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日本語MaxOne High-Density Microelectrode Array (HD-MEA) System
Versatility to Empower Your Research
MaxOne – Powerful single-well high-density microelectrode array system for recording and stimulating your cells.
Key Features
High-resolution and high-quality data while tracking dynamic changes at cellular, subcellular and network levels.
Smallest signals capture (uV) thanks to low-noise recording channels and high electrode density.
Compactly built, MaxOne Recording Unit can be flexibly installed in various environments and is compatible with other devices for both cultured samples and acute tissues.
Optimized recordings strategies to analyze the entire culture at individual neuronal levels, increasing data reproducibility and statistical power.
Cell development, maturation, or compound effects assess by performing longitudinal experiments over the course of days, weeks, and months.
Non-invasive and label-free recordings, eliminating any potential side effects associated with the use of dyes and prolonged exposure to light.
Product Overview
MaxWell Biosystems’ MaxOne is a CMOS-based HD-MEA, an electrical imaging system for neuroscience, drug discovery, and cell assessment applications. MaxOne captures high-quality signals at subcellular resolution from long-term culture experiments and acute tissue experiments (e.g., brain slices, retina).
3’625 Electrodes/mm2
Low-Noise Readouts
Flexible Electrical Stimulation
Network level
Cellular level
Subcellular level
MaxOne HD-MEA system can be flexibly installed in diverse environments. For instance, MaxOne Recording Unit can operate long-term inside cell-culture incubators, and can be integrated with perfusion systems, enabling users to perform acute tissue recordings. Additionally, the system is compatible with other devices, such as being placed under an upright microscope for imaging and microscopy purposes, and integrated with tissue holders for acute tissue experiments.
Learn About MaxOne AccessoriesAll consumable MaxOne Chips share the same core features of our HD-MEA technology but differs in ways that allows them to be more suitable for cultured or acute samples.
Learn About MaxOne Chips
MaxOne System
| MaxOne System Features | ||
|---|---|---|
| Components | Recording Unit Hub | |
| System status indicator | LED | |
| Dimension (L x W x H) | Recording Unit: 150 x 95 x 25 mm3 Hub: 185 x 280 x 90 mm3 | |
| Incubator friendly | Yes, for the Recording Unit |
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Publications Featuring the MaxOne
 | Vacca, F; Galluzzi, F; Blanco-Formoso, M; Gianiorio, T; Fazioa, De A F; Tantussi, F; Stürmer, S; Haq, W; Zrenner, E; Chaffio, A; lC. Joffrois,; Picaud, S; Benfenati, F; Angelis, De F; Colombo, E Solid-State Nanopores for Spatially Resolved Chemical Neuromodulation Journal Article Nano Letters , 2024. @article{Vacca2024, title = {Solid-State Nanopores for Spatially Resolved Chemical Neuromodulation}, author = {F. Vacca and F. Galluzzi and M. Blanco-Formoso and T. Gianiorio and A.F. De Fazioa and F. Tantussi and S. Stürmer and W. Haq and E. Zrenner and A. Chaffio and lC. Joffrois and S. Picaud and F. Benfenati and F. De Angelis and E. Colombo}, url = {https://pubs.acs.org/doi/10.1021/acs.nanolett.4c02604}, doi = {10.1021/acs.nanolett.4c02604}, year = {2024}, date = {2024-11-19}, journal = {Nano Letters }, abstract = {Most neural prosthetic devices are based on electrical stimulation, although the modulation of neuronal activity by a localized chemical delivery would better mimic physiological synaptic machinery. In the past decade, various drug delivery approaches attempted to emulate synaptic transmission, although they were hampered by poor retention of their cargo while reaching the target destination, low spatial resolution, and poor biocompatibility and stability of the materials involved. Here, we propose a planar solid-state device for multisite neurotransmitter translocation at the nanoscale consisting of a nanopatterned ceramic membrane connected to a reservoir designed to store neurotransmitters. We achieved diffusion-mediated glutamate stimulation of primary neurons, while we showed the feasibility to translocate other molecules through the pores by either pressure or diffusion, proving the versatility of the proposed technology. Finally, the system proved to be a promising neuronal stimulation interface in mice and nonhuman primates ex vivo, paving the way toward a biomimetic chemical stimulation in neural prosthetics and brain machine interfaces.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Most neural prosthetic devices are based on electrical stimulation, although the modulation of neuronal activity by a localized chemical delivery would better mimic physiological synaptic machinery. In the past decade, various drug delivery approaches attempted to emulate synaptic transmission, although they were hampered by poor retention of their cargo while reaching the target destination, low spatial resolution, and poor biocompatibility and stability of the materials involved. Here, we propose a planar solid-state device for multisite neurotransmitter translocation at the nanoscale consisting of a nanopatterned ceramic membrane connected to a reservoir designed to store neurotransmitters. We achieved diffusion-mediated glutamate stimulation of primary neurons, while we showed the feasibility to translocate other molecules through the pores by either pressure or diffusion, proving the versatility of the proposed technology. Finally, the system proved to be a promising neuronal stimulation interface in mice and nonhuman primates ex vivo, paving the way toward a biomimetic chemical stimulation in neural prosthetics and brain machine interfaces. |
 | Andrews, John P; Geng, Jinghui; Voitiuk, Kateryna; Elliott, Matthew A T; Shin, David; Robbins, Ash; Spaeth, Alex; Wang, Albert; Li, Lin; Solis, Daniel; Keefe, Matthew G; Sevetson, Jessica L; de Jesús, Julio Rivera A; Donohue, Kevin C; Larson, Hanh H; Ehrlich, Drew; Auguste, Kurtis I; Salama, Sofie; Sohal, Vikaas; Sharf, Tal; Haussler, David; Cadwell, Cathryn R; Schaffer, David V; Chang, Edward F; Teodorescu, Mircea; Nowakowski, Tomasz Jan Multimodal Evaluation of Network Activity and Optogenetic Interventions in Human Hippocampal Slices Journal Article Nature Neuroscience , 2024. @article{Andrews2024, title = {Multimodal Evaluation of Network Activity and Optogenetic Interventions in Human Hippocampal Slices}, author = {John P. Andrews and Jinghui Geng and Kateryna Voitiuk and Matthew A. T. Elliott and David Shin and Ash Robbins and Alex Spaeth and Albert Wang and Lin Li and Daniel Solis and Matthew G. Keefe and Jessica L. Sevetson and Julio A. Rivera de Jesús and Kevin C. Donohue and H. Hanh Larson and Drew Ehrlich and Kurtis I. Auguste and Sofie Salama and Vikaas Sohal and Tal Sharf and David Haussler and Cathryn R. Cadwell and David V. Schaffer and Edward F. Chang and Mircea Teodorescu and Tomasz Jan Nowakowski}, url = {https://www.nature.com/articles/s41593-024-01782-5}, doi = {10.1038/s41593-024-01782-5}, year = {2024}, date = {2024-11-15}, journal = {Nature Neuroscience }, abstract = {Seizures are made up of the coordinated activity of networks of neurons, suggesting that control of neurons in the pathologic circuits of epilepsy could allow for control of the disease. Optogenetics has been effective at stopping seizure-like activity in non-human disease models by increasing inhibitory tone or decreasing excitation, although this effect has not been shown in human brain tissue. Many of the genetic means for achieving c hannelrhodopsin expression in non-human models are not possible in humans, and vector-mediated methods are susceptible to species-specific tropism that may affect translational potential. Here we demonstrate adeno-associated virus–mediated, optogenetic reductions in network firing rates of human hippocampal slices recorded on high-density microelectrode arrays under several hyperactivity-provoking conditions. This platform can serve to bridge the gap between human and animal studies by exploring genetic interventions on network activity in human brain tissue.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Seizures are made up of the coordinated activity of networks of neurons, suggesting that control of neurons in the pathologic circuits of epilepsy could allow for control of the disease. Optogenetics has been effective at stopping seizure-like activity in non-human disease models by increasing inhibitory tone or decreasing excitation, although this effect has not been shown in human brain tissue. Many of the genetic means for achieving c hannelrhodopsin expression in non-human models are not possible in humans, and vector-mediated methods are susceptible to species-specific tropism that may affect translational potential. Here we demonstrate adeno-associated virus–mediated, optogenetic reductions in network firing rates of human hippocampal slices recorded on high-density microelectrode arrays under several hyperactivity-provoking conditions. This platform can serve to bridge the gap between human and animal studies by exploring genetic interventions on network activity in human brain tissue. |
 | Elliott, Matthew A T; Andrews, John P; van der Molen, Tjitse; Geng, Jinghui; Spaeth, Alex; Voituik, Kateryna; Core, Cordero; Gillespie, Thomas; Sinervo, Ari; Parks, David F; Robbins, Ash; Solís, Daniel; Chang, Edward F; Nowakowski, Tomasz Jan; Teodorescu, Mircea; Haussler, David; Sharf, Tal Pathological Microcircuits Initiate Epileptiform Events in Patient Hippocampal Slices Journal Article bioRxiv, 2024. @article{Elliott2024, title = {Pathological Microcircuits Initiate Epileptiform Events in Patient Hippocampal Slices}, author = {Matthew A.T. Elliott and John P. Andrews and Tjitse van der Molen and Jinghui Geng and Alex Spaeth and Kateryna Voituik and Cordero Core and Thomas Gillespie and Ari Sinervo and David F. Parks and Ash Robbins and Daniel Solís and Edward F. Chang and Tomasz Jan Nowakowski and Mircea Teodorescu and David Haussler and Tal Sharf}, url = {https://www.biorxiv.org/content/10.1101/2024.11.13.623525v1}, doi = {https://doi.org/10.1101/2024.11.13.623525}, year = {2024}, date = {2024-11-14}, journal = {bioRxiv}, abstract = {How seizures begin at the level of microscopic neural circuits remains unknown. High-density CMOS microelectrode arrays provide a new avenue for investigating neuronal network activity, with unprecedented spatial and temporal resolution. We use high-density CMOS-based microelectrode arrays to probe the network activity of human hippocampal brain slices from six patients with mesial temporal lobe epilepsy in the presence of hyperactivity promoting media. Two slices from the dentate gyrus exhibited epileptiform activity in the presence of low magnesium media with kainic acid. Both slices displayed an electrophysiological phenotype consistent with a reciprocally connected circuit, suggesting a recurrent feedback loop is a key driver of epileptiform onset. Larger prospective studies are needed, but these findings have the potential to elucidate the network signals underlying the initiation of seizure behavior.}, keywords = {}, pubstate = {published}, tppubtype = {article} } How seizures begin at the level of microscopic neural circuits remains unknown. High-density CMOS microelectrode arrays provide a new avenue for investigating neuronal network activity, with unprecedented spatial and temporal resolution. We use high-density CMOS-based microelectrode arrays to probe the network activity of human hippocampal brain slices from six patients with mesial temporal lobe epilepsy in the presence of hyperactivity promoting media. Two slices from the dentate gyrus exhibited epileptiform activity in the presence of low magnesium media with kainic acid. Both slices displayed an electrophysiological phenotype consistent with a reciprocally connected circuit, suggesting a recurrent feedback loop is a key driver of epileptiform onset. Larger prospective studies are needed, but these findings have the potential to elucidate the network signals underlying the initiation of seizure behavior. |
| Geng, Jinghui; Voitiuk, Kateryna; Parks, David F; Robbins, Ash; Alex Spaeth, ; Sevetson, Jessica L; Hernandez, Sebastian; Schweiger, Hunter E; Andrews, John P; Seiler, Spencer T; Elliott, Matthew A T; Chang, Edward F; Nowakowski, Tomasz J; Currie, Rob; Mostajo-Radji, Mohammed A; Haussler, David; Sharf, Tal; Salama, Sofie R; Teodorescu, Mircea Multiscale Cloud-based Pipeline for Neuronal Electrophysiology Analysis and Visualization Journal Article bioRxiv, 2024. @article{Geng2024, title = {Multiscale Cloud-based Pipeline for Neuronal Electrophysiology Analysis and Visualization}, author = {Jinghui Geng and Kateryna Voitiuk and David F. Parks and Ash Robbins and Alex Spaeth and Jessica L. Sevetson and Sebastian Hernandez and Hunter E. Schweiger and John P. Andrews and Spencer T. Seiler and Matthew A.T. Elliott and Edward F. Chang and Tomasz J. Nowakowski and Rob Currie and Mohammed A. Mostajo-Radji and David Haussler and Tal Sharf and Sofie R. Salama and Mircea Teodorescu}, url = {https://www.biorxiv.org/content/10.1101/2024.11.14.623530v1}, doi = {https://doi.org/10.1101/2024.11.14.623530}, year = {2024}, date = {2024-11-14}, journal = {bioRxiv}, abstract = {Electrophysiology offers a high-resolution method for real-time measurement of neural activity. The vast amount of data generated requires efficient storage and sophisticated processing to extract neural function and network dynamics. However, analysis is often challenging due to the need for multiple software tools with different runtime dependencies. Longitudinal recordings from high-density microelectrode arrays (HD-MEAs) can be of considerable size for local storage, complicating data management, sharing, and backup. To address these challenges, we developed an open-source cloud-based pipeline to store, analyze, and visualize neuronal electrophysiology recordings from HD-MEAs. This pipeline is dependency agnostic by utilizing cloud storage, cloud computing resources, and an Internet of Things messaging protocol. We containerized the analysis algorithms to serve as scalable and flexible building blocks within the pipeline. We designed graphical user interfaces and command line tools to remove the requirement of programming skills. The interactive visualizations provide multi-modality information on various neuronal features. This cloud-based pipeline is an efficient solution for electrophysiology data processing, the limitations of local software tools, and storage constraints. It simplifies the electrophysiology data analysis process and facilitates understanding neuronal activity. In this paper, we applied this pipeline on two types of cultures, cortical organoids and ex vivo brain slice recordings.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Electrophysiology offers a high-resolution method for real-time measurement of neural activity. The vast amount of data generated requires efficient storage and sophisticated processing to extract neural function and network dynamics. However, analysis is often challenging due to the need for multiple software tools with different runtime dependencies. Longitudinal recordings from high-density microelectrode arrays (HD-MEAs) can be of considerable size for local storage, complicating data management, sharing, and backup. To address these challenges, we developed an open-source cloud-based pipeline to store, analyze, and visualize neuronal electrophysiology recordings from HD-MEAs. This pipeline is dependency agnostic by utilizing cloud storage, cloud computing resources, and an Internet of Things messaging protocol. We containerized the analysis algorithms to serve as scalable and flexible building blocks within the pipeline. We designed graphical user interfaces and command line tools to remove the requirement of programming skills. The interactive visualizations provide multi-modality information on various neuronal features. This cloud-based pipeline is an efficient solution for electrophysiology data processing, the limitations of local software tools, and storage constraints. It simplifies the electrophysiology data analysis process and facilitates understanding neuronal activity. In this paper, we applied this pipeline on two types of cultures, cortical organoids and ex vivo brain slice recordings. |
 | Kobayashi, Toki; Shimba, Kenta; Narumi, Taiyo; Asahina, Takahiro; Kotani, Kiyoshi; Jimbo, Yasuhiko Revealing Single-Neuron and Network-Activity Interaction by Combining High-Density Microelectrode Array and Optogenetics Journal Article Nature Communications , 2024. @article{Kobayashi2024, title = {Revealing Single-Neuron and Network-Activity Interaction by Combining High-Density Microelectrode Array and Optogenetics}, author = {Toki Kobayashi and Kenta Shimba and Taiyo Narumi and Takahiro Asahina and Kiyoshi Kotani and Yasuhiko Jimbo }, url = {https://www.nature.com/articles/s41467-024-53505-w}, doi = {10.1038/s41467-024-53505-w}, year = {2024}, date = {2024-11-11}, journal = {Nature Communications }, abstract = {The synchronous activity of neuronal networksisconsideredcrucialforbrain function. However, the interaction between single-neuron activity and network-wide activity remains poorly understood. This study explored this interaction within cultured networks of rat cortical neurons. Employing a combination of high-density microelectrode array recording and optogenetic stimulation, we established an experimental setup enabling simultaneous recording and stimulation at a precise single-neuron level that can be scaled to the level of the whole network. Leveraging our system, we identified a network burst-dependent response change in single neurons, providing a possible mechanism for the network-burst-dependent loss of information within the network and consequent cognitive impairment during epileptic seizures. Additionally, we directly recorded a leader neuron initiating a spontaneous network burst and characterized its firing properties, indicating that the bursting activity of hub neurons in the brain can initiate network-wide activity. Our study offers valuable insights into brain networks characterized by a combination of bottom-up self-organization and top-down regulation.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The synchronous activity of neuronal networksisconsideredcrucialforbrain function. However, the interaction between single-neuron activity and network-wide activity remains poorly understood. This study explored this interaction within cultured networks of rat cortical neurons. Employing a combination of high-density microelectrode array recording and optogenetic stimulation, we established an experimental setup enabling simultaneous recording and stimulation at a precise single-neuron level that can be scaled to the level of the whole network. Leveraging our system, we identified a network burst-dependent response change in single neurons, providing a possible mechanism for the network-burst-dependent loss of information within the network and consequent cognitive impairment during epileptic seizures. Additionally, we directly recorded a leader neuron initiating a spontaneous network burst and characterized its firing properties, indicating that the bursting activity of hub neurons in the brain can initiate network-wide activity. Our study offers valuable insights into brain networks characterized by a combination of bottom-up self-organization and top-down regulation. |
