in neuronal information processing is a fundamental task in neuroscience. Over the last years, sophisticated patch-clamp investigations have provided unexpected and exciting data on axonal phenomena and functioning, but there is still a need for methods to investigate full axonal arbors at sufficient throughput. Here, we present a new method for the simultaneous mapping of the axonal arbors of a large number of individual neurons, which relies on their extracellular signals that have been recorded with high-density microelectrode arrays (HD-MEAs). The segmentation of axons was performed based on the local correlation of extracellular signals. Comparison of the results with both, ground truth and receiver operator characteristics, shows that the new segmentation method outperforms previously used methods. Using a standard HD-MEA, we mapped the axonal arbors of 68 neurons in <6 h. The fully automated method can be extended to new generations of HD-MEAs with larger data output and is estimated to provide data of axonal arbors of thousands of neurons within recording sessions of a few hours.},
keywords = {Axonal Arbors, HD-MEA},
pubstate = {published},
tppubtype = {article}
}
Understanding the role of axons in neuronal information processing is a fundamental task in neuroscience. Over the last years, sophisticated patch-clamp investigations have provided unexpected and exciting data on axonal phenomena and functioning, but there is still a need for methods to investigate full axonal arbors at sufficient throughput. Here, we present a new method for the simultaneous mapping of the axonal arbors of a large number of individual neurons, which relies on their extracellular signals that have been recorded with high-density microelectrode arrays (HD-MEAs). The segmentation of axons was performed based on the local correlation of extracellular signals. Comparison of the results with both, ground truth and receiver operator characteristics, shows that the new segmentation method outperforms previously used methods. Using a standard HD-MEA, we mapped the axonal arbors of 68 neurons in <6 h. The fully automated method can be extended to new generations of HD-MEAs with larger data output and is estimated to provide data of axonal arbors of thousands of neurons within recording sessions of a few hours.
@inbook{Obien2019b,
title = {Large-Scale, High-Resolution Microelectrode Arrays for Interrogation of Neurons and Networks},
author = {Marie Engelene J Obien and Urs Frey},
url = {https://link.springer.com/book/10.1007%2F978-3-030-11135-9#about},
doi = {10.1007/978-3-030-11135-9},
year = {2019},
date = {2019-05-20},
publisher = {Springer},
abstract = {This book provides a comprehensive overview of the incredible advances achieved in the study of in vitro neuronal networks for use in basic and applied research. These cultures of dissociated neurons offer a perfect trade-off between complex experimental models and theoretical modeling approaches giving new opportunities for experimental design but also providing new challenges in data management and interpretation. Topics include culturing methodologies, neuroengineering techniques, stem cell derived neuronal networks, techniques for measuring network activity, and recent improvements in large-scale data analysis. The book ends with a series of case studies examining potential applications of these technologies.},
keywords = {In-Vitro, Neuronal Networks},
pubstate = {published},
tppubtype = {inbook}
}
This book provides a comprehensive overview of the incredible advances achieved in the study of in vitro neuronal networks for use in basic and applied research. These cultures of dissociated neurons offer a perfect trade-off between complex experimental models and theoretical modeling approaches giving new opportunities for experimental design but also providing new challenges in data management and interpretation. Topics include culturing methodologies, neuroengineering techniques, stem cell derived neuronal networks, techniques for measuring network activity, and recent improvements in large-scale data analysis. The book ends with a series of case studies examining potential applications of these technologies.
@article{Mita2019,
title = {Classification of Inhibitory and Excitatory Neurons of Dissociated Cultures Based on Action Potential Waveforms on High-density CMOS Microelectrode Arrays},
author = {Takeshi Mita and Douglas J. Bakkum and Urs Frey and Andreas Hierlemann and Ryohei Kanzaki and Hirokazu Takahashi },
url = {https://www.jstage.jst.go.jp/article/ieejeiss/139/5/139_615/_article/-char/en},
doi = {10.1541/ieejeiss.139.615},
issn = {1348-8155},
year = {2019},
date = {2019-05-01},
journal = {IEEJ Transactions on Electronics, Information and Systems},
volume = {139},
number = {5},
pages = {615-624},
abstract = {Electrophysiological data from in vivo and slice preparations show that inhibitory neurons had shorter duration action potentials (AP) than excitatory neurons. However, this criterion has not yet been established in dissociated cultured neurons. In the present study, we used a high-density CMOS microelectrode array to extracellularly investigate neural signals in primary dissociated cultures of rat neocortex, and we characterized AP waveforms to discriminate excitatory and inhibitory neurons. The CMOS array offers the possibility to acquire comprehensive spatio-temporal neural activity patterns with 11,011 electrodes in about 2×1.75 mm2 area at 20-kHz sampling rate. The waveforms of APs were investigated around cell bodies of neurons, which were classified into either excitatory neurons or inhibitory neurons on the basis of MAP2 and GABA immunostaining images. Consistent with previous in vivo and slice studies, we demonstrated that AP waveforms of inhibitory neurons had shorter durations and recovery time than those of excitatory neurons. The discrimination accuracy was around 0.9 in the receiver-operating characteristics (ROC) analyses. Additionally, taking advantage of non-invasive CMOS recording, we investigated AP waveforms throughout development of cultures. We confirmed that APs were classified into two classes, i.e., putative excitatory and inhibitory neurons, regardless of developmental stages, and found that the duration and recovery time of AP shortened in matured cultures. Thus, AP waveforms have rich information about cell types and developmental stages, which are of worth to elucidate underlying mechanisms of neuronal dynamics in spatio-temporal patterns.},
keywords = {Action Potential, HD-MEA},
pubstate = {published},
tppubtype = {article}
}
Electrophysiological data from in vivo and slice preparations show that inhibitory neurons had shorter duration action potentials (AP) than excitatory neurons. However, this criterion has not yet been established in dissociated cultured neurons. In the present study, we used a high-density CMOS microelectrode array to extracellularly investigate neural signals in primary dissociated cultures of rat neocortex, and we characterized AP waveforms to discriminate excitatory and inhibitory neurons. The CMOS array offers the possibility to acquire comprehensive spatio-temporal neural activity patterns with 11,011 electrodes in about 2×1.75 mm2 area at 20-kHz sampling rate. The waveforms of APs were investigated around cell bodies of neurons, which were classified into either excitatory neurons or inhibitory neurons on the basis of MAP2 and GABA immunostaining images. Consistent with previous in vivo and slice studies, we demonstrated that AP waveforms of inhibitory neurons had shorter durations and recovery time than those of excitatory neurons. The discrimination accuracy was around 0.9 in the receiver-operating characteristics (ROC) analyses. Additionally, taking advantage of non-invasive CMOS recording, we investigated AP waveforms throughout development of cultures. We confirmed that APs were classified into two classes, i.e., putative excitatory and inhibitory neurons, regardless of developmental stages, and found that the duration and recovery time of AP shortened in matured cultures. Thus, AP waveforms have rich information about cell types and developmental stages, which are of worth to elucidate underlying mechanisms of neuronal dynamics in spatio-temporal patterns.
@article{Emmenegger2019,
title = {Technologies to Study Action Potential Propagation With a Focus on HD-MEAs},
author = {Vishalini Emmenegger and Marie Engelene J. Obien and Felix Franke and Andreas Hierlemann},
url = {https://www.frontiersin.org/articles/10.3389/fncel.2019.00159/full},
doi = {10.3389/fncel.2019.00159 },
issn = {1662-5102 },
year = {2019},
date = {2019-04-26},
journal = {Frontiers in Cellular Neuroscience},
volume = {13},
pages = {1-11},
abstract = {Axons convey information in neuronal circuits via reliable conduction of action potentials from the axon initial segment to the presynaptic terminals. Recent experimental findings increasingly evidence that the axonal function is not limited to the simple transmission of action potentials. Advances in subcellular-resolution recording techniques have shown that axons display activity-dependent modulation in spike shape and conduction velocity, which influence synaptic strength and latency. We briefly review, here, how recent methodological developments facilitate the understanding of the axon physiology. We included the three most common methods, i.e. genetically encoded voltage imaging, subcellular patch-clamp and high-density microelectrode arrays (HD-MEAs). We then describe the potential of using HD-MEAs in studying axonal physiology in more detail. Due to their robustness, amenability to high-throughput and high spatiotemporal resolution, HD-MEAs can provide a direct functional electrical readout of single cells and cellular ensembles at subcellular resolution. HD-MEAs can, therefore, be employed in investigating axonal pathologies, the effects of large-scale genomic interventions (e.g., with RNAi or CRISPR) or in compound screenings. A combination of extracellular microelectrode arrays, intracellular microelectrodes and optical imaging may potentially reveal yet unexplored repertoires of axonal functions.},
keywords = {Action Potential, HD-MEA},
pubstate = {published},
tppubtype = {article}
}
Axons convey information in neuronal circuits via reliable conduction of action potentials from the axon initial segment to the presynaptic terminals. Recent experimental findings increasingly evidence that the axonal function is not limited to the simple transmission of action potentials. Advances in subcellular-resolution recording techniques have shown that axons display activity-dependent modulation in spike shape and conduction velocity, which influence synaptic strength and latency. We briefly review, here, how recent methodological developments facilitate the understanding of the axon physiology. We included the three most common methods, i.e. genetically encoded voltage imaging, subcellular patch-clamp and high-density microelectrode arrays (HD-MEAs). We then describe the potential of using HD-MEAs in studying axonal physiology in more detail. Due to their robustness, amenability to high-throughput and high spatiotemporal resolution, HD-MEAs can provide a direct functional electrical readout of single cells and cellular ensembles at subcellular resolution. HD-MEAs can, therefore, be employed in investigating axonal pathologies, the effects of large-scale genomic interventions (e.g., with RNAi or CRISPR) or in compound screenings. A combination of extracellular microelectrode arrays, intracellular microelectrodes and optical imaging may potentially reveal yet unexplored repertoires of axonal functions.