 | Bertacchi, Michele; Maharaux, Gwendoline; Loubat, Agnès; Jung, Matthieu; Studer, Michèle FGF8-Mediated Gene Regulation Affects Regional Identity in Human Cerebral Organoids Journal Article eLife , 2024. @article{Bertacchi2024, title = {FGF8-Mediated Gene Regulation Affects Regional Identity in Human Cerebral Organoids}, author = {Michele Bertacchi and Gwendoline Maharaux and Agnès Loubat and Matthieu Jung and Michèle Studer}, url = {https://elifesciences.org/articles/98096#content}, doi = {https://doi.org/10.7554/eLife.98096}, year = {2024}, date = {2024-11-01}, journal = {eLife }, abstract = {The morphogen FGF8 establishes graded positional cues imparting regional cellular responses via modulation of early target genes. The roles of FGF signaling and its effector genes remain poorly characterized in human experimental models mimicking early fetal telencephalic development. We used hiPSC-derived cerebral organoids as an in vitro platform to investigate the effect of FGF8 signaling on neural identity and differentiation. We found that FGF8 treatment increases cellular heterogeneity, leading to distinct telencephalic and mesencephalic-like domains that co-develop in multi-regional organoids. Within telencephalic regions, FGF8 affects the anteroposterior and dorsoventral identity of neural progenitors and the balance between GABAergic and glutamatergic neurons, thus impacting spontaneous neuronal network activity. Moreover, FGF8 efficiently modulates key regulators responsible for several human neurodevelopmental disorders. Overall, our results show that FGF8 signaling is directly involved in both regional patterning and cellular diversity in human cerebral organoids and in modulating genes associated with normal and pathological neural development.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The morphogen FGF8 establishes graded positional cues imparting regional cellular responses via modulation of early target genes. The roles of FGF signaling and its effector genes remain poorly characterized in human experimental models mimicking early fetal telencephalic development. We used hiPSC-derived cerebral organoids as an in vitro platform to investigate the effect of FGF8 signaling on neural identity and differentiation. We found that FGF8 treatment increases cellular heterogeneity, leading to distinct telencephalic and mesencephalic-like domains that co-develop in multi-regional organoids. Within telencephalic regions, FGF8 affects the anteroposterior and dorsoventral identity of neural progenitors and the balance between GABAergic and glutamatergic neurons, thus impacting spontaneous neuronal network activity. Moreover, FGF8 efficiently modulates key regulators responsible for several human neurodevelopmental disorders. Overall, our results show that FGF8 signaling is directly involved in both regional patterning and cellular diversity in human cerebral organoids and in modulating genes associated with normal and pathological neural development. |
 | Sawada, Takeshi; Iino, Yusuke; Yoshida, Kensuke; Okazaki, Hitoshi; Nomura, Shinnosuke; Shimizu, Chika; Arima, Tomoki; Juichi, Motoki; Zhou, Siqi; Kurabayashi, Nobuhiro; Sakurai, Takeshi; Yagishita, Sho; Yanagisawa, Masashi; Toyoizumi, Taro; Kasai, Haruo; Shi, Shoi Prefrontal Synaptic Regulation of Homeostatic Sleep Pressure Revealed Through Synaptic Chemogenetics Journal Article Science , 2024. @article{Sawada2024, title = {Prefrontal Synaptic Regulation of Homeostatic Sleep Pressure Revealed Through Synaptic Chemogenetics}, author = {Takeshi Sawada and Yusuke Iino and Kensuke Yoshida and Hitoshi Okazaki and Shinnosuke Nomura and Chika Shimizu and Tomoki Arima and Motoki Juichi and Siqi Zhou and Nobuhiro Kurabayashi and Takeshi Sakurai and Sho Yagishita and Masashi Yanagisawa and Taro Toyoizumi and Haruo Kasai and Shoi Shi}, url = {https://www.science.org/doi/10.1126/science.adl3043}, doi = {10.1126/science.adl3043}, year = {2024}, date = {2024-09-27}, journal = {Science }, abstract = {Sleep is regulated by homeostatic processes, yet the biological basis of sleep pressure that accumulates during wakefulness, triggers sleep, and dissipates during sleep remains elusive. We explored a causal relationship between cellular synaptic strength and electroencephalography delta power indicating macro-level sleep pressure by developing a theoretical framework and a molecular tool to manipulate synaptic strength. The mathematical model predicted that increased synaptic strength promotes the neuronal “down state” and raises the delta power. Our molecular tool (synapse-targeted chemically induced translocation of Kalirin-7, SYNCit-K), which induces dendritic spine enlargement and synaptic potentiation through chemically induced translocation of protein Kalirin-7, demonstrated that synaptic potentiation of excitatory neurons in the prefrontal cortex (PFC) increases nonrapid eye movement sleep amounts and delta power. Thus, synaptic strength of PFC excitatory neurons dictates sleep pressure in mammals.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Sleep is regulated by homeostatic processes, yet the biological basis of sleep pressure that accumulates during wakefulness, triggers sleep, and dissipates during sleep remains elusive. We explored a causal relationship between cellular synaptic strength and electroencephalography delta power indicating macro-level sleep pressure by developing a theoretical framework and a molecular tool to manipulate synaptic strength. The mathematical model predicted that increased synaptic strength promotes the neuronal “down state” and raises the delta power. Our molecular tool (synapse-targeted chemically induced translocation of Kalirin-7, SYNCit-K), which induces dendritic spine enlargement and synaptic potentiation through chemically induced translocation of protein Kalirin-7, demonstrated that synaptic potentiation of excitatory neurons in the prefrontal cortex (PFC) increases nonrapid eye movement sleep amounts and delta power. Thus, synaptic strength of PFC excitatory neurons dictates sleep pressure in mammals. |
 | Zhang, Xinyu; Burattini, Margherita; Duru, Jens; Chala, Nafsika; Wyssen, Nino; Cofiño-Fabres, Carla; Rivera-Arbeláez, José Manuel; Passier, Robert; Poulikakos, Dimos; Aldo Ferrari, Christina Tringides ; Vörös, János; Luciani, Giovanni Battista; Miragoli, Michele; Zambelli, Tomaso Multimodal Mapping of Electrical and Mechanical Latency of Human-Induced Pluripotent Stem Cell-Derived Cardiomyocyte Layers Journal Article ACS Nano, 2024, ISSN: 1936-0851. @article{Zhang2024, title = {Multimodal Mapping of Electrical and Mechanical Latency of Human-Induced Pluripotent Stem Cell-Derived Cardiomyocyte Layers}, author = {Xinyu Zhang and Margherita Burattini and Jens Duru and Nafsika Chala and Nino Wyssen and Carla Cofiño-Fabres and José Manuel Rivera-Arbeláez and Robert Passier and Dimos Poulikakos and Aldo Ferrari, Christina Tringides and János Vörös and Giovanni Battista Luciani and Michele Miragoli and Tomaso Zambelli}, url = {https://doi.org/10.1021/acsnano.4c03896}, doi = {10.1021/acsnano.4c03896}, issn = {1936-0851}, year = {2024}, date = {2024-08-22}, journal = {ACS Nano}, abstract = {The synchronization of the electrical and mechanical coupling assures the physiological pump function of the heart, but life-threatening pathologies may jeopardize this equilibrium. Recently, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a model for personalized investigation because they can recapitulate human diseased traits, such as compromised electrical capacity or mechanical circuit disruption. This research avails the model of hiPSC-CMs and showcases innovative techniques to study the electrical and mechanical properties as well as their modulation due to inherited cardiomyopathies. In this work, hiPSC-CMs carrying either Brugada syndrome (BRU) or dilated cardiomyopathy (DCM), were organized in a bilayer configuration to first validate the experimental methods and second mimic the physiological environment. High-density CMOS-based microelectrode arrays (HD-MEA) have been employed to study the electrical activity. Furthermore, mechanical function was investigated via quantitative video-based evaluation, upon stimulation with a β-adrenergic agonist. This study introduces two experimental methods. First, high-throughput mechanical measurements in the hiPSC-CM layers (xy-inspection) are obtained using both a recently developed optical tracker (OPT) and confocal reference-free traction force microscopy (cTFM) aimed to quantify cardiac kinematics. Second, atomic force microscopy (AFM) with FluidFM probes, combined with the xy-inspection methods, supplemented a three-dimensional understanding of cell−cell mechanical coupling (xyz-inspection). This particular combination represents amulti-technique approach to detecting electrical and mechanical latency among the cell layers, examining differences and possible implications following inherited cardiomyopathies. It can not only detect disease characteristics in the proposed in vitro model but also quantitatively assess its response to drugs, thereby demonstrating its feasibility as ascalable tool for clinical and pharmacological studies.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The synchronization of the electrical and mechanical coupling assures the physiological pump function of the heart, but life-threatening pathologies may jeopardize this equilibrium. Recently, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a model for personalized investigation because they can recapitulate human diseased traits, such as compromised electrical capacity or mechanical circuit disruption. This research avails the model of hiPSC-CMs and showcases innovative techniques to study the electrical and mechanical properties as well as their modulation due to inherited cardiomyopathies. In this work, hiPSC-CMs carrying either Brugada syndrome (BRU) or dilated cardiomyopathy (DCM), were organized in a bilayer configuration to first validate the experimental methods and second mimic the physiological environment. High-density CMOS-based microelectrode arrays (HD-MEA) have been employed to study the electrical activity. Furthermore, mechanical function was investigated via quantitative video-based evaluation, upon stimulation with a β-adrenergic agonist. This study introduces two experimental methods. First, high-throughput mechanical measurements in the hiPSC-CM layers (xy-inspection) are obtained using both a recently developed optical tracker (OPT) and confocal reference-free traction force microscopy (cTFM) aimed to quantify cardiac kinematics. Second, atomic force microscopy (AFM) with FluidFM probes, combined with the xy-inspection methods, supplemented a three-dimensional understanding of cell−cell mechanical coupling (xyz-inspection). This particular combination represents amulti-technique approach to detecting electrical and mechanical latency among the cell layers, examining differences and possible implications following inherited cardiomyopathies. It can not only detect disease characteristics in the proposed in vitro model but also quantitatively assess its response to drugs, thereby demonstrating its feasibility as ascalable tool for clinical and pharmacological studies. |
| Hoang, Huu; Matsumoto, Nobuyoshi; Miyano, Miyuki; Ikegaya, Yuji; Cortese, Aurelio Dopamine-induced Relaxation of Connectivity Diversifies Burst Patterns in Cultured Hippocampal Networks Journal Article bioRxiv, 2024. @article{Hoang2024, title = {Dopamine-induced Relaxation of Connectivity Diversifies Burst Patterns in Cultured Hippocampal Networks}, author = {Huu Hoang and Nobuyoshi Matsumoto and Miyuki Miyano and Yuji Ikegaya and Aurelio Cortese}, url = {https://www.biorxiv.org/content/10.1101/2024.06.26.600923v1}, doi = {10.1101/2024.06.26.600923}, year = {2024}, date = {2024-06-30}, journal = {bioRxiv}, abstract = {The intricate interplay of neurotransmitters orchestrates a symphony of neural activity in the hippocampus, with dopamine emerging as a key conductor in this complex ensemble. Despite numerous studies uncovering the cellular mechanisms of dopamine, its influence on hippocampal neural networks remains elusive. Combining in vitro electrophysiological recordings of rat embryonic hippocampal neurons, pharmacological interventions, and computational analyses of spike trains, we found that dopamine induces a relaxation in network connectivity, characterised by a reduction in spike coherence. This relaxation expands the repertoire of burst dynamics within these hippocampal networks, a phenomenon notably absent under the administration of dopamine antagonists. Our study provides a thorough understanding of the roles of dopamine signalling in shaping functional networks of hippocampal neurons.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The intricate interplay of neurotransmitters orchestrates a symphony of neural activity in the hippocampus, with dopamine emerging as a key conductor in this complex ensemble. Despite numerous studies uncovering the cellular mechanisms of dopamine, its influence on hippocampal neural networks remains elusive. Combining in vitro electrophysiological recordings of rat embryonic hippocampal neurons, pharmacological interventions, and computational analyses of spike trains, we found that dopamine induces a relaxation in network connectivity, characterised by a reduction in spike coherence. This relaxation expands the repertoire of burst dynamics within these hippocampal networks, a phenomenon notably absent under the administration of dopamine antagonists. Our study provides a thorough understanding of the roles of dopamine signalling in shaping functional networks of hippocampal neurons. |
| Beaubois, Romain; Cheslet, Jérémy; Duenki, Tomoya; Venuto, Giuseppe De; Carè, Marta; Khoyratee, Farad; Chiappalone, Michela; Branchereau, Pascal; Ikeuchi, Yoshiho; Levi, Timothée BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network Journal Article Nature Communications, 2024. @article{Beaubois2024, title = {BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network}, author = {Romain Beaubois and Jérémy Cheslet and Tomoya Duenki and Giuseppe De Venuto and Marta Carè and Farad Khoyratee and Michela Chiappalone and Pascal Branchereau and Yoshiho Ikeuchi and Timothée Levi }, url = {https://www.nature.com/articles/s41467-024-48905-x}, doi = {10.1038/s41467-024-48905-x}, year = {2024}, date = {2024-06-20}, journal = {Nature Communications}, abstract = {Characterization and modeling of biological neural networks has emerged as a field driving significant advancements in our understanding of brain function and related pathologies. As of today, pharmacological treatments for neurological disorders remain limited, pushing the exploration of promising alternative approaches such as electroceutics. Recent research in bioelectronics and neuromorphic engineering have fostered the development of the new generation of neuroprostheses for brain repair. However, achieving their full potential necessitates a deeper understanding of biohybrid interaction. In this study, we present a novel real-time, biomimetic, cost-effective and user-friendly neural network capable of real-time emulation for biohybrid experiments. Our system facilitates the investigation and replication of biophysically detailed neural network dynamics while prioritizing cost-efficiency, flexibility and ease of use. We showcase the feasibility of conducting biohybrid experiments using standard biophysical interfaces and a variety of biological cells as well as real-time emulation of diverse network configurations. We envision our system as a crucial step towards the development of neuromorphic-based neuroprostheses for bioelectrical therapeutics, enabling seamless communication with biological networks on a comparable timescale. Its embedded real-time functionality enhances practicality and accessibility, amplifying its potential for real-world applications in biohybrid experiments.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Characterization and modeling of biological neural networks has emerged as a field driving significant advancements in our understanding of brain function and related pathologies. As of today, pharmacological treatments for neurological disorders remain limited, pushing the exploration of promising alternative approaches such as electroceutics. Recent research in bioelectronics and neuromorphic engineering have fostered the development of the new generation of neuroprostheses for brain repair. However, achieving their full potential necessitates a deeper understanding of biohybrid interaction. In this study, we present a novel real-time, biomimetic, cost-effective and user-friendly neural network capable of real-time emulation for biohybrid experiments. Our system facilitates the investigation and replication of biophysically detailed neural network dynamics while prioritizing cost-efficiency, flexibility and ease of use. We showcase the feasibility of conducting biohybrid experiments using standard biophysical interfaces and a variety of biological cells as well as real-time emulation of diverse network configurations. We envision our system as a crucial step towards the development of neuromorphic-based neuroprostheses for bioelectrical therapeutics, enabling seamless communication with biological networks on a comparable timescale. Its embedded real-time functionality enhances practicality and accessibility, amplifying its potential for real-world applications in biohybrid experiments. |
| Sifringer, Léo; Fratzl, Alex; Clément, Blandine F; Chansoria, Parth; Mönkemöller, Leah S; Duru, Jens; Ihle, Stephan J; Steffens, Simon; Beltraminelli, Anna; Ceylan, Eylul; Hengsteler, Julian; Maurer, Benedikt; Weaver, Sean M; Tringides, Christina M; Vulić, Katarina; Madduri, Srinivas; Zenobi-Wong, Marcy; Roska, Botond; Vörös, János; Ruff, Tobias An implantable biohybrid nerve model towards synaptic deep brain stimulation Journal Article bioRxiv, 2024. @article{Sifringer2024, title = {An implantable biohybrid nerve model towards synaptic deep brain stimulation}, author = {Léo Sifringer and Alex Fratzl and Blandine F. Clément and Parth Chansoria and Leah S. Mönkemöller and Jens Duru and Stephan J. Ihle and Simon Steffens and Anna Beltraminelli and Eylul Ceylan and Julian Hengsteler and Benedikt Maurer and Sean M. Weaver and Christina M. Tringides and Katarina Vulić and Srinivas Madduri and Marcy Zenobi-Wong and Botond Roska and János Vörös and Tobias Ruff}, url = {http://biorxiv.org/lookup/doi/10.1101/2024.05.31.596665}, doi = {10.1101/2024.05.31.596665}, year = {2024}, date = {2024-06-03}, journal = {bioRxiv}, abstract = {Restoring functional vision in blind patients lacking a healthy optic nerve requires bypassing retinal circuits, ideally, by directly stimulating the visual thalamus. However, available deep brain stimulation electrodes do not provide the resolution required for vision restoration. We developed an implantable biohybrid nerve model designed for synaptic stimulation of deep brain targets. The interface combines a stretchable stimulation array with an aligned microfluidic axon guidance system seeded with neural spheroids to facilitate the development of a 3 mm long nerve-like structure. A bioresorbable hydrogel nerve conduit was used as a bridge between the tissue and the biohybrid implant. We demonstrated stimulation of spheroids within the biohybrid structure in vitro and used high-density CMOS microelectrode arrays to show faithful activity conduction across the device. Finally, implantation of the biohybrid nerve onto the mouse cortex showed that neural spheroids grow axons in vivo and remain functionally active for more than 22 days post-implantation.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Restoring functional vision in blind patients lacking a healthy optic nerve requires bypassing retinal circuits, ideally, by directly stimulating the visual thalamus. However, available deep brain stimulation electrodes do not provide the resolution required for vision restoration. We developed an implantable biohybrid nerve model designed for synaptic stimulation of deep brain targets. The interface combines a stretchable stimulation array with an aligned microfluidic axon guidance system seeded with neural spheroids to facilitate the development of a 3 mm long nerve-like structure. A bioresorbable hydrogel nerve conduit was used as a bridge between the tissue and the biohybrid implant. We demonstrated stimulation of spheroids within the biohybrid structure in vitro and used high-density CMOS microelectrode arrays to show faithful activity conduction across the device. Finally, implantation of the biohybrid nerve onto the mouse cortex showed that neural spheroids grow axons in vivo and remain functionally active for more than 22 days post-implantation. |