@article{Viswam2019,
title = {Optimal Electrode Size for Multi-Scale Extracellular-Potential Recording From Neuronal Assemblies},
author = {Vijay Viswam and Marie Engelene J. Obien and Felix Franke and Urs Frey and Andreas Hierlemann},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2019.00385/full},
doi = {10.3389/fnins.2019.00385},
issn = {1662-453X},
year = {2019},
date = {2019-04-26},
journal = {Frontiers in Neuroscience},
volume = {13},
abstract = {Advances in microfabrication technology have enabled the production of devices containing arrays of thousands of closely spaced recording electrodes, which afford subcellular resolution of electrical signals in neurons and neuronal networks. Rationalizing the electrode size and configuration in such arrays demands consideration of application-specific requirements and inherent features of the electrodes. Tradeoffs among size, spatial density, sensitivity, noise, attenuation, and other factors are inevitable. Although recording extracellular signals from neurons with planar metal electrodes is fairly well established, the effects of the electrode characteristics on the quality and utility of recorded signals, especially for small, densely packed electrodes, have yet to be fully characterized. Here, we present a combined experimental and computational approach to elucidating how electrode size, and size-dependent parameters, such as impedance, baseline noise, and transmission characteristics, influence recorded neuronal signals. Using arrays containing platinum electrodes of different sizes, we experimentally evaluated the electrode performance in the recording of local-field-potentials (LFPs) and extracellular-action-potentials (EAPs) from the following cell preparations: acute brain slices, dissociated cell cultures, and organotypic slice cultures. Moreover, we simulated the potential spatial decay of point-current sources to investigate signal averaging using known signal sources. We demonstrated that the noise and signal attenuation depend more on the electrode impedance than on electrode size, per se, especially for electrodes < 10 µm in width or diameter to achieve high-spatial-resolution readout. By minimizing electrode impedance in small electrodes (< 10 µm), via surface modification, we could maximize the signal-to-noise ratio to electrically visualize the propagation of axonal EAPs and to isolate single-unit spikes. Due to the large amplitude of LFP signals, recording quality was high and nearly independent of electrode size. These findings should be of value in configuring in vitro and in vivo microelectrode arrays for extracellular recordings with high spatial resolution in various applications.},
keywords = {Neuronal Assemblies},
pubstate = {published},
tppubtype = {article}
}
Advances in microfabrication technology have enabled the production of devices containing arrays of thousands of closely spaced recording electrodes, which afford subcellular resolution of electrical signals in neurons and neuronal networks. Rationalizing the electrode size and configuration in such arrays demands consideration of application-specific requirements and inherent features of the electrodes. Tradeoffs among size, spatial density, sensitivity, noise, attenuation, and other factors are inevitable. Although recording extracellular signals from neurons with planar metal electrodes is fairly well established, the effects of the electrode characteristics on the quality and utility of recorded signals, especially for small, densely packed electrodes, have yet to be fully characterized. Here, we present a combined experimental and computational approach to elucidating how electrode size, and size-dependent parameters, such as impedance, baseline noise, and transmission characteristics, influence recorded neuronal signals. Using arrays containing platinum electrodes of different sizes, we experimentally evaluated the electrode performance in the recording of local-field-potentials (LFPs) and extracellular-action-potentials (EAPs) from the following cell preparations: acute brain slices, dissociated cell cultures, and organotypic slice cultures. Moreover, we simulated the potential spatial decay of point-current sources to investigate signal averaging using known signal sources. We demonstrated that the noise and signal attenuation depend more on the electrode impedance than on electrode size, per se, especially for electrodes < 10 µm in width or diameter to achieve high-spatial-resolution readout. By minimizing electrode impedance in small electrodes (< 10 µm), via surface modification, we could maximize the signal-to-noise ratio to electrically visualize the propagation of axonal EAPs and to isolate single-unit spikes. Due to the large amplitude of LFP signals, recording quality was high and nearly independent of electrode size. These findings should be of value in configuring in vitro and in vivo microelectrode arrays for extracellular recordings with high spatial resolution in various applications.
@article{Russell2019,
title = {Medullary Respiratory Circuit Is Reorganized by a Seasonally-Induced Program in Preparation for Hibernation },
author = {Thomas L. Russell and Jichang Zhang and Michal Okoniewksi and Felix Franke and Sandrine Bichet and Andreas Hierlemann},
url = {https://www.frontiersin.org/article/10.3389/fnins.2019.00376},
doi = {10.3389/fnins.2019.00376 },
issn = {1662-453X},
year = {2019},
date = {2019-04-26},
journal = {Frontiers in Neuroscience },
volume = {13},
abstract = {Deep hibernators go through several cycles of profound drops in body temperature during the winter season, with core temperatures sometimes reaching near freezing. Yet unlike non-hibernating mammals, they can sustain breathing rhythms. The physiological processes that make this possible are still not understood. In this study, we focused on the medullary Ventral Respiratory Column of a facultative hibernator, the Syrian hamster. Using shortened day-lengths, we induced a "winter-adapted" physiological state, which is a prerequisite for hibernation. When recording electrophysiological signals from acute slices in the winter-adapted pre-Bötzinger complex, spike trains showed higher spike rates, amplitudes, complexity, as well as higher temperature sensitivity, suggesting an increase in connectivity and/or synaptic strength during the winter season. We further examined action potential waveforms and found that the depolarization integral, as measured by the area under the curve, is selectively enhanced in winter-adapted animals. This suggests that a shift in the ion handling kinetics is also being induced by the winter-adaptation program. RNA sequencing of respiratory pre-motor neurons, followed by gene set enrichment analysis, revealed differential regulation and splicing in structural, synaptic, and ion handling genes. Splice junction analysis suggested that differential exon usage is occurring in a select subset of ion handling subunits (ATP1A3, KCNC3, SCN1B), and synaptic structure genes (SNCB, SNCG, RAB3A). Our findings show that the hamster respiratory center undergoes a seasonally-cued alteration in electrophysiological properties, likely protecting against respiratory failure at low temperatures.},
keywords = {Respiratory Circuit},
pubstate = {published},
tppubtype = {article}
}
Deep hibernators go through several cycles of profound drops in body temperature during the winter season, with core temperatures sometimes reaching near freezing. Yet unlike non-hibernating mammals, they can sustain breathing rhythms. The physiological processes that make this possible are still not understood. In this study, we focused on the medullary Ventral Respiratory Column of a facultative hibernator, the Syrian hamster. Using shortened day-lengths, we induced a "winter-adapted" physiological state, which is a prerequisite for hibernation. When recording electrophysiological signals from acute slices in the winter-adapted pre-Bötzinger complex, spike trains showed higher spike rates, amplitudes, complexity, as well as higher temperature sensitivity, suggesting an increase in connectivity and/or synaptic strength during the winter season. We further examined action potential waveforms and found that the depolarization integral, as measured by the area under the curve, is selectively enhanced in winter-adapted animals. This suggests that a shift in the ion handling kinetics is also being induced by the winter-adaptation program. RNA sequencing of respiratory pre-motor neurons, followed by gene set enrichment analysis, revealed differential regulation and splicing in structural, synaptic, and ion handling genes. Splice junction analysis suggested that differential exon usage is occurring in a select subset of ion handling subunits (ATP1A3, KCNC3, SCN1B), and synaptic structure genes (SNCB, SNCG, RAB3A). Our findings show that the hamster respiratory center undergoes a seasonally-cued alteration in electrophysiological properties, likely protecting against respiratory failure at low temperatures.
@article{Ronchi2019,
title = {Single-Cell Electrical Stimulation Using CMOS-Based High-Density Microelectrode Arrays},
author = {Silvia Ronchi and Michele Fiscella and Camilla Marchetti and Vijay Viswam and Jan Muller and Urs Frey and Andreas Hierlemann},
url = {https://www.frontiersin.org/article/10.3389/fnins.2019.00208 },
doi = {10.3389/fnins.2019.00208 },
issn = {1662-453X },
year = {2019},
date = {2019-03-13},
journal = {Frontiers in Neuroscience},
volume = {13},
abstract = {Non-invasive electrical stimulation can be used to study and control neural activity in the brain or to alleviate somatosensory dysfunctions. One intriguing prospect is to precisely stimulate individual targeted neurons. Here, we investigated single-neuron current and voltage stimulation in vitro using high-density microelectrode arrays featuring 26’400 bidirectional electrodes at a pitch of 17.5 µm and an electrode area of 5 × 9 µm². We determined optimal waveforms, amplitudes and durations for both stimulation modes. Owing to the high spatial resolution of our arrays and the close proximity of the electrodes to the respective neurons, we were able to stimulate the axon initial segments (AIS) with charges of less than 2 picoCoulombs. This resulted in minimal artifact production and reliable readout of stimulation efficiency directly at the soma of the stimulated cell. Stimulation signals as low as 70 mV or 100 nA,with pulse durations as short as 18 µs, yielded measurable action potential initiation and propagation. We found that the required stimulation signal amplitudes decreased with cell growth and development and that stimulation efficiency did not improve at higher electric fields generated by simultaneous multi-electrode stimulation.},
keywords = {ETH-CMOS-MEA, Stimulation},
pubstate = {published},
tppubtype = {article}
}
Non-invasive electrical stimulation can be used to study and control neural activity in the brain or to alleviate somatosensory dysfunctions. One intriguing prospect is to precisely stimulate individual targeted neurons. Here, we investigated single-neuron current and voltage stimulation in vitro using high-density microelectrode arrays featuring 26’400 bidirectional electrodes at a pitch of 17.5 µm and an electrode area of 5 × 9 µm². We determined optimal waveforms, amplitudes and durations for both stimulation modes. Owing to the high spatial resolution of our arrays and the close proximity of the electrodes to the respective neurons, we were able to stimulate the axon initial segments (AIS) with charges of less than 2 picoCoulombs. This resulted in minimal artifact production and reliable readout of stimulation efficiency directly at the soma of the stimulated cell. Stimulation signals as low as 70 mV or 100 nA,with pulse durations as short as 18 µs, yielded measurable action potential initiation and propagation. We found that the required stimulation signal amplitudes decreased with cell growth and development and that stimulation efficiency did not improve at higher electric fields generated by simultaneous multi-electrode stimulation.