 | Khajehnejad, Moein; Habibollahi, Forough; Paul, Aswin; Razi, Adeel; Kagan, Brett J Biological Neurons Compete with Deep Reinforcement Learning in Sample Efficiency in a Simulated Gameworld Journal Article arXiv , 2024. @article{Khajehnejad2024, title = {Biological Neurons Compete with Deep Reinforcement Learning in Sample Efficiency in a Simulated Gameworld}, author = {Moein Khajehnejad and Forough Habibollahi and Aswin Paul and Adeel Razi and Brett J. Kagan}, url = {http://arxiv.org/abs/2405.16946}, doi = { https://doi.org/10.48550/arXiv.2405.16946}, year = {2024}, date = {2024-05-27}, journal = {arXiv }, abstract = {How do biological systems and machine learning algorithms compare in the number of samples required to show significant improvements in completing a task? We compared the learning efficiency of in vitro biological neural networks to the state-of-the-art deep reinforcement learning (RL) algorithms in a simplified simulation of the game `Pong'. Using DishBrain, a system that embodies in vitro neural networks with in silico computation using a high-density multi-electrode array, we contrasted the learning rate and the performance of these biological systems against time-matched learning from three state-of-the-art deep RL algorithms (i.e., DQN, A2C, and PPO) in the same game environment. This allowed a meaningful comparison between biological neural systems and deep RL. We find that when samples are limited to a real-world time course, even these very simple biological cultures outperformed deep RL algorithms across various game performance characteristics, implying a higher sample efficiency. Ultimately, even when tested across multiple types of information input to assess the impact of higher dimensional data input, biological neurons showcased faster learning than all deep reinforcement learning agents.}, keywords = {}, pubstate = {published}, tppubtype = {article} } How do biological systems and machine learning algorithms compare in the number of samples required to show significant improvements in completing a task? We compared the learning efficiency of in vitro biological neural networks to the state-of-the-art deep reinforcement learning (RL) algorithms in a simplified simulation of the game `Pong'. Using DishBrain, a system that embodies in vitro neural networks with in silico computation using a high-density multi-electrode array, we contrasted the learning rate and the performance of these biological systems against time-matched learning from three state-of-the-art deep RL algorithms (i.e., DQN, A2C, and PPO) in the same game environment. This allowed a meaningful comparison between biological neural systems and deep RL. We find that when samples are limited to a real-world time course, even these very simple biological cultures outperformed deep RL algorithms across various game performance characteristics, implying a higher sample efficiency. Ultimately, even when tested across multiple types of information input to assess the impact of higher dimensional data input, biological neurons showcased faster learning than all deep reinforcement learning agents. |
| Bucci, Annalisa; Büttner, Marc; Domdei, Niklas; Rosselli, Federica Bianca; Znidaric, Matej; Diggelmann, Roland; Gennaro, Martina De; Cowan, Cameron S; Harmening, Wolf; Hierlemann, Andreas; Roska, Botond; Franke, Felix Action potential propagation speed compensates for traveling distance in the human retina Journal Article bioRxiv , 2024. @article{Bucci2024, title = {Action potential propagation speed compensates for traveling distance in the human retina}, author = {Annalisa Bucci and Marc Büttner and Niklas Domdei and Federica Bianca Rosselli and Matej Znidaric and Roland Diggelmann and Martina De Gennaro and Cameron S. Cowan and Wolf Harmening and Andreas Hierlemann and Botond Roska and Felix Franke }, url = {http://biorxiv.org/lookup/doi/10.1101/2024.04.30.591867}, doi = {10.1101/2024.04.30.591867}, year = {2024}, date = {2024-05-01}, journal = {bioRxiv }, abstract = {Neural information processing requires accurately timed action potentials arriving from presynaptic neurons at the postsynaptic neuron. However, axons of ganglion cells in the human retina feature low axonal conduction speeds and vastly different lengths, which poses a challenge to the brain for constructing a temporally coherent image over the visual field. Combining results from microelectrode array recordings, human behavioral measurements, transmission electron microscopy, and mathematical modelling of the retinal nerve fiber layer, we demonstrate that axonal propagation speeds compensate for variations in axonal length across the human retina including the fovea. The human brain synchronizes the arrival times of action potentials at the optic disc by increasing the diameters of longer axons, which increases their propagation speeds.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Neural information processing requires accurately timed action potentials arriving from presynaptic neurons at the postsynaptic neuron. However, axons of ganglion cells in the human retina feature low axonal conduction speeds and vastly different lengths, which poses a challenge to the brain for constructing a temporally coherent image over the visual field. Combining results from microelectrode array recordings, human behavioral measurements, transmission electron microscopy, and mathematical modelling of the retinal nerve fiber layer, we demonstrate that axonal propagation speeds compensate for variations in axonal length across the human retina including the fovea. The human brain synchronizes the arrival times of action potentials at the optic disc by increasing the diameters of longer axons, which increases their propagation speeds. |
 | Fenton, Timothy A; Haouchine, Olivia Y; Hallam, Elizabeth L; Smith, Emily M; Jackson, Kiya C; Rahbarian, Darlene; Canales, Cesar; Adhikari, Anna; Nord, Alexander S; Ben-Shalom, Roy; Silverman, Jill L Hyperexcitability and translational phenotypes in a preclinical mouse model of SYNGAP1-Related Intellectual Disability Journal Article Research Square, 2024. @article{Fenton2024, title = {Hyperexcitability and translational phenotypes in a preclinical mouse model of SYNGAP1-Related Intellectual Disability}, author = {Timothy A Fenton and Olivia Y Haouchine and Elizabeth L Hallam and Emily M Smith and Kiya C Jackson and Darlene Rahbarian and Cesar Canales and Anna Adhikari and Alexander S Nord and Roy Ben-Shalom and Jill L Silverman}, url = {https://www.researchsquare.com/article/rs-4067746/v1}, doi = {10.21203/rs.3.rs-4067746/v1}, year = {2024}, date = {2024-03-19}, journal = {Research Square}, abstract = {Disruption of SYNGAP1 directly causes a genetically identifiable neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability (SRID). Without functional SynGAP1 protein, individuals are developmentally delayed and have prominent features of intellectual disability, motor impairments, and epilepsy. Over the past two decades, there have been numerous discoveries indicting the critical role of Syngap1. Several rodent models with a loss of Syngap1 have been engineered identifying precise roles in neuronal structure and function, as well as key biochemical pathways key for synapse integrity. Homozygous loss of Syngap1 is lethal. Heterozygous mutations of Syngap1 result in a broad range of behavioral phenotypes. Our in vivo functional data, using the mouse model from the Huganir laboratory, corroborated earlier reported behaviors including robust hyperactivity and deficits in learning and memory in young adults. In extension, we report impairments in slow wave sleep, a critical component of the domain of sleep. We characterized Syngap1+/- mice by using neurophysiology collected with wireless, telemetric electroencephalography (EEG). Syngap1+/- mice also exhibited elevated spiking events and spike trains, in addition to elevated power, most notably in the delta frequency band. For the first time, we illustrated how primary neurons from Syngap1+/- mice function and display increased network firing activity, greater bursts, and shorter inter-burst intervals between peaks by employing high density microelectrode arrays (HD-MEA). Our reported data bridge in-vitro electrophysiological neuronal activity and function with in vivo neurophysiological brain activity and function. These data elucidate quantitative, translational biomarkers in vivo and in vitro that can be utilized for the development of and efficacy assessment of targeted treatments for SRID.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Disruption of SYNGAP1 directly causes a genetically identifiable neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability (SRID). Without functional SynGAP1 protein, individuals are developmentally delayed and have prominent features of intellectual disability, motor impairments, and epilepsy. Over the past two decades, there have been numerous discoveries indicting the critical role of Syngap1. Several rodent models with a loss of Syngap1 have been engineered identifying precise roles in neuronal structure and function, as well as key biochemical pathways key for synapse integrity. Homozygous loss of Syngap1 is lethal. Heterozygous mutations of Syngap1 result in a broad range of behavioral phenotypes. Our in vivo functional data, using the mouse model from the Huganir laboratory, corroborated earlier reported behaviors including robust hyperactivity and deficits in learning and memory in young adults. In extension, we report impairments in slow wave sleep, a critical component of the domain of sleep. We characterized Syngap1+/- mice by using neurophysiology collected with wireless, telemetric electroencephalography (EEG). Syngap1+/- mice also exhibited elevated spiking events and spike trains, in addition to elevated power, most notably in the delta frequency band. For the first time, we illustrated how primary neurons from Syngap1+/- mice function and display increased network firing activity, greater bursts, and shorter inter-burst intervals between peaks by employing high density microelectrode arrays (HD-MEA). Our reported data bridge in-vitro electrophysiological neuronal activity and function with in vivo neurophysiological brain activity and function. These data elucidate quantitative, translational biomarkers in vivo and in vitro that can be utilized for the development of and efficacy assessment of targeted treatments for SRID. |
| Voitiuk, Kateryna; Seiler, Spencer T; de Melo, Mirella Pessoa; Geng, Jinghui; Hernandez, Sebastian; Schweiger, Hunter E; Sevetson, Jess L; Parks, David F; Robbins, Ash; Torres-Montoya, Sebastian; Ehrlich, Drew; Elliott, Matthew A T; Sharf, Tal; Haussler, David; Mostajo-Radji, Mohammed A; Salama, Sofie R; Teodorescu, Mircea A feedback-driven IoT microfluidic, electrophysiology, and imaging platform for brain organoid studies Journal Article bioRxiv, 2024. @article{Voitiuk2024, title = {A feedback-driven IoT microfluidic, electrophysiology, and imaging platform for brain organoid studies}, author = {Kateryna Voitiuk and Spencer T. Seiler and Mirella Pessoa de Melo and Jinghui Geng and Sebastian Hernandez and Hunter E. Schweiger and Jess L. Sevetson and David F. Parks and Ash Robbins and Sebastian Torres-Montoya and Drew Ehrlich and Matthew A.T. Elliott and Tal Sharf and David Haussler and Mohammed A. Mostajo-Radji and Sofie R. Salama and Mircea Teodorescu}, url = {http://biorxiv.org/lookup/doi/10.1101/2024.03.15.585237}, doi = {10.1101/2024.03.15.585237}, year = {2024}, date = {2024-03-17}, journal = {bioRxiv}, abstract = {The analysis of tissue cultures, particularly brain organoids, takes a high degree of coordination, measurement, and monitoring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Unified by an Internet of Things (IoT) architecture, our approach enables continuous, communicative interactions among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids and monitor their neuronal activity. The organoids are cultured in custom, 3D-printed chambers attached to commercial microelectrode arrays for electrophysiology monitoring. Periodic feeding is achieved using programmable microfluidic pumps. We developed computer vision fluid volume estimations of aspirated media, achieving high accuracy, and used feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a 7-day study of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated experimental samples maintained robust neural activity throughout the experiment, comparable with the control samples. The automated system enabled hourly electrophysiology recordings that revealed dramatic temporal changes in neuron firing rates not observed in once-a-day recordings. One-Sentence Summary: An IoT laboratory robotics system that enables touch-free feeding, imaging, and electrophysiology of brain organoids.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The analysis of tissue cultures, particularly brain organoids, takes a high degree of coordination, measurement, and monitoring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Unified by an Internet of Things (IoT) architecture, our approach enables continuous, communicative interactions among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids and monitor their neuronal activity. The organoids are cultured in custom, 3D-printed chambers attached to commercial microelectrode arrays for electrophysiology monitoring. Periodic feeding is achieved using programmable microfluidic pumps. We developed computer vision fluid volume estimations of aspirated media, achieving high accuracy, and used feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a 7-day study of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated experimental samples maintained robust neural activity throughout the experiment, comparable with the control samples. The automated system enabled hourly electrophysiology recordings that revealed dramatic temporal changes in neuron firing rates not observed in once-a-day recordings. One-Sentence Summary: An IoT laboratory robotics system that enables touch-free feeding, imaging, and electrophysiology of brain organoids. |
 | Kasuba, Krishna Chaitanya; Buccino, Alessio Paolo; Bartram, Julian; Gaub, Benjamin M; Fauser, Felix J; Ronchi, Silvia; Kumar, Sreedhar Saseendran; Geissler, Sydney; Nava, Michele M; Hierlemann, Andreas; Müller, Daniel J Nature Nanotechnology, 2024. @article{Kasuba2024, title = {Mechanical stimulation and electrophysiological monitoring at subcellular resolution reveals differential mechanosensation of neurons within networks}, author = {Krishna Chaitanya Kasuba and Alessio Paolo Buccino and Julian Bartram and Benjamin M. Gaub and Felix J. Fauser and Silvia Ronchi and Sreedhar Saseendran Kumar and Sydney Geissler and Michele M. Nava and Andreas Hierlemann and Daniel J. Müller }, url = {https://www.nature.com/articles/s41565-024-01609-1}, doi = {10.1038/s41565-024-01609-1}, year = {2024}, date = {2024-02-20}, journal = {Nature Nanotechnology}, abstract = {A growing consensus that the brain is a mechanosensitive organ is driving the need for tools that mechanically stimulate and simultaneously record the electrophysiological response of neurons within neuronal networks. Here we introduce a synchronized combination of atomic force microscopy, high-density microelectrode array and fluorescence microscopy to monitor neuronal networks and to mechanically characterize and stimulate individual neurons at piconewton force sensitivity and nanometre precision while monitoring their electrophysiological activity at subcellular spatial and millisecond temporal resolution. No correlation is found between mechanical stiffness and electrophysiological activity of neuronal compartments. Furthermore, spontaneously active neurons show exceptional functional resilience to static mechanical compression of their soma. However, application of fast transient (∼500 ms) mechanical stimuli to the neuronal soma can evoke action potentials, which depend on the anchoring of neuronal membrane and actin cytoskeleton. Neurons show higher responsivity, including bursts of action potentials, to slower transient mechanical stimuli (∼60 s). Moreover, transient and repetitive application of the same compression modulates the neuronal firing rate. Seemingly, neuronal networks can differentiate and respond to specific characteristics of mechanical stimulation. Ultimately, the developed multiparametric tool opens the door to explore manifold nanomechanobiological responses of neuronal systems and new ways of mechanical control.}, keywords = {}, pubstate = {published}, tppubtype = {article} } A growing consensus that the brain is a mechanosensitive organ is driving the need for tools that mechanically stimulate and simultaneously record the electrophysiological response of neurons within neuronal networks. Here we introduce a synchronized combination of atomic force microscopy, high-density microelectrode array and fluorescence microscopy to monitor neuronal networks and to mechanically characterize and stimulate individual neurons at piconewton force sensitivity and nanometre precision while monitoring their electrophysiological activity at subcellular spatial and millisecond temporal resolution. No correlation is found between mechanical stiffness and electrophysiological activity of neuronal compartments. Furthermore, spontaneously active neurons show exceptional functional resilience to static mechanical compression of their soma. However, application of fast transient (∼500 ms) mechanical stimuli to the neuronal soma can evoke action potentials, which depend on the anchoring of neuronal membrane and actin cytoskeleton. Neurons show higher responsivity, including bursts of action potentials, to slower transient mechanical stimuli (∼60 s). Moreover, transient and repetitive application of the same compression modulates the neuronal firing rate. Seemingly, neuronal networks can differentiate and respond to specific characteristics of mechanical stimulation. Ultimately, the developed multiparametric tool opens the door to explore manifold nanomechanobiological responses of neuronal systems and new ways of mechanical control. |