@article{Obien2019,
title = {Accurate signal-source localization in brain slices by means of high-density microelectrode arrays},
author = {Marie Engelene J. Obien and Andreas Hierlemann and Urs Frey},
url = {https://www.nature.com/articles/s41598-018-36895-y},
doi = {10.1038/s41598-018-36895-y},
year = {2019},
date = {2019-01-28},
journal = {Scientific Reports},
volume = {9},
number = {788},
abstract = {Extracellular recordings by means of high-density microelectrode arrays (HD-MEAs) have become a powerful tool to resolve subcellular details of single neurons in active networks grown from dissociated cells. To extend the application of this technology to slice preparations, we developed models describing how extracellular signals, produced by neuronal cells in slices, are detected by microelectrode arrays. The models help to analyze and understand the electrical-potential landscape in an in vitro HD-MEA-recording scenario based on point-current sources. We employed two modeling schemes, (i) a simple analytical approach, based on the method of images (MoI), and (ii) an approach, based on finite-element methods (FEM). We compared and validated the models with large-scale, high-spatiotemporal-resolution recordings of slice preparations by means of HD-MEAs. We then developed a model-based localization algorithm and compared the performance of MoI and FEM models. Both models provided accurate localization results and a comparable and negligible systematic error, when the point source was in saline, a condition similar to cell-culture experiments. Moreover, the relative random error in the x-y-z-localization amounted only up to 4.3% for z-distances up to 200 μm from the HD-MEA surface. In tissue, the systematic errors of both, MoI and FEM models were significantly higher, and a pre-calibration was required. Nevertheless, the FEM values proved to be closer to the tissue experimental results, yielding 5.2 μm systematic mean error, compared to 22.0 μm obtained with MoI. These results suggest that the medium volume or “saline height”, the brain slice thickness and anisotropy, and the location of the reference electrode, which were included in the FEM model, considerably affect the extracellular signal and localization performance, when the signal source is at larger distance to the array. After pre-calibration, the relative random error of the z-localization in tissue was only 3% for z-distances up to 200 μm. We then applied the model and related detailed understanding of extracellular recordings to achieve an electrically-guided navigation of a stimulating micropipette, solely based on the measured HD-MEA signals, and managed to target spontaneously active neurons in an acute brain slice for electroporation.},
keywords = {Brain Slice},
pubstate = {published},
tppubtype = {article}
}
Extracellular recordings by means of high-density microelectrode arrays (HD-MEAs) have become a powerful tool to resolve subcellular details of single neurons in active networks grown from dissociated cells. To extend the application of this technology to slice preparations, we developed models describing how extracellular signals, produced by neuronal cells in slices, are detected by microelectrode arrays. The models help to analyze and understand the electrical-potential landscape in an in vitro HD-MEA-recording scenario based on point-current sources. We employed two modeling schemes, (i) a simple analytical approach, based on the method of images (MoI), and (ii) an approach, based on finite-element methods (FEM). We compared and validated the models with large-scale, high-spatiotemporal-resolution recordings of slice preparations by means of HD-MEAs. We then developed a model-based localization algorithm and compared the performance of MoI and FEM models. Both models provided accurate localization results and a comparable and negligible systematic error, when the point source was in saline, a condition similar to cell-culture experiments. Moreover, the relative random error in the x-y-z-localization amounted only up to 4.3% for z-distances up to 200 μm from the HD-MEA surface. In tissue, the systematic errors of both, MoI and FEM models were significantly higher, and a pre-calibration was required. Nevertheless, the FEM values proved to be closer to the tissue experimental results, yielding 5.2 μm systematic mean error, compared to 22.0 μm obtained with MoI. These results suggest that the medium volume or “saline height”, the brain slice thickness and anisotropy, and the location of the reference electrode, which were included in the FEM model, considerably affect the extracellular signal and localization performance, when the signal source is at larger distance to the array. After pre-calibration, the relative random error of the z-localization in tissue was only 3% for z-distances up to 200 μm. We then applied the model and related detailed understanding of extracellular recordings to achieve an electrically-guided navigation of a stimulating micropipette, solely based on the measured HD-MEA signals, and managed to target spontaneously active neurons in an acute brain slice for electroporation.