 | Hruska-Plochan, Marian; Wiersma, Vera I; Betz, Katharina M; Mallona, Izaskun; Ronchi, Silvia; Maniecka, Zuzanna; Hock, Eva-Maria; Tantardini, Elena; Laferriere, Florent; Sahadevan, Sonu; Hoop, Vanessa; Delvendahl, Igor; Pérez-Berlanga, Manuela; Gatta, Beatrice; Panatta, Martina; van der Bourg, Alexander; Bohaciakova, Dasa; Sharma, Puneet; Vos, Laura De; Frontzek, Karl; Aguzzi, Adriano; Lashley, Tammaryn; Robinson, Mark D; Karayannis, Theofanis; Mueller, Martin; Hierlemann, Andreas; Polymenidou, Magdalini A model of human neural networks reveals NPTX2 pathology in ALS and FTLD Journal Article Nature, 2024. @article{Hruska-Plochan2024, title = {A model of human neural networks reveals NPTX2 pathology in ALS and FTLD}, author = {Marian Hruska-Plochan and Vera I. Wiersma and Katharina M. Betz and Izaskun Mallona and Silvia Ronchi and Zuzanna Maniecka and Eva-Maria Hock and Elena Tantardini and Florent Laferriere and Sonu Sahadevan and Vanessa Hoop and Igor Delvendahl and Manuela Pérez-Berlanga and Beatrice Gatta and Martina Panatta and Alexander van der Bourg and Dasa Bohaciakova and Puneet Sharma and Laura De Vos and Karl Frontzek and Adriano Aguzzi and Tammaryn Lashley and Mark D. Robinson and Theofanis Karayannis and Martin Mueller and Andreas Hierlemann and Magdalini Polymenidou }, url = {https://www.nature.com/articles/s41586-024-07042-7}, doi = {10.1038/s41586-024-07042-7}, year = {2024}, date = {2024-02-14}, journal = {Nature}, abstract = {Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1, which involve human-specific mechanisms that cannot be directly studied in animal models. Here, to explore the emergence and consequences of TDP-43 pathologies, we generated induced pluripotent stem cell-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors. Single-cell transcriptomics and comparison to independent neural stem cells showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks (which we designate iNets). Neuronal and glial maturation in iNets was similar to that of cortical organoids. Overexpression of wild-type TDP-43 in a minority of neurons within iNets led to progressive fragmentation and aggregation of the protein, resulting in a partial loss of function and neurotoxicity. Single-cell transcriptomics revealed a novel set of misregulated RNA targets in TDP-43-overexpressing neurons and in patients with TDP-43 proteinopathies exhibiting a loss of nuclear TDP-43. The strongest misregulated target encoded the synaptic protein NPTX2, the levels of which are controlled by TDP-43 binding on its 3′ untranslated region. When NPTX2 was overexpressed in iNets, it exhibited neurotoxicity, whereas correcting NPTX2 misregulation partially rescued neurons from TDP-43-induced neurodegeneration. Notably, NPTX2 was consistently misaccumulated in neurons from patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby revealing a TDP-43-dependent pathway of neurotoxicity.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1, which involve human-specific mechanisms that cannot be directly studied in animal models. Here, to explore the emergence and consequences of TDP-43 pathologies, we generated induced pluripotent stem cell-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors. Single-cell transcriptomics and comparison to independent neural stem cells showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks (which we designate iNets). Neuronal and glial maturation in iNets was similar to that of cortical organoids. Overexpression of wild-type TDP-43 in a minority of neurons within iNets led to progressive fragmentation and aggregation of the protein, resulting in a partial loss of function and neurotoxicity. Single-cell transcriptomics revealed a novel set of misregulated RNA targets in TDP-43-overexpressing neurons and in patients with TDP-43 proteinopathies exhibiting a loss of nuclear TDP-43. The strongest misregulated target encoded the synaptic protein NPTX2, the levels of which are controlled by TDP-43 binding on its 3′ untranslated region. When NPTX2 was overexpressed in iNets, it exhibited neurotoxicity, whereas correcting NPTX2 misregulation partially rescued neurons from TDP-43-induced neurodegeneration. Notably, NPTX2 was consistently misaccumulated in neurons from patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby revealing a TDP-43-dependent pathway of neurotoxicity. |
 | Wang, Guodong; Zhang, Dandan; Qin, Liangshan; Liu, Quanhui; Tang, Wenkui; Liu, Mingxing; Xu, Fan; Tang, Fen; Cheng, Leping; Mo, Huiming; Yuan, Xiang; Wang, Zhiqiang; Huang, Ben Forskolin-driven conversion of human somatic cells into induced neurons through regulation of the cAMP-CREB1-JNK signaling Journal Article Theranostics , 2024. @article{Wang2024, title = {Forskolin-driven conversion of human somatic cells into induced neurons through regulation of the cAMP-CREB1-JNK signaling}, author = {Guodong Wang and Dandan Zhang and Liangshan Qin and Quanhui Liu and Wenkui Tang and Mingxing Liu and Fan Xu and Fen Tang and Leping Cheng and Huiming Mo and Xiang Yuan and Zhiqiang Wang and Ben Huang}, url = {https://www.thno.org/v14p1701.htm}, doi = {10.7150/thno.92700}, year = {2024}, date = {2024-02-11}, journal = {Theranostics }, abstract = {Human somatic cells can be reprogrammed into neuron cell fate through regulation of a single transcription factor or application of small molecule cocktails. Methods: Here, we report that forskolin efficiently induces the conversion of human somatic cells into induced neurons (FiNs). Results: A large population of neuron-like phenotype cells was observed as early as 24-36 h post-induction. There were >90% TUJ1-, >80% MAP2-, and >80% NEUN-positive neurons at 5 days post-induction. Multiple subtypes of neurons were present among TUJ1-positive cells, including >60% cholinergic, >20% glutamatergic, >10% GABAergic, and >5% dopaminergic neurons. FiNs exhibited typical neural electrophysiological activity in vitro and the ability to survive in vitro and in vivo more than 2 months. Mechanistically, forskolin functions in FiN reprogramming by regulating the cAMP-CREB1-JNK signals, which upregulates cAMP-CREB1 expression and downregulates JNK expression. Conclusion: Overall, our studies identify a safer and efficient single-small-molecule-driven reprogramming approach for induced neuron generation and reveal a novel regulatory mechanism of neuronal cell fate acquisition.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Human somatic cells can be reprogrammed into neuron cell fate through regulation of a single transcription factor or application of small molecule cocktails. Methods: Here, we report that forskolin efficiently induces the conversion of human somatic cells into induced neurons (FiNs). Results: A large population of neuron-like phenotype cells was observed as early as 24-36 h post-induction. There were >90% TUJ1-, >80% MAP2-, and >80% NEUN-positive neurons at 5 days post-induction. Multiple subtypes of neurons were present among TUJ1-positive cells, including >60% cholinergic, >20% glutamatergic, >10% GABAergic, and >5% dopaminergic neurons. FiNs exhibited typical neural electrophysiological activity in vitro and the ability to survive in vitro and in vivo more than 2 months. Mechanistically, forskolin functions in FiN reprogramming by regulating the cAMP-CREB1-JNK signals, which upregulates cAMP-CREB1 expression and downregulates JNK expression. Conclusion: Overall, our studies identify a safer and efficient single-small-molecule-driven reprogramming approach for induced neuron generation and reveal a novel regulatory mechanism of neuronal cell fate acquisition. |
 | Hornauer, Philipp; Prack, Gustavo; Anastasi, Nadia; Ronchi, Silvia; Kim, Taehoon; Donner, Christian; Fiscella, Michele; Borgwardt, Karsten; Taylor, Verdon; Jagasia, Ravi; Roqueiro, Damian; Hierlemann, Andreas; Schröter, Manuel DeePhys: A machine learning–assisted platform for electrophysiological phenotyping of human neuronal networks Journal Article Stem Cell Reports, 2024. @article{Hornauer2024, title = {DeePhys: A machine learning–assisted platform for electrophysiological phenotyping of human neuronal networks}, author = {Philipp Hornauer and Gustavo Prack and Nadia Anastasi and Silvia Ronchi and Taehoon Kim and Christian Donner and Michele Fiscella and Karsten Borgwardt and Verdon Taylor and Ravi Jagasia and Damian Roqueiro and Andreas Hierlemann and Manuel Schröter}, url = {https://www.sciencedirect.com/science/article/pii/S2213671123005015}, doi = {10.1016/j.stemcr.2023.12.008}, year = {2024}, date = {2024-01-25}, journal = {Stem Cell Reports}, abstract = {Reproducible functional assays to study in vitro neuronal networks represent an important cornerstone in the quest to develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven functional phenotyping of in vitro neuronal cultures recorded by high-density microelectrode arrays. DeePhys is a modular workflow that offers a range of techniques to extract features from spike-sorted data, allowing for the examination of functional phenotypes both at the individual cell and network levels, as well as across development. In addition, DeePhys incorporates the capability to integrate novel features and to use machine-learning-assisted approaches, which facilitates a comprehensive evaluation of pharmacological interventions. To illustrate its practical application, we apply DeePhys to human induced pluripotent stem cell–derived dopaminergic neurons obtained from both patients and healthy individuals and showcase how DeePhys enables phenotypic screenings.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Reproducible functional assays to study in vitro neuronal networks represent an important cornerstone in the quest to develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven functional phenotyping of in vitro neuronal cultures recorded by high-density microelectrode arrays. DeePhys is a modular workflow that offers a range of techniques to extract features from spike-sorted data, allowing for the examination of functional phenotypes both at the individual cell and network levels, as well as across development. In addition, DeePhys incorporates the capability to integrate novel features and to use machine-learning-assisted approaches, which facilitates a comprehensive evaluation of pharmacological interventions. To illustrate its practical application, we apply DeePhys to human induced pluripotent stem cell–derived dopaminergic neurons obtained from both patients and healthy individuals and showcase how DeePhys enables phenotypic screenings. |
| van der Molen, Tjitse; Spaeth, Alex; Chini, Mattia; Bartram, Julian; Dendukuri, Aditya; Zhang, Zongren; Bhaskaran-Nair, Kiran; Blauvelt, Lon J; Petzold, Linda R; Hansma, Paul K; Teodorescu, Mircea; Hierlemann, Andreas; Hengen, Keith B; Hanganu-Opatz, Ileana L; Kosik, Kenneth S; Sharf, Tal Protosequences in human cortical organoids model intrinsic states in the developing cortex Journal Article bioRxiv, 2023. @article{Molen2023, title = {Protosequences in human cortical organoids model intrinsic states in the developing cortex}, author = {Tjitse van der Molen and Alex Spaeth and Mattia Chini and Julian Bartram and Aditya Dendukuri and Zongren Zhang and Kiran Bhaskaran-Nair and Lon J. Blauvelt and Linda R. Petzold and Paul K. Hansma and Mircea Teodorescu and Andreas Hierlemann and Keith B. Hengen and Ileana L. Hanganu-Opatz and Kenneth S. Kosik and Tal Sharf}, url = {https://www.biorxiv.org/content/10.1101/2023.12.29.573646v1}, doi = {10.1101/2023.12.29.573646}, year = {2023}, date = {2023-12-30}, journal = {bioRxiv}, abstract = {Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development. |
 | Cai, Hongwei; Ao, Zheng; Tian, Chunhui; Wu, Zhuhao; Liu, Hongcheng; Tchieu, Jason; Gu, Mingxia; Mackie, Ken; Guo, Feng Brain organoid reservoir computing for artificial intelligence Journal Article Nature Electronics, 2023. @article{Cai2023b, title = {Brain organoid reservoir computing for artificial intelligence}, author = {Hongwei Cai and Zheng Ao and Chunhui Tian and Zhuhao Wu and Hongcheng Liu and Jason Tchieu and Mingxia Gu and Ken Mackie and Feng Guo }, url = {https://www.nature.com/articles/s41928-023-01069-w}, doi = {10.1038/s41928-023-01069-w}, year = {2023}, date = {2023-12-11}, journal = {Nature Electronics}, abstract = {Brain-inspired computing hardware aims to emulate the structure and working principles of the brain and could be used to address current limitations in artificial intelligence technologies. However, brain-inspired silicon chips are still limited in their ability to fully mimic brain function as most examples are built on digital electronic principles. Here we report an artificial intelligence hardware approach that uses adaptive reservoir computation of biological neural networks in a brain organoid. In this approach—which is termed Brainoware—computation is performed by sending and receiving information from the brain organoid using a high-density multielectrode array. By applying spatiotemporal electrical stimulation, nonlinear dynamics and fading memory properties are achieved, as well as unsupervised learning from training data by reshaping the organoid functional connectivity. We illustrate the practical potential of this technique by using it for speech recognition and nonlinear equation prediction in a reservoir computing framework.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Brain-inspired computing hardware aims to emulate the structure and working principles of the brain and could be used to address current limitations in artificial intelligence technologies. However, brain-inspired silicon chips are still limited in their ability to fully mimic brain function as most examples are built on digital electronic principles. Here we report an artificial intelligence hardware approach that uses adaptive reservoir computation of biological neural networks in a brain organoid. In this approach—which is termed Brainoware—computation is performed by sending and receiving information from the brain organoid using a high-density multielectrode array. By applying spatiotemporal electrical stimulation, nonlinear dynamics and fading memory properties are achieved, as well as unsupervised learning from training data by reshaping the organoid functional connectivity. We illustrate the practical potential of this technique by using it for speech recognition and nonlinear equation prediction in a reservoir computing framework. |
| Friston, Karl J; Salvatori, Tommaso; Isomura, Takuya; Tschantz, Alexander; Kiefer, Alex; Verbelen, Tim; Koudahl, Magnus; Paul, Aswin; Parr, Thomas; Razi, Adeel; Kagan, Brett; Buckley, Christopher L; and Ramstead, Maxwell J D Active Inference and Intentional Behaviour Journal Article arXiv, 2023. @article{Friston2023, title = {Active Inference and Intentional Behaviour}, author = {Karl J. Friston and Tommaso Salvatori and Takuya Isomura and Alexander Tschantz and Alex Kiefer and Tim Verbelen and Magnus Koudahl and Aswin Paul and Thomas Parr and Adeel Razi and Brett Kagan and Christopher L. Buckley and and Maxwell J. D. Ramstead}, url = {http://arxiv.org/abs/2312.07547}, doi = {10.48550/arXiv.2312.07547}, year = {2023}, date = {2023-12-06}, journal = {arXiv}, abstract = {Recent advances in theoretical biology suggest that basal cognition and sentient behaviour are emergent properties of in vitro cell cultures and neuronal networks, respectively. Such neuronal networks spontaneously learn structured behaviours in the absence of reward or reinforcement. In this paper, we characterise this kind of selforganisation through the lens of the free energy principle, i.e., as self-evidencing. We do this by first discussing the definitions of reactive and sentient behaviour in the setting of active inference, which describes the behaviour of agents that model the consequences of their actions. We then introduce a formal account of intentional behaviour, that describes agents as driven by a preferred endpoint or goal in latent state-spaces. We then investigate these forms of (reactive, sentient, and intentional) behaviour using simulations. First, we simulate the aforementioned in vitro experiments, in which neuronal cultures spontaneously learn to play Pong, by implementing nested, free energy minimising processes. The simulations are then used to deconstruct the ensuing predictive behaviour—leading to the distinction between merely reactive, sentient, and intentional behaviour, with the latter formalised in terms of inductive planning. This distinction is further studied using simple machine learning benchmarks (navigation in a grid world and the Tower of Hanoi problem), that show how quickly and efficiently adaptive behaviour emerges under an inductive form of active inference.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Recent advances in theoretical biology suggest that basal cognition and sentient behaviour are emergent properties of in vitro cell cultures and neuronal networks, respectively. Such neuronal networks spontaneously learn structured behaviours in the absence of reward or reinforcement. In this paper, we characterise this kind of selforganisation through the lens of the free energy principle, i.e., as self-evidencing. We do this by first discussing the definitions of reactive and sentient behaviour in the setting of active inference, which describes the behaviour of agents that model the consequences of their actions. We then introduce a formal account of intentional behaviour, that describes agents as driven by a preferred endpoint or goal in latent state-spaces. We then investigate these forms of (reactive, sentient, and intentional) behaviour using simulations. First, we simulate the aforementioned in vitro experiments, in which neuronal cultures spontaneously learn to play Pong, by implementing nested, free energy minimising processes. The simulations are then used to deconstruct the ensuing predictive behaviour—leading to the distinction between merely reactive, sentient, and intentional behaviour, with the latter formalised in terms of inductive planning. This distinction is further studied using simple machine learning benchmarks (navigation in a grid world and the Tower of Hanoi problem), that show how quickly and efficiently adaptive behaviour emerges under an inductive form of active inference. |