@article{Dudina2019,
title = {Monolithic CMOS sensor platform featuring an array of 9’216 carbon-nanotube-sensor elements and low-noise, wide-bandwidth and wide-dynamic-range readout circuitry},
author = {Alexandra Dudina and Florent Seichepine and Yihui Chen and and Alexander Stettler and Andreas Hierlemann and and Urs Frey},
url = {https://www.sciencedirect.com/science/article/pii/S0925400518317672?via%3Dihub},
doi = {10.1016/j.snb.2018.10.004},
year = {2019},
date = {2019-01-15},
journal = {Sensors and Actuators B: Chemical},
volume = {279},
pages = {255-266},
abstract = {We present the design and characterization of a monolithic complementary metal–oxide–semiconductor (CMOS) biosensor platform comprising of a switch-matrix-based array of 9′216 carbon nanotube field-effect transistors (CNTFETs) and associated readout circuitry. The switch-matrix allows for flexible selection and simultaneous routing of 96 sensor elements to the corresponding readout channels. A low-noise, wide-bandwidth, wide-dynamic-range transimpedance continuous-time amplifier architecture has been implemented to facilitate resistance measurements in the range between 50 kΩ and 1 GΩ at a bandwidth of up to 1 MHz. The achieved accuracy of the resistance measurements over the whole range is 4%. The system has been successfully fabricated and tested and shows a noise performance equal to 2.14 pArms at a bandwidth of 1 kHz and 0.84 nArms at a bandwidth of 1 MHz. A batch integration of the CNTFETs has been achieved by using a dielectrophoresis (DEP)–based manipulation technique. The current-voltage curves of CNTFETs have been acquired, and the sensing capabilities of the system have been demonstrated by recording resistance changes of CNTFETs upon exposure to solutions with different pH values and different concentrations of NaCl. The smallest resolvable concentrations for the respective analytes were estimated to amount to 0.025 pH-units and 4 mM NaCl.},
keywords = {ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
We present the design and characterization of a monolithic complementary metal–oxide–semiconductor (CMOS) biosensor platform comprising of a switch-matrix-based array of 9′216 carbon nanotube field-effect transistors (CNTFETs) and associated readout circuitry. The switch-matrix allows for flexible selection and simultaneous routing of 96 sensor elements to the corresponding readout channels. A low-noise, wide-bandwidth, wide-dynamic-range transimpedance continuous-time amplifier architecture has been implemented to facilitate resistance measurements in the range between 50 kΩ and 1 GΩ at a bandwidth of up to 1 MHz. The achieved accuracy of the resistance measurements over the whole range is 4%. The system has been successfully fabricated and tested and shows a noise performance equal to 2.14 pArms at a bandwidth of 1 kHz and 0.84 nArms at a bandwidth of 1 MHz. A batch integration of the CNTFETs has been achieved by using a dielectrophoresis (DEP)–based manipulation technique. The current-voltage curves of CNTFETs have been acquired, and the sensing capabilities of the system have been demonstrated by recording resistance changes of CNTFETs upon exposure to solutions with different pH values and different concentrations of NaCl. The smallest resolvable concentrations for the respective analytes were estimated to amount to 0.025 pH-units and 4 mM NaCl.
@article{Shadmani2019b,
title = {Stimulation and Artifact-suppression Techniques for in-vitro High-density Microelectrode Array Systems.},
author = {Amir Shadmani and Vijay Viswam and Yihui Chen and Raziyeh Bounik and Jelena Dragas and Milos Radivojevic and Sydney Geissler and Sergey Sitnikov and Jan Muller and Andreas Hierlemann },
url = {https://ieeexplore.ieee.org/document/8599003},
doi = {10.1109/TBME.2018.2890530},
year = {2019},
date = {2019-01-01},
journal = {IEEE Transactions on Biomedical Engineering},
abstract = {We present novel voltage stimulation buffers with controlled output current, along with recording circuits featuring adjustable high-pass cut-off filtering to perform efficient stimulation while actively suppressing stimulation artifacts in high-density microelectrode arrays. Owing to the dense packing and close proximity of the electrodes in such systems, a stimulation through one electrode can cause large electrical artifacts on neighboring electrodes that easily saturate the corresponding recording amplifiers. To suppress such artifacts, the high-pass corner frequencies of all available 2048 recording channels can be raised from several Hz to several kHz by applying a "soft-reset" or pole-shifting technique. With the implemented artifact suppression technique, the saturation time of the recording circuits, connected to electrodes in immediate vicinity to the stimulation site, could be reduced to less than 150μs. For the stimulation buffer, we developed a circuit, which can operate in two modes: either control of only the stimulation voltage, or control of current and voltage during stimulation. The voltage-only controlled mode employs a local common-mode feedback operational transconductance amplifier with a near rail-to-rail input/output range, suitable for driving high capacitive loads. The current/voltage controlled mode is based on a positive current conveyor generating adjustable output currents, while its upper and lower output voltages are limited by two feedback loops. The current/voltage controlled circuit can generate stimulation pulses up to 30 μA with less than ±0.1% linearity error in the low-current mode, and up to 300 μA with less than ±0.2% linearity error in the high-current mode.},
keywords = {ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
We present novel voltage stimulation buffers with controlled output current, along with recording circuits featuring adjustable high-pass cut-off filtering to perform efficient stimulation while actively suppressing stimulation artifacts in high-density microelectrode arrays. Owing to the dense packing and close proximity of the electrodes in such systems, a stimulation through one electrode can cause large electrical artifacts on neighboring electrodes that easily saturate the corresponding recording amplifiers. To suppress such artifacts, the high-pass corner frequencies of all available 2048 recording channels can be raised from several Hz to several kHz by applying a "soft-reset" or pole-shifting technique. With the implemented artifact suppression technique, the saturation time of the recording circuits, connected to electrodes in immediate vicinity to the stimulation site, could be reduced to less than 150μs. For the stimulation buffer, we developed a circuit, which can operate in two modes: either control of only the stimulation voltage, or control of current and voltage during stimulation. The voltage-only controlled mode employs a local common-mode feedback operational transconductance amplifier with a near rail-to-rail input/output range, suitable for driving high capacitive loads. The current/voltage controlled mode is based on a positive current conveyor generating adjustable output currents, while its upper and lower output voltages are limited by two feedback loops. The current/voltage controlled circuit can generate stimulation pulses up to 30 μA with less than ±0.1% linearity error in the low-current mode, and up to 300 μA with less than ±0.2% linearity error in the high-current mode.
@article{Bakkum2018b,
title = {The Axon Initial Segment is the Dominant Contributor to the Neuron's Extracellular Electrical Potential Landscape},
author = {Douglas J. Bakkum and Marie Engelene J. Obien and Milos Radivojevic and David Jäckel and Urs Frey and Hirokazu Takahashi and Andreas Hierlemann},
url = {https://onlinelibrary.wiley.com/doi/full/10.1002/adbi.201800308},
doi = {10.1002/adbi.201800308},
year = {2018},
date = {2018-11-29},
journal = {Advanced Biosystems},
abstract = {Extracellular voltage fields, produced by a neuron's action potentials, provide a widely used means for studying neuronal and neuronal‐network function. The neuron's soma and dendrites are thought to drive the extracellular action potential (EAP) landscape, while the axon's contribution is usually considered less important. However, by recording voltages of single neurons in dissociated rat cortical cultures and Purkinje cells in acute mouse cerebellar slices through hundreds of densely packed electrodes, it is found, instead, that the axon initial segment dominates the measured EAP landscape, and, surprisingly, the soma only contributes to a minor extent. As expected, the recorded dominant signal has negative polarity (charge entering the cell) and initiates at the distal end. Interestingly, signals with positive polarity (charge exiting the cell) occur near some but not all dendritic branches and occur after a delay. Such basic knowledge about which neuronal compartments contribute to the extracellular voltage landscape is important for interpreting results from all electrical readout schemes. Finally, initiation of the electrical activity at the distal end of the axon initial segment (AIS) and subsequent spreading into the axon proper and backward through the proximal AIS toward the soma are confirmed. The corresponding extracellular waveforms across different neuronal compartments could be tracked.},
keywords = {ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
Extracellular voltage fields, produced by a neuron's action potentials, provide a widely used means for studying neuronal and neuronal‐network function. The neuron's soma and dendrites are thought to drive the extracellular action potential (EAP) landscape, while the axon's contribution is usually considered less important. However, by recording voltages of single neurons in dissociated rat cortical cultures and Purkinje cells in acute mouse cerebellar slices through hundreds of densely packed electrodes, it is found, instead, that the axon initial segment dominates the measured EAP landscape, and, surprisingly, the soma only contributes to a minor extent. As expected, the recorded dominant signal has negative polarity (charge entering the cell) and initiates at the distal end. Interestingly, signals with positive polarity (charge exiting the cell) occur near some but not all dendritic branches and occur after a delay. Such basic knowledge about which neuronal compartments contribute to the extracellular voltage landscape is important for interpreting results from all electrical readout schemes. Finally, initiation of the electrical activity at the distal end of the axon initial segment (AIS) and subsequent spreading into the axon proper and backward through the proximal AIS toward the soma are confirmed. The corresponding extracellular waveforms across different neuronal compartments could be tracked.