 | Elliott, Matthew A T; Schweiger, Hunter E; Robbins, Ash; Vera-Choqqueccota, Samira; Ehrlich, Drew; Hernandez, Sebastian; Voitiuk, Kateryna; Geng, Jinghui; Sevetson, Jess L; Core, Cordero; Rosen, Yohei M; Teodorescu, Mircea; Wagner, Nico O; Haussler, David; Mostajo-Radji, Mohammed A Internet-Connected Cortical Organoids for Project-Based Stem Cell and Neuroscience Education Journal Article eNeuro, 2023. @article{Elliott2023, title = {Internet-Connected Cortical Organoids for Project-Based Stem Cell and Neuroscience Education}, author = {Matthew A. T. Elliott and Hunter E. Schweiger and Ash Robbins and Samira Vera-Choqqueccota and Drew Ehrlich and Sebastian Hernandez and Kateryna Voitiuk and Jinghui Geng and Jess L. Sevetson and Cordero Core and Yohei M. Rosen and Mircea Teodorescu and Nico O. Wagner and David Haussler and Mohammed A. Mostajo-Radji}, url = {https://www.eneuro.org/lookup/doi/10.1523/ENEURO.0308-23.2023}, doi = {10.1523/ENEURO.0308-23.2023}, year = {2023}, date = {2023-11-28}, journal = {eNeuro}, abstract = {The introduction of Internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell (PSC)-derived cortical organoids in two different settings: using microscopy to monitor organoid growth in an introductory tissue culture course and using high-density (HD) multielectrode arrays (MEAs) to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The introduction of Internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell (PSC)-derived cortical organoids in two different settings: using microscopy to monitor organoid growth in an introductory tissue culture course and using high-density (HD) multielectrode arrays (MEAs) to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training. |
 | Kobayashi, Toki; Shimba, Kenta; Kotani, Kiyoshi; Jimbo, Yasuhiko Measuring and Inducing the Plasticity of Single-Neuron Scale at Multiple Points Conference ISSS Xplore, 2023. @conference{Kobayashi2023, title = {Measuring and Inducing the Plasticity of Single-Neuron Scale at Multiple Points}, author = {Toki Kobayashi and Kenta Shimba and Kiyoshi Kotani and Yasuhiko Jimbo}, url = {https://ieeexplore.ieee.org/abstract/document/10322076}, doi = {10.1109/BMEiCON60347.2023.10322076}, year = {2023}, date = {2023-11-22}, journal = {IEEE Xplore}, publisher = {ISSS Xplore}, abstract = {Information processing in the brain is supported by the plasticity of the connections of neurons in biological neuronal networks. There is a gap between our understanding on plasticity of individual connections and that of the neuronal networks. Here, we aimed to induce and measure plasticity at the connections of individual neurons and at the network level. We achieved inducing plasticity with a combination of single cell stimulation by optogenetics and high-resolution extracellular potentials recording by high-density microelectrode array. Spike timing plasticity in a single neuron was successfully measured. Although we also tried to induce synaptic potentiation by tetanus stimulation, no significant change was observed. In the future, we will investigate how the plasticity of individual connections changes dynamics of entire network.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } Information processing in the brain is supported by the plasticity of the connections of neurons in biological neuronal networks. There is a gap between our understanding on plasticity of individual connections and that of the neuronal networks. Here, we aimed to induce and measure plasticity at the connections of individual neurons and at the network level. We achieved inducing plasticity with a combination of single cell stimulation by optogenetics and high-resolution extracellular potentials recording by high-density microelectrode array. Spike timing plasticity in a single neuron was successfully measured. Although we also tried to induce synaptic potentiation by tetanus stimulation, no significant change was observed. In the future, we will investigate how the plasticity of individual connections changes dynamics of entire network. |
| Tamatani, Chie; Shimba, Kenta; andYasuhiko Jimbo, Kiyoshi Kotani Activity- and Spatial-dependent Variations in Axonal Conduction Recorded from Microtunnel Electrodes Conference IEEE Xplore, 2023. @conference{Tamatani2023, title = {Activity- and Spatial-dependent Variations in Axonal Conduction Recorded from Microtunnel Electrodes}, author = {Chie Tamatani and Kenta Shimba and Kiyoshi Kotani andYasuhiko Jimbo }, url = {https://ieeexplore.ieee.org/abstract/document/10321980}, doi = {10.1109/BMEiCON60347.2023.10321980}, year = {2023}, date = {2023-11-22}, publisher = {IEEE Xplore}, abstract = {Axons are not simple transmission cables in neuronal networks, but they are directly involved in information processing. We developed a novel culture device that aims to assess axonal conduction properties. The microdevice consists of microtunnels directly fabricated on high-density microelectrode array. Neuron growth and axon isolation were confirmed by immunofluorescent staining and neural activity recording. Several dozens of electrodes were detected from each tunnel and signals had enough S/N ratio to handle each spike event. Activity- and spatial-dependent variations in conduction velocity were observed. These results suggest that our microdevice is feasible to study axonal information processing.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } Axons are not simple transmission cables in neuronal networks, but they are directly involved in information processing. We developed a novel culture device that aims to assess axonal conduction properties. The microdevice consists of microtunnels directly fabricated on high-density microelectrode array. Neuron growth and axon isolation were confirmed by immunofluorescent staining and neural activity recording. Several dozens of electrodes were detected from each tunnel and signals had enough S/N ratio to handle each spike event. Activity- and spatial-dependent variations in conduction velocity were observed. These results suggest that our microdevice is feasible to study axonal information processing. |
 | Nakajima, Ryota; Shirakami, Arata; Tsumura, Hayato; Matsuda, Kouki; Nakamura, Eita; Shimono, Masanori Mutual generation in neuronal activity across the brain via deep neural approach, and its network interpretation Journal Article Communications Biology, 2023. @article{Nakajima2023, title = {Mutual generation in neuronal activity across the brain via deep neural approach, and its network interpretation}, author = {Ryota Nakajima and Arata Shirakami and Hayato Tsumura and Kouki Matsuda and Eita Nakamura and Masanori Shimono}, url = {https://www.nature.com/articles/s42003-023-05453-2}, doi = {10.1038/s42003-023-05453-2}, year = {2023}, date = {2023-10-31}, journal = {Communications Biology}, abstract = {In the brain, many regions work in a network-like association, yet it is not known how durable these associations are in terms of activity and could survive without structural connections. To assess the association or similarity between brain regions with a generating approach, this study evaluated the similarity of activities of neurons within each region after disconnecting between regions. The “generation” approach here refers to using a multi-layer LSTM (Long Short-Term Memory) model to learn the rules of activity generation in one region and then apply that knowledge to generate activity in other regions. Surprisingly, the results revealed that activity generation from one region to disconnected regions was possible with similar accuracy to generation between the same regions in many cases. Notably, firing rates and synchronization of firing between neuron pairs, often used as neuronal representations, could be reproduced with precision. Additionally, accuracies were associated with the relative angle between brain regions and the strength of the structural connections that initially connected them. This outcome enables us to look into trends governing non-uniformity of the cortex based on the potential to generate informative data and reduces the need for animal experiments.}, keywords = {}, pubstate = {published}, tppubtype = {article} } In the brain, many regions work in a network-like association, yet it is not known how durable these associations are in terms of activity and could survive without structural connections. To assess the association or similarity between brain regions with a generating approach, this study evaluated the similarity of activities of neurons within each region after disconnecting between regions. The “generation” approach here refers to using a multi-layer LSTM (Long Short-Term Memory) model to learn the rules of activity generation in one region and then apply that knowledge to generate activity in other regions. Surprisingly, the results revealed that activity generation from one region to disconnected regions was possible with similar accuracy to generation between the same regions in many cases. Notably, firing rates and synchronization of firing between neuron pairs, often used as neuronal representations, could be reproduced with precision. Additionally, accuracies were associated with the relative angle between brain regions and the strength of the structural connections that initially connected them. This outcome enables us to look into trends governing non-uniformity of the cortex based on the potential to generate informative data and reduces the need for animal experiments. |
 | Duru, Jens; Rüfenacht, Arielle; Löhle, Josephine; Pozzi, Marcello; Forró, Csaba; Ledermann, Linus; Bernardi, Aeneas; Matter, Michael; Renia, André; Simona, Benjamin; Tringides, Christina M; Bernhard, Stéphane; Ihle, Stephan J; Hengsteler, Julian; Maurer, Benedikt; Zhanga, Xinyu; Nakatsuka, Nako Driving electrochemical reactions at the microscale using CMOS microelectrode arrays Journal Article Lab on a Chip, 2023, ISSN: 1473-0189. @article{Duru2023c, title = {Driving electrochemical reactions at the microscale using CMOS microelectrode arrays}, author = {Jens Duru and Arielle Rüfenacht and Josephine Löhle and Marcello Pozzi and Csaba Forró and Linus Ledermann and Aeneas Bernardi and Michael Matter and André Renia and Benjamin Simona and Christina M. Tringides and Stéphane Bernhard and Stephan J. Ihle and Julian Hengsteler and Benedikt Maurer and Xinyu Zhanga and Nako Nakatsuka}, url = {https://pubs.rsc.org/en/content/articlelanding/2023/lc/d3lc00630a}, doi = {10.1039/D3LC00630A}, issn = {1473-0189}, year = {2023}, date = {2023-10-30}, journal = {Lab on a Chip}, abstract = {Precise control of pH values at electrode interfaces enables the systematic investigation of pH-dependent processes by electrochemical means. In this work, we employed high-density complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs) as miniaturized systems to induce and confine electrochemical reactions in areas corresponding to the pitch of single electrodes (17.5 μm). First, we present a strategy for generating localized pH patterns on the surface of the CMOS MEA with unprecedented spatial resolution. Leveraging the versatile routing capabilities of the switch matrix beneath the CMOS MEA, we created arbitrary combinations of anodic and cathodic electrodes and hence pH patterns. Moreover, we utilized the system to produce polymeric surface patterns by additive and subtractive methods. For additive patterning, we controlled the in situ formation of polydopamine at the microelectrode surface through oxidation of free dopamine above a threshold pH > 8.5. For subtractive patterning, we removed cell-adhesive poly-L-lysine from the electrode surface and backfilled the voids with antifouling polymers. Such polymers were chosen to provide a proof-of-concept application of controlling neuronal growth via electrochemically-induced patterns on the CMOS MEA surface. Importantly, our platform is compatible with commercially available high-density MEAs and requires no custom equipment, rendering the findings generalizable and accessible.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Precise control of pH values at electrode interfaces enables the systematic investigation of pH-dependent processes by electrochemical means. In this work, we employed high-density complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs) as miniaturized systems to induce and confine electrochemical reactions in areas corresponding to the pitch of single electrodes (17.5 μm). First, we present a strategy for generating localized pH patterns on the surface of the CMOS MEA with unprecedented spatial resolution. Leveraging the versatile routing capabilities of the switch matrix beneath the CMOS MEA, we created arbitrary combinations of anodic and cathodic electrodes and hence pH patterns. Moreover, we utilized the system to produce polymeric surface patterns by additive and subtractive methods. For additive patterning, we controlled the in situ formation of polydopamine at the microelectrode surface through oxidation of free dopamine above a threshold pH > 8.5. For subtractive patterning, we removed cell-adhesive poly-L-lysine from the electrode surface and backfilled the voids with antifouling polymers. Such polymers were chosen to provide a proof-of-concept application of controlling neuronal growth via electrochemically-induced patterns on the CMOS MEA surface. Importantly, our platform is compatible with commercially available high-density MEAs and requires no custom equipment, rendering the findings generalizable and accessible. |
 | Metto, Abigael C; Telgkamp, Petra; McLane-Svoboda, Autumn K; Gilad, Assaf A; Pelled, Galit Brain Research, 2023. @article{Metto2023, title = {Closed-loop neurostimulation via expression of magnetogenetics-sensitive protein in inhibitory neurons leads to reduction of seizure activity in a rat model of epilepsy}, author = {Abigael C. Metto and Petra Telgkamp and Autumn K. McLane-Svoboda and Assaf A. Gilad and Galit Pelled}, url = {https://www.sciencedirect.com/science/article/pii/S0006899323003621}, doi = {https://doi.org/10.1016/j.brainres.2023.148591}, year = {2023}, date = {2023-09-24}, journal = {Brain Research}, abstract = {On-demand neurostimulation has shown success in epilepsy patients with pharmacoresistant seizures. Seizures produce magnetic fields that can be recorded using magnetoencephalography. We developed a new closed-loop approach to control seizure activity based on magnetogenetics using the electromagnetic perceptive gene (EPG) that encodes a protein that responds to magnetic fields. The EPG transgene was expressed in inhibitory interneurons under the hDlx promoter and kainic acid was used to induce acute seizures. In vivo electrophysiological signals were recorded. We found that hDlx EPG rats exhibited a significant delay in the onset of first seizure (1142.72 ± 186.35 s) compared to controls (644.03 ± 15.06 s) and significantly less seizures (4.11 ± 1.03) compared to controls (8.33 ± 1.58). These preliminary findings suggest that on-demand activation of EPG expressed in inhibitory interneurons suppresses seizure activity, and magnetogenetics via EPG may be an effective strategy to alleviate seizure severity in a closed-loop, and cell-specific fashion.}, keywords = {}, pubstate = {published}, tppubtype = {article} } On-demand neurostimulation has shown success in epilepsy patients with pharmacoresistant seizures. Seizures produce magnetic fields that can be recorded using magnetoencephalography. We developed a new closed-loop approach to control seizure activity based on magnetogenetics using the electromagnetic perceptive gene (EPG) that encodes a protein that responds to magnetic fields. The EPG transgene was expressed in inhibitory interneurons under the hDlx promoter and kainic acid was used to induce acute seizures. In vivo electrophysiological signals were recorded. We found that hDlx EPG rats exhibited a significant delay in the onset of first seizure (1142.72 ± 186.35 s) compared to controls (644.03 ± 15.06 s) and significantly less seizures (4.11 ± 1.03) compared to controls (8.33 ± 1.58). These preliminary findings suggest that on-demand activation of EPG expressed in inhibitory interneurons suppresses seizure activity, and magnetogenetics via EPG may be an effective strategy to alleviate seizure severity in a closed-loop, and cell-specific fashion. |
| Levi, Timothee; Beaubois, Romain; Cheslet, Jérémy; Duenki, Tomoya; Khoyratee, Farad; Branchereau, Pascal; Ikeuchi, Yoshiho BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network Journal Article Research Square, 2023. @article{Levi2023, title = {BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network}, author = {Timothee Levi and Romain Beaubois and Jérémy Cheslet and Tomoya Duenki and Farad Khoyratee and Pascal Branchereau and Yoshiho Ikeuchi}, url = {https://www.researchsquare.com}, doi = {10.21203/rs.3.rs-3191285/v1}, year = {2023}, date = {2023-09-15}, journal = {Research Square}, abstract = {Characterization and modeling of biological neural networks is a field opening to major advances in our understanding of the mechanisms governing the functioning of the brain and the different pathologies that can affect it. Recent researches in bioelectronics and neuromorphic engineering lead to the design of the new generation of neuroprosthesis. Here we show a novel real-time, biomimetic and energy-efficient neural network for bio-hybrid experiments and parallel emulation. This novel system is used to investigate and reproduce neural network dynamics. The setup is running on a digital platform using a System on Chip (SoC) featuring both Programmable Logic (PL) and processors in a Processing System (PS) part. The FPGA part is computing the biomimetic and real-time electrical activities of Hodgkin-Huxley neural network while the processors handle monitoring and communication. New methods of resource and power optimization has been applied to the FPGA to allow detailed neuron modeling with synapses showing short term plasticity. The system is validated by comparison with biological data and model. We also demonstrate the feasibility of bio-hybrid experiments with different bio-physical interface and different biological cells. The complete setup achieves communication with a fully flexible real-time device thus constituting a step towards neuromorphic-based neuroprosthesis for bioelectrical therapeutics.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Characterization and modeling of biological neural networks is a field opening to major advances in our understanding of the mechanisms governing the functioning of the brain and the different pathologies that can affect it. Recent researches in bioelectronics and neuromorphic engineering lead to the design of the new generation of neuroprosthesis. Here we show a novel real-time, biomimetic and energy-efficient neural network for bio-hybrid experiments and parallel emulation. This novel system is used to investigate and reproduce neural network dynamics. The setup is running on a digital platform using a System on Chip (SoC) featuring both Programmable Logic (PL) and processors in a Processing System (PS) part. The FPGA part is computing the biomimetic and real-time electrical activities of Hodgkin-Huxley neural network while the processors handle monitoring and communication. New methods of resource and power optimization has been applied to the FPGA to allow detailed neuron modeling with synapses showing short term plasticity. The system is validated by comparison with biological data and model. We also demonstrate the feasibility of bio-hybrid experiments with different bio-physical interface and different biological cells. The complete setup achieves communication with a fully flexible real-time device thus constituting a step towards neuromorphic-based neuroprosthesis for bioelectrical therapeutics. |