@article{Viswam2018,
title = {Impedance Spectroscopy and Electrophysiological Imaging of Cells With a High-Density CMOS Microelectrode Array System},
author = {Vijay Viswam and Raziyeh Bounik and Amir Shadmani and Jelena Dragas and Cedar Urwyler and Julia Alicia Boos and Marie Engelene J. Obien and Jan Muller and Yihui Chen and Andreas Hierlemann},
url = {https://ieeexplore.ieee.org/document/8532304},
doi = {10.1109/TBCAS.2018.2881044},
issn = {1932-4545},
year = {2018},
date = {2018-11-12},
journal = {IEEE Transactions on Biomedical Circuits and Systems},
volume = {12},
number = {6},
pages = {1356-1368},
abstract = {A monolithic multi-functional CMOS microelectrode array system was developed that enables label-free electrochemical impedance spectroscopy of cells in vitro at high spatiotemporal resolution. The electrode array includes 59,760 platinum microelectrodes, densely packed within a 4.5 mm × 2.5 mm sensing region at a pitch of 13.5 μm. A total of 32 on-chip lock-in amplifiers can be used to measure the impedance of any arbitrarily chosen subset of electrodes in the array. A sinusoidal voltage, generated by an on-chip waveform generator with a frequency range from 1 Hz to 1 MHz, was applied to the reference electrode. The sensing currents through the selected recording electrodes were amplified, demodulated, filtered, and digitized to obtain the magnitude and phase information of the respective impedances. The circuitry consumes only 412 μW at 3.3 V supply voltage and occupies only 0.1 mm 2 , for each channel. The system also included 2048 extracellular action-potential recording channels on the same chip. Proof of concept measurements of electrical impedance imaging and electrophysiology recording of cardiac cells and brain slices are demonstrated in this paper. Optical and impedance images showed a strong correlation.},
keywords = {HD-MEA},
pubstate = {published},
tppubtype = {article}
}
A monolithic multi-functional CMOS microelectrode array system was developed that enables label-free electrochemical impedance spectroscopy of cells in vitro at high spatiotemporal resolution. The electrode array includes 59,760 platinum microelectrodes, densely packed within a 4.5 mm × 2.5 mm sensing region at a pitch of 13.5 μm. A total of 32 on-chip lock-in amplifiers can be used to measure the impedance of any arbitrarily chosen subset of electrodes in the array. A sinusoidal voltage, generated by an on-chip waveform generator with a frequency range from 1 Hz to 1 MHz, was applied to the reference electrode. The sensing currents through the selected recording electrodes were amplified, demodulated, filtered, and digitized to obtain the magnitude and phase information of the respective impedances. The circuitry consumes only 412 μW at 3.3 V supply voltage and occupies only 0.1 mm 2 , for each channel. The system also included 2048 extracellular action-potential recording channels on the same chip. Proof of concept measurements of electrical impedance imaging and electrophysiology recording of cardiac cells and brain slices are demonstrated in this paper. Optical and impedance images showed a strong correlation.
Presenting measurements of neuronal preparations with a novel CMOS-based microelectrode array at high-spatiotemporal-resolution on subcellular, cellular, and network level.
J. Müller, M. Ballini, P. Livi, Y. Chen, M. Radivojevic, A. Shadmani, V. Viswam, I. L. Jones, M. Fiscella, R. Diggelmann, A. Stettler, U. Frey, D. J. Bakkum, and A. Hierlemann, “High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels,” Lab Chip, vol. 15, no. 13, pp. 2767–2780, May 2015.
Reviewing the current understanding of microelectrode signals and the techniques for analyzing them, with focus on the ongoing advancements in microelectrode technology (in vivo and in vitro) and recent advanced microelectrode array measurement methods that facilitate the understanding of single neurons and network function.
M. E. J. Obien, K. Deligkaris, T. Bullmann, D. J. Bakkum, and U. Frey, “Revealing Neuronal Function through Microelectrode Array Recordings,” Front. Neurosci., 8:423, Jan 2015.
A high-resolution CMOS-based microelectrode array featuring 1,024 low-noise readout channels, 26,400 electrodes at a density of 3,265 electrodes per mm2, including on-chip 10bit ADCs and consuming only 75 mW.
M. Ballini, J. Muller, P. Livi, Y. Chen, U. Frey, A. Stettler, A. Shadmani, V. Viswam, I. L. Jones, D. Jackel, M. Radivojevic, M. K. Lewandowska, W. Gong, M. Fiscella, D. J. Bakkum, F. Heer, and A. Hierlemann, “A 1024-Channel CMOS Microelectrode Array With 26,400 Electrodes for Recording and Stimulation of Electrogenic Cells In Vitro,” IEEE Journal of Solid-State Circuits, vol. 49, no. 11, pp. 2705-2719, 2014.
Demonstrating a method to electrically visualize action potential propagation on axons and revealing
large variations in velocity.
D. J. Bakkum, U. Frey, M. Radivojevic, T. L. Russell, J. Muller, M. Fiscella, H. Takahashi, and A. Hierlemann, “Tracking axonal action potential propagation on a high-density microelectrode array across hundreds of sites,” Nature Communications, 4:2181, Jul 2013.
Recording and modeling extracellular action potentials of Purkinje cells at subcellular resolution.
U. Frey, U. Egert, F. Heer, S. Hafizovic, and A. Hierlemann, “Microelectronic System for High-Resolution Mapping of Extracellular Electric Fields Applied to Brain Slices,” Biosensors and Bioelectronics, vol. 24, no. 7, pp. 2191-2198, 2009.
Controlling BMP-2 expression to modulate the electrophysiological properties of cardiomyocytes using an HD-MEA for detailed monitoring.
C. D. Sanchez-Bustamante, U. Frey, J. M. Kelm, A. Hierlemann, and M. Fussenegger,
“Modulation of Cardiomyocyte Electrical Properties Using Regulated Bone Morphogenetic Protein-2 Expression,” Tissue Engineering Part A, vol. 14, no. 12, pp. 1969-1988, 2008.
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