| Silverman, Jill L; Fenton, Timothy; Haouchine, Olivia; Hallam, Elizabeth; Smith, Emily; Jackson, Kiya; Rahbarian, Darlene; Canales, Cesar; Adhikari, Anna; Nord, Alex; Ben-Shalom, Roy Hyperexcitability and translational phenotypes in a preclinical model of SYNGAP1mutations Journal Article Research Square, 2023. @article{Silverman2023, title = {Hyperexcitability and translational phenotypes in a preclinical model of SYNGAP1mutations}, author = {Jill L. Silverman and Timothy Fenton and Olivia Haouchine and Elizabeth Hallam and Emily Smith and Kiya Jackson and Darlene Rahbarian and Cesar Canales and Anna Adhikari and Alex Nord and Roy Ben-Shalom}, url = {https://www.researchsquare.com/article/rs-3246655/v1}, doi = {https://doi.org/10.21203/rs.3.rs-3246655/v1}, year = {2023}, date = {2023-09-13}, journal = {Research Square}, abstract = {SYNGAP1is a critical gene for neuronal development, synaptic structure, and function. Although rare, the disruption of SYNGAP1directly causes a genetically identi able neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability. Without functional SynGAP1 protein, patients present with intellectual disability, motor impairments, and epilepsy. Previous work using mouse models with a variety of germline and conditional mutations has helped delineate SynGAP1’s critical roles in neuronal structure and function, as well as key biochemical signaling pathways essential to synapse integrity. Homozygous loss of SYNGAP1is embryonically lethal. Heterozygous mutations of SynGAP1result in a broad range of phenotypes including increased locomotor activity, impaired working spatial memory, impaired cued fear memory, and increased stereotypic behavior. Ourinvivofunctional data, using the original germline mutation mouse line from the Huganir laboratory, corroborated robust hyperactivity and learning and memory de cits. Here, we describe impairments in the translational biomarker domain of sleep, characterized using neurophysiological data collected with wireless telemetric electroencephalography (EEG). We discoveredSyngap1+/− mice exhibited elevated spike trains in both number and duration, in addition to elevated power, most notably in the delta power band. Primary neurons fromSyngap1+/− mice displayed increased network ring activity, greater spikes per burst, and shorter inter-burst intervals between peaks using high density micro-electrode arrays (HD-MEA). This work is translational, innovative, and highly signi cant as it outlines functional impairments in Syngap1mutant mice. Simultaneously, the work utilized untethered, wireless neurophysiology that can discover potential biomarkers of Syngap1RID, for clinical trials, as it has done with other NDDs. Our work is substantial forward progress toward translational work for SynGAP1R-ID as it bridges in-vitroelectrophysiological neuronal activity and function with invivoneurophysiological brain activity and function. These data elucidate multiple quantitative, translational biomarkers invivoand invitrofor the development of treatments for SYNGAP1-related intellectual disability.}, keywords = {}, pubstate = {published}, tppubtype = {article} } SYNGAP1is a critical gene for neuronal development, synaptic structure, and function. Although rare, the disruption of SYNGAP1directly causes a genetically identi able neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability. Without functional SynGAP1 protein, patients present with intellectual disability, motor impairments, and epilepsy. Previous work using mouse models with a variety of germline and conditional mutations has helped delineate SynGAP1’s critical roles in neuronal structure and function, as well as key biochemical signaling pathways essential to synapse integrity. Homozygous loss of SYNGAP1is embryonically lethal. Heterozygous mutations of SynGAP1result in a broad range of phenotypes including increased locomotor activity, impaired working spatial memory, impaired cued fear memory, and increased stereotypic behavior. Ourinvivofunctional data, using the original germline mutation mouse line from the Huganir laboratory, corroborated robust hyperactivity and learning and memory de cits. Here, we describe impairments in the translational biomarker domain of sleep, characterized using neurophysiological data collected with wireless telemetric electroencephalography (EEG). We discoveredSyngap1+/− mice exhibited elevated spike trains in both number and duration, in addition to elevated power, most notably in the delta power band. Primary neurons fromSyngap1+/− mice displayed increased network ring activity, greater spikes per burst, and shorter inter-burst intervals between peaks using high density micro-electrode arrays (HD-MEA). This work is translational, innovative, and highly signi cant as it outlines functional impairments in Syngap1mutant mice. Simultaneously, the work utilized untethered, wireless neurophysiology that can discover potential biomarkers of Syngap1RID, for clinical trials, as it has done with other NDDs. Our work is substantial forward progress toward translational work for SynGAP1R-ID as it bridges in-vitroelectrophysiological neuronal activity and function with invivoneurophysiological brain activity and function. These data elucidate multiple quantitative, translational biomarkers invivoand invitrofor the development of treatments for SYNGAP1-related intellectual disability. |
 | Habibollahi, Forough; Kagan, Brett J; Burkitt, Anthony N; French, Chris Critical dynamics arise during structured information presentation within embodied in vitro neuronal networks Journal Article Nature Communications, 2023. @article{Habibollahi2023, title = {Critical dynamics arise during structured information presentation within embodied in vitro neuronal networks}, author = {Forough Habibollahi and Brett J. Kagan and Anthony N. Burkitt and Chris French }, url = {https://www.nature.com/articles/s41467-023-41020-3}, doi = {https://doi.org/10.1038/s41467-023-41020-3}, year = {2023}, date = {2023-08-30}, journal = {Nature Communications}, abstract = {Understanding how brains process information is an incredibly difficult task. Amongst the metrics characterising information processing in the brain, observations of dynamic near-critical states have generated significant interest. However, theoretical and experimental limitations associated with human and animal models have precluded a definite answer about when and why neural criticality arises with links from attention, to cognition, and even to consciousness. To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of ‘Pong’ to demonstrate Synthetic Biological Intelligence (SBI). We demonstrate that critical dynamics emerge when neural networks receive task-related structured sensory input, reorganizing the system to a near-critical state. Additionally, better task performance correlated with proximity to critical dynamics. However, criticality alone is insufficient for a neuronal network to demonstrate learning in the absence of additional information regarding the consequences of previous actions. These findings offer compelling support that neural criticality arises as a base feature of incoming structured information processing without the need for higher order cognition.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Understanding how brains process information is an incredibly difficult task. Amongst the metrics characterising information processing in the brain, observations of dynamic near-critical states have generated significant interest. However, theoretical and experimental limitations associated with human and animal models have precluded a definite answer about when and why neural criticality arises with links from attention, to cognition, and even to consciousness. To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of ‘Pong’ to demonstrate Synthetic Biological Intelligence (SBI). We demonstrate that critical dynamics emerge when neural networks receive task-related structured sensory input, reorganizing the system to a near-critical state. Additionally, better task performance correlated with proximity to critical dynamics. However, criticality alone is insufficient for a neuronal network to demonstrate learning in the absence of additional information regarding the consequences of previous actions. These findings offer compelling support that neural criticality arises as a base feature of incoming structured information processing without the need for higher order cognition. |
 | Radivojevic, Milos; Punga, Anna Rostedt Functional imaging of conduction dynamics in cortical and spinal axons Journal Article eLife, 2023. @article{Radivojevic2023_2, title = {Functional imaging of conduction dynamics in cortical and spinal axons}, author = {Milos Radivojevic and Anna Rostedt Punga}, url = {https://elifesciences.org/articles/86512}, doi = {https://doi.org/10.7554/eLife.86512}, year = {2023}, date = {2023-08-22}, journal = {eLife}, abstract = {Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here, we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-cm-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 m of cortical and spinal axons in total and found specific features in their structure and function.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here, we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-cm-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 m of cortical and spinal axons in total and found specific features in their structure and function. |
 | Duru, Jens; Maurer, Benedikt; Doran, Ciara Giles; Jelitto, Robert; Küchler, Joël; Ihle, Stephan J; Ruff, Tobias; John, Robert; Genocchi, Barbara; Vörös, János Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays Journal Article Biosensors and Bioelectronics, 2023. @article{Duru2023b, title = {Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays}, author = {Jens Duru and Benedikt Maurer and Ciara Giles Doran and Robert Jelitto and Joël Küchler and Stephan J. Ihle and Tobias Ruff and Robert John and Barbara Genocchi and János Vörös }, url = {https://www.sciencedirect.com/science/article/pii/S095656632300533X?via%3Dihub}, doi = {https://doi.org/10.1016/j.bios.2023.115591}, year = {2023}, date = {2023-08-18}, journal = {Biosensors and Bioelectronics}, abstract = {Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks' early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks' early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation. |
 | Miyahara, Yuki; Shimba, Kenta; Kotani, Kiyoshi; Jimbo, Yasuhiko IEEE EMBC 2023 2023. @conference{Miyahara2023, title = {Development of a Hypersensitivity Evaluation Method for Cultured Sensory Neurons Using Electrical Activity Recording}, author = {Yuki Miyahara and Kenta Shimba and Kiyoshi Kotani and Yasuhiko Jimbo}, url = {https://arinex.com.au/EMBC/pdf/full-paper_363.pdf}, year = {2023}, date = {2023-07-27}, organization = {IEEE EMBC 2023}, abstract = {Investigation of hypersensitivity caused by peripheral sensitization progression is important for developing novel pain treatments. Existing methods cannot record plastic changes in neuronal activity because they occur over a few days. We aimed to establish an efficient method to evaluate neuronal activity alterations caused by peripheral sensitization on highdensity microelectrode arrays (HD-MEAs) which can record neuronal activity for a long time. Rat dorsal root ganglion (DRG) neurons were dissected from rat embryos and cultured on HDMEAs. DRG neurons were labeled with NeuO, live staining dye. Neurons were detected with the fluorescence signal and electrodes were selected with the fluorescence images. The number of DRG neurons, whose activity were recorded, detected based on fluorescence observation was five times greater than that based on neuronal activity. Analysis of changes in neuronal activity observed in pharmacological stimulation experiments suggested that substance P induced peripheral sensitization and enhanced capsaicin sensitivity. In addition, results of immunofluorescence staining suggested that peripheral sensitization occurred mostly in neurons that co-expressed transient receptor potential vanilloid 1 (TRPV1) and neurokinin 1 receptor (NK1R). In conclusion, we established an efficient method for assessing the effects of peripheral sensitization on DRG neurons cultured on HD-MEAs.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } Investigation of hypersensitivity caused by peripheral sensitization progression is important for developing novel pain treatments. Existing methods cannot record plastic changes in neuronal activity because they occur over a few days. We aimed to establish an efficient method to evaluate neuronal activity alterations caused by peripheral sensitization on highdensity microelectrode arrays (HD-MEAs) which can record neuronal activity for a long time. Rat dorsal root ganglion (DRG) neurons were dissected from rat embryos and cultured on HDMEAs. DRG neurons were labeled with NeuO, live staining dye. Neurons were detected with the fluorescence signal and electrodes were selected with the fluorescence images. The number of DRG neurons, whose activity were recorded, detected based on fluorescence observation was five times greater than that based on neuronal activity. Analysis of changes in neuronal activity observed in pharmacological stimulation experiments suggested that substance P induced peripheral sensitization and enhanced capsaicin sensitivity. In addition, results of immunofluorescence staining suggested that peripheral sensitization occurred mostly in neurons that co-expressed transient receptor potential vanilloid 1 (TRPV1) and neurokinin 1 receptor (NK1R). In conclusion, we established an efficient method for assessing the effects of peripheral sensitization on DRG neurons cultured on HD-MEAs. |
| Akita, Dai; Suwa, Eisuke; Ikeda, Narumitsu; Takahashi, Hirokazu Neural Activity and Information Processing Capacity of Neuronal Culture Conference IEEE EMBC 2023 2023. @conference{Akita2023, title = {Neural Activity and Information Processing Capacity of Neuronal Culture}, author = {Dai Akita and Eisuke Suwa and Narumitsu Ikeda and Hirokazu Takahashi}, url = {https://arinex.com.au/EMBC/pdf/full-paper_654.pdf}, year = {2023}, date = {2023-07-27}, organization = {IEEE EMBC 2023}, abstract = {Whether artificial or living, neural networks perform tremendously diverse kinds of information processing, such as visual feature extraction, speech recognition, motor control, and so on. Some studies have evaluated the computational ability of living neural networks based on the performances of specific tasks, yet could not comprehensively grasp the versatile ability. In this study, we investigated dissociated culture of neurons as a physical reservoir, which generates diverse outputs through linear regression, or readout, of the dynamical states. Based on the theory of reservoir computing, the potential computational capabilities of neuronal culture were evaluated by the information processing capacity (IPC), which indicates how a target function can be achieved from the given dynamics. As a result, we found that the neuronal culture exhibited significant IPC and that IPC varied with the inter-step interval (ISI), the time step of reservoir computing. The cultures exhibited a memory capacity of 10 time steps for computation, and this memory capacity decayed at an ISI of 5 ms or shorter. In addition, the IPC had a significant positive correlation with the intensity of the evoked response relative to spontaneous activity. The multiple regression model with evoked response and ISI showed the positive effect of evoked response and 30 ms as the best ISI for IPC. These results suggest that the distinct evoked response and the optimal time step to interact with the neuronal culture are key factors to uncover computational resources from the neuronal system.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } Whether artificial or living, neural networks perform tremendously diverse kinds of information processing, such as visual feature extraction, speech recognition, motor control, and so on. Some studies have evaluated the computational ability of living neural networks based on the performances of specific tasks, yet could not comprehensively grasp the versatile ability. In this study, we investigated dissociated culture of neurons as a physical reservoir, which generates diverse outputs through linear regression, or readout, of the dynamical states. Based on the theory of reservoir computing, the potential computational capabilities of neuronal culture were evaluated by the information processing capacity (IPC), which indicates how a target function can be achieved from the given dynamics. As a result, we found that the neuronal culture exhibited significant IPC and that IPC varied with the inter-step interval (ISI), the time step of reservoir computing. The cultures exhibited a memory capacity of 10 time steps for computation, and this memory capacity decayed at an ISI of 5 ms or shorter. In addition, the IPC had a significant positive correlation with the intensity of the evoked response relative to spontaneous activity. The multiple regression model with evoked response and ISI showed the positive effect of evoked response and 30 ms as the best ISI for IPC. These results suggest that the distinct evoked response and the optimal time step to interact with the neuronal culture are key factors to uncover computational resources from the neuronal system. |
 | Yamamoto, Hideaki; Hirano-Iwata, Ayumi; Sato, Shigeo Microfluidic technologies for reconstituting neuronal network functions in vitro Journal Article JSAP Review, 2023. @article{Yamamoto2023, title = {Microfluidic technologies for reconstituting neuronal network functions in vitro}, author = {Hideaki Yamamoto and Ayumi Hirano-Iwata and Shigeo Sato}, url = {https://www.jstage.jst.go.jp/article/oubutsu/92/5/92_278/_article/-char/en}, doi = {10.11470/oubutsu.92.5_278}, year = {2023}, date = {2023-07-06}, journal = {JSAP Review}, abstract = {The structure and function of complex neuronal networks in the brain can be partially reconstituted in vitro by integrating cell culture and microfluidic device technologies. In this report, we review our recent studies on developing microfluidic devices to reconstitute small neuronal networks bearing a modular structure, which is a canonical structure found in the nervous systems of animals. We also describe the process of recording functional activity from the reconstituted neuronal networks. These fundamental technologies offer novel tools for investigating structure–function relationships in living neuronal networks and exploring the physical basis of biological computing in the brain.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The structure and function of complex neuronal networks in the brain can be partially reconstituted in vitro by integrating cell culture and microfluidic device technologies. In this report, we review our recent studies on developing microfluidic devices to reconstitute small neuronal networks bearing a modular structure, which is a canonical structure found in the nervous systems of animals. We also describe the process of recording functional activity from the reconstituted neuronal networks. These fundamental technologies offer novel tools for investigating structure–function relationships in living neuronal networks and exploring the physical basis of biological computing in the brain. |
 | McSweeney, Danny; English, Jay; Howell, Ethan; Ribbe, Fumiko; Pak, ChangHui Methods in Molecular Biology, 2023. @inbook{McSweeney2023, title = {Measuring Neuronal Network Activity Using Human Induced Neuronal Cells - Stem Cell-Based Neural Model Systems for Brain Disorders}, author = {Danny McSweeney and Jay English and Ethan Howell and Fumiko Ribbe and ChangHui Pak}, url = {https://link.springer.com/protocol/10.1007/978-1-0716-3287-1_19}, year = {2023}, date = {2023-06-11}, publisher = {Methods in Molecular Biology}, abstract = {Synchronous firing of neurons, often referred to as “network activity” or “network bursting,” is an indication of a mature and synaptically connected network of neurons. We previously reported this phenomenon in 2D human neuronal in vitro models (McSweeney et al. iScience 25:105187, 2022). Using induced neurons (iNs) differentiated from human pluripotent stem cells (hPSCs) coupled with high-density microelectrodes arrays (HD-MEAs), we probed the underlying patterns of neuronal activity and found irregularities in network signaling across mutant states (McSweeney et al. iScience 25:105187, 2022). Here, we describe methods for plating cortical excitatory iNs differentiated from hPSCs on top of HD-MEAs and culturing iNs to maturity, examples of representative human wild-type Ngn2-iN data, and troubleshooting tips and tricks for the experimenter interested in integrating HD-MEAs into one’s research approach.}, keywords = {}, pubstate = {published}, tppubtype = {inbook} } Synchronous firing of neurons, often referred to as “network activity” or “network bursting,” is an indication of a mature and synaptically connected network of neurons. We previously reported this phenomenon in 2D human neuronal in vitro models (McSweeney et al. iScience 25:105187, 2022). Using induced neurons (iNs) differentiated from human pluripotent stem cells (hPSCs) coupled with high-density microelectrodes arrays (HD-MEAs), we probed the underlying patterns of neuronal activity and found irregularities in network signaling across mutant states (McSweeney et al. iScience 25:105187, 2022). Here, we describe methods for plating cortical excitatory iNs differentiated from hPSCs on top of HD-MEAs and culturing iNs to maturity, examples of representative human wild-type Ngn2-iN data, and troubleshooting tips and tricks for the experimenter interested in integrating HD-MEAs into one’s research approach. |
 | Zhao, Eric T; Hull, Jacob M; Hemed, Nofar Mintz; Ulusan, Hasan; Bartram, Julian; Zhang, Anqi; Wang, Pingyu; Pham, Albert; Silvia Ronchi, John Huguenard R; Hierlemann, Andreas; Melosh, Nicholas A A CMOS-based highly scalable flexible neural electrode interface Journal Article Science Advances, 2023. @article{Zhao2023, title = {A CMOS-based highly scalable flexible neural electrode interface}, author = {Eric T. Zhao and Jacob M. Hull and Nofar Mintz Hemed and Hasan Ulusan and Julian Bartram and Anqi Zhang and Pingyu Wang and Albert Pham and Silvia Ronchi, John R. Huguenard and Andreas Hierlemann and Nicholas A. Melosh}, url = {https://www.science.org/doi/10.1126/sciadv.adf9524}, doi = {DOI: 10.1126/sciadv.adf9524}, year = {2023}, date = {2023-06-07}, journal = {Science Advances}, abstract = {Perception, thoughts, and actions are encoded by the coordinated activity of large neuronal populations spread over large areas. However, existing electrophysiological devices are limited by their scalability in capturing this cortex-wide activity. Here, we developed an electrode connector based on an ultra-conformable thin-film electrode array that self-assembles onto silicon microelectrode arrays enabling multithousand channel counts at a millimeter scale. The interconnects are formed using microfabricated electrode pads suspended by thin support arms, termed Flex2Chip. Capillary-assisted assembly drives the pads to deform toward the chip surface, and van der Waals forces maintain this deformation, establishing Ohmic contact. Flex2Chip arrays successfully measured extracellular action potentials ex vivo and resolved micrometer scale seizure propagation trajectories in epileptic mice. We find that seizure dynamics in absence epilepsy in the Scn8a+/− model do not have constant propagation trajectories.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Perception, thoughts, and actions are encoded by the coordinated activity of large neuronal populations spread over large areas. However, existing electrophysiological devices are limited by their scalability in capturing this cortex-wide activity. Here, we developed an electrode connector based on an ultra-conformable thin-film electrode array that self-assembles onto silicon microelectrode arrays enabling multithousand channel counts at a millimeter scale. The interconnects are formed using microfabricated electrode pads suspended by thin support arms, termed Flex2Chip. Capillary-assisted assembly drives the pads to deform toward the chip surface, and van der Waals forces maintain this deformation, establishing Ohmic contact. Flex2Chip arrays successfully measured extracellular action potentials ex vivo and resolved micrometer scale seizure propagation trajectories in epileptic mice. We find that seizure dynamics in absence epilepsy in the Scn8a+/− model do not have constant propagation trajectories. |
 | Girardi, Gregory; Zumpano, Danielle; Goshi, Noah; Raybould, Helen; Seker, Erkin Cultured Vagal Afferent Neurons as Sensors for Intestinal Effector Molecules Journal Article biosensors, 2023. @article{Girardi2023, title = {Cultured Vagal Afferent Neurons as Sensors for Intestinal Effector Molecules}, author = {Gregory Girardi and Danielle Zumpano and Noah Goshi and Helen Raybould and Erkin Seker}, url = {https://www.mdpi.com/2079-6374/13/6/601}, doi = {10.3390/bios13060601}, year = {2023}, date = {2023-05-31}, journal = {biosensors}, abstract = {The gut–brain axis embodies the bi-directional communication between the gastrointestinal tract and the central nervous system (CNS), where vagal afferent neurons (VANs) serve as sensors for a variety of gut-derived signals. The gut is colonized by a large and diverse population of microorganisms that communicate via small (effector) molecules, which also act on the VAN terminals situated in the gut viscera and consequently influence many CNS processes. However, the convoluted in vivo environment makes it difficult to study the causative impact of the effector molecules on VAN activation or desensitization. Here, we report on a VAN culture and its proof-of-principle demonstration as a cell-based sensor to monitor the influence of gastrointestinal effector molecules on neuronal behavior. We initially compared the effect of surface coatings (poly-L-lysine vs. Matrigel) and culture media composition (serum vs. growth factor supplement) on neurite growth as a surrogate of VAN regeneration following tissue harvesting, where the Matrigel coating, but not the media composition, played a significant role in the increased neurite growth. We then used both live-cell calcium imaging and extracellular electrophysiological recordings to show that the VANs responded to classical effector molecules of endogenous and exogenous origin (cholecystokinin serotonin and capsaicin) in a complex fashion. We expect this study to enable platforms for screening various effector molecules and their influence on VAN activity, assessed by their information-rich electrophysiological fingerprints.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The gut–brain axis embodies the bi-directional communication between the gastrointestinal tract and the central nervous system (CNS), where vagal afferent neurons (VANs) serve as sensors for a variety of gut-derived signals. The gut is colonized by a large and diverse population of microorganisms that communicate via small (effector) molecules, which also act on the VAN terminals situated in the gut viscera and consequently influence many CNS processes. However, the convoluted in vivo environment makes it difficult to study the causative impact of the effector molecules on VAN activation or desensitization. Here, we report on a VAN culture and its proof-of-principle demonstration as a cell-based sensor to monitor the influence of gastrointestinal effector molecules on neuronal behavior. We initially compared the effect of surface coatings (poly-L-lysine vs. Matrigel) and culture media composition (serum vs. growth factor supplement) on neurite growth as a surrogate of VAN regeneration following tissue harvesting, where the Matrigel coating, but not the media composition, played a significant role in the increased neurite growth. We then used both live-cell calcium imaging and extracellular electrophysiological recordings to show that the VANs responded to classical effector molecules of endogenous and exogenous origin (cholecystokinin serotonin and capsaicin) in a complex fashion. We expect this study to enable platforms for screening various effector molecules and their influence on VAN activity, assessed by their information-rich electrophysiological fingerprints. |
| Bartram, Julian; Franke, Felix; Kumar, Sreedhar Saseendran; Buccino, Alessio Paolo; Xue, Xiaohan; Gänswein, Tobias; Schröter, Manuel; Kim, Taehoon; Kasuba, Krishna Chaitanya; Hierlemann, Andreas Parallel reconstruction of the excitatory and inhibitory inputs received by single neurons reveals the synaptic basis of recurrent spiking Journal Article eLife, 2023. @article{Bartram2023b, title = {Parallel reconstruction of the excitatory and inhibitory inputs received by single neurons reveals the synaptic basis of recurrent spiking}, author = {Julian Bartram and Felix Franke and Sreedhar Saseendran Kumar and Alessio Paolo Buccino and Xiaohan Xue and Tobias Gänswein and Manuel Schröter and Taehoon Kim and Krishna Chaitanya Kasuba and Andreas Hierlemann}, url = {https://elifesciences.org/reviewed-preprints/86820}, doi = {10.7554/eLife.86820}, year = {2023}, date = {2023-05-17}, journal = {eLife}, abstract = {Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between the synaptic input patterns and the spiking output of individual neurons remains largely unresolved. Here, we developed, validated and applied a novel in vitro experimental platform and analytical procedures that provide – for individual neurons – simultaneous excitatory and inhibitory synaptic activity estimates during recurrent network activity. Our approach combines whole-network high-density microelectrode array (HD-MEA) recordings from rat neuronal cultures with patch clamping and enables a comprehensive mapping and characterization of active incoming connections to single postsynaptic neurons. We found that, during network states with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided precisely with the maxima of fast fluctuations in the input E/I ratio. These spike-associated E/I ratio escalations were largely due to a rapid bidirectional change in synaptic inhibition that was modulated by the network-activity level. Our approach also uncovered the underlying circuit architecture and we show that individual neurons received a few key inhibitory connections – often from special hub neurons – that were instrumental in controlling postsynaptic spiking. Balanced network theory predicts dynamical regimes governed by small and rapid input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of cortical networks in general.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between the synaptic input patterns and the spiking output of individual neurons remains largely unresolved. Here, we developed, validated and applied a novel in vitro experimental platform and analytical procedures that provide – for individual neurons – simultaneous excitatory and inhibitory synaptic activity estimates during recurrent network activity. Our approach combines whole-network high-density microelectrode array (HD-MEA) recordings from rat neuronal cultures with patch clamping and enables a comprehensive mapping and characterization of active incoming connections to single postsynaptic neurons. We found that, during network states with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided precisely with the maxima of fast fluctuations in the input E/I ratio. These spike-associated E/I ratio escalations were largely due to a rapid bidirectional change in synaptic inhibition that was modulated by the network-activity level. Our approach also uncovered the underlying circuit architecture and we show that individual neurons received a few key inhibitory connections – often from special hub neurons – that were instrumental in controlling postsynaptic spiking. Balanced network theory predicts dynamical regimes governed by small and rapid input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of cortical networks in general. |
 | Duru, Jens; Maurer, Benedikt; Doran, Ciara Giles; Jelitto, Robert; Küchler, Joël; Ihle, Stephan J; Ruff, Tobias; John, Robert; Genocchi, Barbara; Vörös, János Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays Journal Article SSRN, 2023. @article{Duru2023, title = {Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays}, author = {Jens Duru and Benedikt Maurer and Ciara Giles Doran and Robert Jelitto and Joël Küchler and Stephan J. Ihle and Tobias Ruff and Robert John and Barbara Genocchi and János Vörös}, url = {https://www.ssrn.com/abstract=4427959}, doi = {DOI: 10.2139/ssrn.4427959}, year = {2023}, date = {2023-04-24}, journal = {SSRN}, abstract = {Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks’ early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks’ early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation. |
 | Xu, He Jax; Yao, Yao; Yao, Fenyong; Chen, Jiehui; Li, Meishi; Yang, Xianfa; Li, Sheng; Lu, Fangru; Hu, Ping; He, Shuijin; Peng, Guangdun; Jing, Naihe Generation of functional posterior spinal motor neurons from hPSCs-derived human spinal cord neural progenitor cells Journal Article Cell Regeneration, 2023. @article{Xu2023, title = {Generation of functional posterior spinal motor neurons from hPSCs-derived human spinal cord neural progenitor cells}, author = {He Jax Xu and Yao Yao and Fenyong Yao and Jiehui Chen and Meishi Li and Xianfa Yang and Sheng Li and Fangru Lu and Ping Hu and Shuijin He and Guangdun Peng and Naihe Jing}, url = {https://cellregeneration.springeropen.com/articles/10.1186/s13619-023-00159-6}, doi = {10.1186/s13619-023-00159-6}, year = {2023}, date = {2023-03-23}, journal = {Cell Regeneration}, abstract = {Spinal motor neurons deficiency results in a series of devastating disorders such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA) and spinal cord injury (SCI). These disorders are currently incurable, while human pluripotent stem cells (hPSCs)-derived spinal motor neurons are promising but suffered from inappropriate regional identity and functional immaturity for the study and treatment of posterior spinal cord related injuries. In this study, we have established human spinal cord neural progenitor cells (hSCNPCs) via hPSCs differentiated neuromesodermal progenitors (NMPs) and demonstrated the hSCNPCs can be continuously expanded up to 40 passages. hSCNPCs can be rapidly differentiated into posterior spinal motor neurons with high efficiency. The functional maturity has been examined in detail. Moreover, a co-culture scheme which is compatible for both neural and muscular differentiation is developed to mimic the neuromuscular junction (NMJ) formation in vitro. Together, these studies highlight the potential avenues for generating clinically relevant spinal motor neurons and modeling neuromuscular diseases through our defined hSCNPCs.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Spinal motor neurons deficiency results in a series of devastating disorders such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA) and spinal cord injury (SCI). These disorders are currently incurable, while human pluripotent stem cells (hPSCs)-derived spinal motor neurons are promising but suffered from inappropriate regional identity and functional immaturity for the study and treatment of posterior spinal cord related injuries. In this study, we have established human spinal cord neural progenitor cells (hSCNPCs) via hPSCs differentiated neuromesodermal progenitors (NMPs) and demonstrated the hSCNPCs can be continuously expanded up to 40 passages. hSCNPCs can be rapidly differentiated into posterior spinal motor neurons with high efficiency. The functional maturity has been examined in detail. Moreover, a co-culture scheme which is compatible for both neural and muscular differentiation is developed to mimic the neuromuscular junction (NMJ) formation in vitro. Together, these studies highlight the potential avenues for generating clinically relevant spinal motor neurons and modeling neuromuscular diseases through our defined hSCNPCs. |
| Radivojevic, Milos; Punga, Anna Rostedt Functional imaging of conduction dynamics in cortical and spinal axons Journal Article BioRxiv, 2023. @article{Radivojevic2023, title = {Functional imaging of conduction dynamics in cortical and spinal axons}, author = {Milos Radivojevic and Anna Rostedt Punga}, url = {https://www.biorxiv.org/content/10.1101/2023.02.28.530461v1}, doi = {https://doi.org/10.1101/2023.02.28.530461}, year = {2023}, date = {2023-03-01}, journal = {BioRxiv}, abstract = {Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-centimeter-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 meters of cortical and spinal axons in total and found specific features in their structure and function.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-centimeter-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 meters of cortical and spinal axons in total and found specific features in their structure and function. |
| Cai, Hongwei; Ao, Zheng; Tian, Chunhui; Wu, Zhuhao; Liu, Hongcheng; Tchieu, Jason; Gu, Mingxia; Mackie, Ken; and Guo, Feng Brain Organoid Computing for Artificial Intelligence Journal Article bioRxiv, 2023. @article{Cai2023, title = {Brain Organoid Computing for Artificial Intelligence}, author = {Hongwei Cai and Zheng Ao and Chunhui Tian and Zhuhao Wu and Hongcheng Liu and Jason Tchieu and Mingxia Gu and Ken Mackie and and Feng Guo}, url = {https://www.biorxiv.org/content/10.1101/2023.02.28.530502v1}, doi = {10.1101/2023.02.28.530502}, year = {2023}, date = {2023-03-01}, journal = {bioRxiv}, abstract = {Brain-inspired hardware emulates the structure and working principles of a biological brain and may address the hardware bottleneck for fast-growing artificial intelligence (AI). Current brain-inspired silicon chips are promising but still limit their power to fully mimic brain function for AI computing. Here, we develop Brainoware, living AI hardware that harnesses the computation power of 3D biological neural networks in a brain organoid. Brain-like 3D in vitro cultures compute by receiving and sending information via a multielectrode array. Applying spatiotemporal electrical stimulation, this approach not only exhibits nonlinear dynamics and fading memory properties but also learns from training data. Further experiments demonstrate real-world applications in solving non-linear equations. This approach may provide new insights into AI hardware. }, keywords = {}, pubstate = {published}, tppubtype = {article} } Brain-inspired hardware emulates the structure and working principles of a biological brain and may address the hardware bottleneck for fast-growing artificial intelligence (AI). Current brain-inspired silicon chips are promising but still limit their power to fully mimic brain function for AI computing. Here, we develop Brainoware, living AI hardware that harnesses the computation power of 3D biological neural networks in a brain organoid. Brain-like 3D in vitro cultures compute by receiving and sending information via a multielectrode array. Applying spatiotemporal electrical stimulation, this approach not only exhibits nonlinear dynamics and fading memory properties but also learns from training data. Further experiments demonstrate real-world applications in solving non-linear equations. This approach may provide new insights into AI hardware. |
 | Kim, Eunhee; Jeon, Sungwoong; Yang, Yoon-Sil; Jin, Chaewon; Kim, Jin-young; Oh, Yong- Seok; Rah, Jong-Cheol; and Choi, Hongsoo A Neurospheroid-Based Microrobot for Targeted Neural Connections in a Hippocampal Slice Journal Article Advanced Materials, 2023. @article{EunheeKim2023, title = {A Neurospheroid-Based Microrobot for Targeted Neural Connections in a Hippocampal Slice}, author = {Eunhee Kim and Sungwoong Jeon and Yoon-Sil Yang and Chaewon Jin and Jin-young Kim and Yong- Seok Oh and Jong-Cheol Rah and and Hongsoo Choi}, url = {https://onlinelibrary.wiley.com/doi/10.1002/adma.202208747?af=R}, doi = {https://doi.org/10.1002/adma.202208747}, year = {2023}, date = {2023-01-14}, journal = {Advanced Materials}, abstract = {Functional restoration by the re-establishment of cellular or neural connections remains a major challenge in targeted cell therapy and regenerative medicine. Recent advances in magnetically powered microrobots have shown potential for use in controlled and targeted cell therapy. In this study, a magnetic neurospheroid (Mag-Neurobot) that could form both structural and functional connections with an organotypic hippocampal slice (OHS) was assessed using an ex vivo model as a bridge toward in vivo application. The Mag-Neurobot consists of hippocampal neurons and superparamagnetic nanoparticles (SPIONs); it is precisely and skillfully manipulated by an external magnetic field. Furthermore, the results of patch-clamp recordings of hippocampal neurons indicated that neither the neuronal excitabilities nor the synaptic functions of SPION-loaded cells were significantly affected. Analysis of neural activity propagation using high-density multi-electrode arrays showed that the delivered Mag-Neurobot was functionally connected with the OHS. The applications of this study include functional verification for targeted cell delivery through the characterization of novel synaptic connections and the functionalities of transported and transplanted cells. The success of the Mag-Neurobot opens up new avenues of research and application; it offers a test platform for functional neural connections and neural regenerative processes through cell transplantation.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Functional restoration by the re-establishment of cellular or neural connections remains a major challenge in targeted cell therapy and regenerative medicine. Recent advances in magnetically powered microrobots have shown potential for use in controlled and targeted cell therapy. In this study, a magnetic neurospheroid (Mag-Neurobot) that could form both structural and functional connections with an organotypic hippocampal slice (OHS) was assessed using an ex vivo model as a bridge toward in vivo application. The Mag-Neurobot consists of hippocampal neurons and superparamagnetic nanoparticles (SPIONs); it is precisely and skillfully manipulated by an external magnetic field. Furthermore, the results of patch-clamp recordings of hippocampal neurons indicated that neither the neuronal excitabilities nor the synaptic functions of SPION-loaded cells were significantly affected. Analysis of neural activity propagation using high-density multi-electrode arrays showed that the delivered Mag-Neurobot was functionally connected with the OHS. The applications of this study include functional verification for targeted cell delivery through the characterization of novel synaptic connections and the functionalities of transported and transplanted cells. The success of the Mag-Neurobot opens up new avenues of research and application; it offers a test platform for functional neural connections and neural regenerative processes through cell transplantation. |
 | Sato, Yuya; Yamamoto, Hideaki; Kato, Hideyuki; Tanii, Takashi; Sato, Shigeo; Hirano-Iwata, Ayumi Microfluidic cell engineering on high-density microelectrode arrays for assessing structure-function relationships in living neuronal networks Journal Article Frontiers in Neuroscience, 2023. @article{Sato2023, title = {Microfluidic cell engineering on high-density microelectrode arrays for assessing structure-function relationships in living neuronal networks}, author = {Yuya Sato and Hideaki Yamamoto and Hideyuki Kato and Takashi Tanii and Shigeo Sato and Ayumi Hirano-Iwata}, url = {https://www.frontiersin.org/articles/10.3389/fnins.2022.943310/full}, doi = {doi: 10.3389/fnins.2022.943310}, year = {2023}, date = {2023-01-09}, journal = {Frontiers in Neuroscience}, 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 a 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 = {}, 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 a 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. |
 | Han, Xiaobo; Matsuda, Naoki; Ishibashi, Yuto; Odawara, Aoi; Takahashi, Sayuri; Tooi, Norie; Kinoshita, Koshi; Suzuki, Ikuro A functional neuron maturation device provides convenient application on microelectrode array for neural network measurement Journal Article Biomaterials Research, 2022. @article{Han2022, title = {A functional neuron maturation device provides convenient application on microelectrode array for neural network measurement}, author = {Xiaobo Han and Naoki Matsuda and Yuto Ishibashi and Aoi Odawara and Sayuri Takahashi and Norie Tooi and Koshi Kinoshita and Ikuro Suzuki }, url = {https://biomaterialsres.biomedcentral.com/articles/10.1186/s40824-022-00324-z}, doi = {https://doi.org/10.1186/s40824-022-00324-z}, year = {2022}, date = {2022-12-20}, journal = {Biomaterials Research}, abstract = {Background Microelectrode array (MEA) systems are valuable for in vitro assessment of neurotoxicity and drug efficiency. However, several difficulties such as protracted functional maturation and high experimental costs hinder the use of MEA analysis requiring human induced pluripotent stem cells (hiPSCs). Neural network functional parameters are also needed for in vitro to in vivo extrapolation. Methods In the present study, we produced a cost effective nanofiber culture platform, the SCAD device, for long-term culture of hiPSC-derived neurons and primary peripheral neurons. The notable advantage of SCAD device is convenient application on multiple MEA systems for neuron functional analysis. Results We showed that the SCAD device could promote functional maturation of cultured hiPSC-derived neurons, and neurons responded appropriately to convulsant agents. Furthermore, we successfully analyzed parameters for in vitro to in vivo extrapolation, i.e., low-frequency components and synaptic propagation velocity of the signal, potentially reflecting neural network functions from neurons cultured on SCAD device. Finally, we measured the axonal conduction velocity of peripheral neurons. Conclusions: Neurons cultured on SCAD devices might constitute a reliable in vitro platform to investigate neuron functions, drug efficacy and toxicity, and neuropathological mechanisms by MEA.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Background Microelectrode array (MEA) systems are valuable for in vitro assessment of neurotoxicity and drug efficiency. However, several difficulties such as protracted functional maturation and high experimental costs hinder the use of MEA analysis requiring human induced pluripotent stem cells (hiPSCs). Neural network functional parameters are also needed for in vitro to in vivo extrapolation. Methods In the present study, we produced a cost effective nanofiber culture platform, the SCAD device, for long-term culture of hiPSC-derived neurons and primary peripheral neurons. The notable advantage of SCAD device is convenient application on multiple MEA systems for neuron functional analysis. Results We showed that the SCAD device could promote functional maturation of cultured hiPSC-derived neurons, and neurons responded appropriately to convulsant agents. Furthermore, we successfully analyzed parameters for in vitro to in vivo extrapolation, i.e., low-frequency components and synaptic propagation velocity of the signal, potentially reflecting neural network functions from neurons cultured on SCAD device. Finally, we measured the axonal conduction velocity of peripheral neurons. Conclusions: Neurons cultured on SCAD devices might constitute a reliable in vitro platform to investigate neuron functions, drug efficacy and toxicity, and neuropathological mechanisms by MEA. |
 | Tran, Hoang-Dai; Shin, Min-Kyoung; Denman, Charlotte; Han, Run-Run; Kuhn, Bernd; Arbuthnott, Gordon; Jo, Junghyun Generation of Human Striatal-Midbrain Assembloids From Human Pluripotent Stem Cells to Model Alpha-Synuclein Propagation Journal Article Sneak Peek - Cell Press, 2022. @article{Tran2022, title = {Generation of Human Striatal-Midbrain Assembloids From Human Pluripotent Stem Cells to Model Alpha-Synuclein Propagation}, author = {Hoang-Dai Tran and Min-Kyoung Shin and Charlotte Denman and Run-Run Han and Bernd Kuhn and Gordon Arbuthnott and Junghyun Jo}, url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4288935}, doi = {http://dx.doi.org/10.2139/ssrn.4288935}, year = {2022}, date = {2022-12-05}, journal = {Sneak Peek - Cell Press}, abstract = {Animal models of the pathology of Parkinson’s disease (PD) have provided most of the treatments to date, but the disease is restricted to human patients. In vitro models using human pluripotent stem cell-derived neural organoids have provided improved access to study PD etiology. Here, we generated human striatal and midbrain organoids and assembled both regionalized neural organoids to form human striatal-midbrain assembloids (hSMAs), mimicking a part of basal ganglia. Both the nigrostriatal and striatonigral pathways are present and electrophysiologically active in the hSMAs. hSMA development in the presence of increased alpha-synuclein (α-syn) from SNCA overexpression, induced nigrostriatal system damage, which is typical of the disease. Using the α-syn-mKO2 reporter and bimolecular fluorescence complementation system, we demonstrated that fluorescent α-syn is transported from the striatal area tothe dopaminergic (DA) neurons of the midbrain area. Furthermore, insoluble α-syn aggregated over time in DA neurons similar to Lewy bodies in human patients. Such assembloids are a compelling new platform to develop novel PD therapeutic strategies.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Animal models of the pathology of Parkinson’s disease (PD) have provided most of the treatments to date, but the disease is restricted to human patients. In vitro models using human pluripotent stem cell-derived neural organoids have provided improved access to study PD etiology. Here, we generated human striatal and midbrain organoids and assembled both regionalized neural organoids to form human striatal-midbrain assembloids (hSMAs), mimicking a part of basal ganglia. Both the nigrostriatal and striatonigral pathways are present and electrophysiologically active in the hSMAs. hSMA development in the presence of increased alpha-synuclein (α-syn) from SNCA overexpression, induced nigrostriatal system damage, which is typical of the disease. Using the α-syn-mKO2 reporter and bimolecular fluorescence complementation system, we demonstrated that fluorescent α-syn is transported from the striatal area tothe dopaminergic (DA) neurons of the midbrain area. Furthermore, insoluble α-syn aggregated over time in DA neurons similar to Lewy bodies in human patients. Such assembloids are a compelling new platform to develop novel PD therapeutic strategies. |
| Akarca, Danyal; Dunn, Alexander W E; Hornauer, Philipp J; Ronchi, Silvia; Fiscella, Michele; Wang, Congwei; Terrigno, Marco; Jagasia, Ravi; Vértes, Petra E; Mierau, Susanna B; Paulsen, Ole; Eglen, Stephen J; Hierlemann, Andreas; Astle, Duncan E; Schröter, Manuel Homophilic wiring principles underpin neuronal network topology in vitro Journal Article BioRxiv, 2022. @article{Akarca2022, title = {Homophilic wiring principles underpin neuronal network topology in vitro}, author = {Danyal Akarca and Alexander W. E. Dunn and Philipp J. Hornauer and Silvia Ronchi and Michele Fiscella and Congwei Wang and Marco Terrigno and Ravi Jagasia and Petra E. Vértes and Susanna B. Mierau and Ole Paulsen and Stephen J. Eglen and Andreas Hierlemann and Duncan E. Astle and Manuel Schröter}, url = {https://www.biorxiv.org/content/10.1101/2022.03.09.483605v2.abstract}, doi = {https://doi.org/10.1101/2022.03.09.483605}, year = {2022}, date = {2022-12-01}, journal = {BioRxiv}, abstract = {Economic efficiency has been a popular explanation for how networks self-organize within the developing nervous system. However, the precise nature of the economic negotiations governing this putative organizational principle remains unclear. Here, we address this question further by combining large-scale electrophysiological recordings, to characterize the functional connectivity of developing neuronal networks in vitro, with a generative modeling approach capable of simulating network formation. We find that the best fitting model uses a homophilic generative wiring principle in which neurons form connections to other neurons which are spatially proximal and have similar connectivity patterns to themselves. Homophilic generative models outperform more canonical models in which neurons wire depending upon their spatial proximity either alone or in combination with the extent of their local connectivity. This homophily-based mechanism for neuronal network emergence accounts for a wide range of observations that are described, but not sufficiently explained, by traditional analyses of network topology. Using rodent and human monolayer and organoid cultures, we show that homophilic generative mechanisms can accurately recapitulate the topology of emerging cellular functional connectivity, representing an important wiring principle and determining factor of neuronal network formation in vitro.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Economic efficiency has been a popular explanation for how networks self-organize within the developing nervous system. However, the precise nature of the economic negotiations governing this putative organizational principle remains unclear. Here, we address this question further by combining large-scale electrophysiological recordings, to characterize the functional connectivity of developing neuronal networks in vitro, with a generative modeling approach capable of simulating network formation. We find that the best fitting model uses a homophilic generative wiring principle in which neurons form connections to other neurons which are spatially proximal and have similar connectivity patterns to themselves. Homophilic generative models outperform more canonical models in which neurons wire depending upon their spatial proximity either alone or in combination with the extent of their local connectivity. This homophily-based mechanism for neuronal network emergence accounts for a wide range of observations that are described, but not sufficiently explained, by traditional analyses of network topology. Using rodent and human monolayer and organoid cultures, we show that homophilic generative mechanisms can accurately recapitulate the topology of emerging cellular functional connectivity, representing an important wiring principle and determining factor of neuronal network formation in vitro. |
 | Habibollahi, Forough; Khajehnejad, Moein; Gaurav, Amitesh; Kagan, Brett Joseph Biological Neurons vs Deep Reinforcement Learning: Sample efficiency in a simulated game-world Conference 2022. @conference{Habibollahi2022, title = {Biological Neurons vs Deep Reinforcement Learning: Sample efficiency in a simulated game-world }, author = {Forough Habibollahi and Moein Khajehnejad and Amitesh Gaurav and Brett Joseph Kagan}, url = {https://openreview.net/forum?id=N5qLXpc7HQy}, year = {2022}, date = {2022-11-28}, journal = {OpenReview.net}, abstract = {How do synthetic biological systems and artificial neural networks compete in their performance in a game environment? Reinforcement learning has undergone significant advances, however remains behind biological neural intelligence in terms of sample efficiency. Yet most biological systems are significantly more complicated than most algorithms. Here we compare the inherent intelligence of in vitro biological neuronal networks to state-of-the-art deep reinforcement learning algorithms in the arcade game 'pong'. We employed DishBrain, a system that embodies in vitro neural networks with in silico computation using a high-density multielectrode array. We compared the learning curve and the performance of these biological systems against time-matched learning from DQN, A2C, and PPO algorithms. Agents were implemented in a reward-based environment of the `Pong' game. Key learning characteristics of the deep reinforcement learning agents were tested with those of the biological neuronal cultures in the same game environment. We find that even these very simple biological cultures typically outperform deep reinforcement learning systems in terms of various game performance characteristics, such as the average rally length implying a higher sample efficiency. Furthermore, the human cell cultures proved to have the overall highest relative improvement in the average number of hits in a rally when comparing the initial 5 minutes and the last 15 minutes of each designed gameplay session. }, keywords = {}, pubstate = {published}, tppubtype = {conference} } How do synthetic biological systems and artificial neural networks compete in their performance in a game environment? Reinforcement learning has undergone significant advances, however remains behind biological neural intelligence in terms of sample efficiency. Yet most biological systems are significantly more complicated than most algorithms. Here we compare the inherent intelligence of in vitro biological neuronal networks to state-of-the-art deep reinforcement learning algorithms in the arcade game 'pong'. We employed DishBrain, a system that embodies in vitro neural networks with in silico computation using a high-density multielectrode array. We compared the learning curve and the performance of these biological systems against time-matched learning from DQN, A2C, and PPO algorithms. Agents were implemented in a reward-based environment of the `Pong' game. Key learning characteristics of the deep reinforcement learning agents were tested with those of the biological neuronal cultures in the same game environment. We find that even these very simple biological cultures typically outperform deep reinforcement learning systems in terms of various game performance characteristics, such as the average rally length implying a higher sample efficiency. Furthermore, the human cell cultures proved to have the overall highest relative improvement in the average number of hits in a rally when comparing the initial 5 minutes and the last 15 minutes of each designed gameplay session. |
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