@article{Yamamoto2023,
title = {Microfluidic technologies for reconstituting neuronal network functions in vitro},
author = {Hideaki Yamamoto and Ayumi Hirano-Iwata and Shigeo Sato},
url = {https://www.jstage.jst.go.jp/article/oubutsu/92/5/92_278/_article/-char/en},
doi = {10.11470/oubutsu.92.5_278},
year = {2023},
date = {2023-07-06},
journal = {JSAP Review},
abstract = {The structure and function of complex neuronal networks in the brain can be partially reconstituted in vitro by integrating cell culture and microfluidic device technologies. In this report, we review our recent studies on developing microfluidic devices to reconstitute small neuronal networks bearing a modular structure, which is a canonical structure found in the nervous systems of animals. We also describe the process of recording functional activity from the reconstituted neuronal networks. These fundamental technologies offer novel tools for investigating structure–function relationships in living neuronal networks and exploring the physical basis of biological computing in the brain.},
keywords = {2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Microfluidics},
pubstate = {published},
tppubtype = {article}
}
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.
@inbook{McSweeney2023,
title = {Measuring Neuronal Network Activity Using Human Induced Neuronal Cells - Stem Cell-Based Neural Model Systems for Brain Disorders},
author = {Danny McSweeney and Jay English and Ethan Howell and Fumiko Ribbe and ChangHui Pak},
url = {https://link.springer.com/protocol/10.1007/978-1-0716-3287-1_19},
year = {2023},
date = {2023-06-11},
publisher = {Methods in Molecular Biology},
abstract = {Synchronous firing of neurons, often referred to as “network activity” or “network bursting,” is an indication of a mature and synaptically connected network of neurons. We previously reported this phenomenon in 2D human neuronal in vitro models (McSweeney et al. iScience 25:105187, 2022). Using induced neurons (iNs) differentiated from human pluripotent stem cells (hPSCs) coupled with high-density microelectrodes arrays (HD-MEAs), we probed the underlying patterns of neuronal activity and found irregularities in network signaling across mutant states (McSweeney et al. iScience 25:105187, 2022). Here, we describe methods for plating cortical excitatory iNs differentiated from hPSCs on top of HD-MEAs and culturing iNs to maturity, examples of representative human wild-type Ngn2-iN data, and troubleshooting tips and tricks for the experimenter interested in integrating HD-MEAs into one’s research approach.},
keywords = {2D Neuronal Culture, Activity Scan Assay, HD-MEA, IPSC, MaxOne, MEA Metrics, MEA Technology, Network Assay},
pubstate = {published},
tppubtype = {inbook}
}
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
@article{Zhao2023,
title = {A CMOS-based highly scalable flexible neural electrode interface},
author = {Eric T. Zhao and Jacob M. Hull and Nofar Mintz Hemed and Hasan Ulusan and Julian Bartram and Anqi Zhang and Pingyu Wang and Albert Pham and Silvia Ronchi, John R. Huguenard and Andreas Hierlemann and Nicholas A. Melosh},
url = {https://www.science.org/doi/10.1126/sciadv.adf9524},
doi = {DOI: 10.1126/sciadv.adf9524},
year = {2023},
date = {2023-06-07},
journal = {Science Advances},
abstract = {Perception, thoughts, and actions are encoded by the coordinated activity of large neuronal populations spread over large areas. However, existing electrophysiological devices are limited by their scalability in capturing this cortex-wide activity. Here, we developed an electrode connector based on an ultra-conformable thin-film electrode array that self-assembles onto silicon microelectrode arrays enabling multithousand channel counts at a millimeter scale. The interconnects are formed using microfabricated electrode pads suspended by thin support arms, termed Flex2Chip. Capillary-assisted assembly drives the pads to deform toward the chip surface, and van der Waals forces maintain this deformation, establishing Ohmic contact. Flex2Chip arrays successfully measured extracellular action potentials ex vivo and resolved micrometer scale seizure propagation trajectories in epileptic mice. We find that seizure dynamics in absence epilepsy in the Scn8a+/− model do not have constant propagation trajectories.},
keywords = {3D Culture, HD-MEA, MaxOne, Other Tissues, Slices},
pubstate = {published},
tppubtype = {article}
}
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.
@article{Girardi2023,
title = {Cultured Vagal Afferent Neurons as Sensors for Intestinal Effector Molecules},
author = {Gregory Girardi and Danielle Zumpano and Noah Goshi and Helen Raybould and Erkin Seker},
url = {https://www.mdpi.com/2079-6374/13/6/601},
doi = {10.3390/bios13060601},
year = {2023},
date = {2023-05-31},
journal = {biosensors},
abstract = {The gut–brain axis embodies the bi-directional communication between the gastrointestinal tract and the central nervous system (CNS), where vagal afferent neurons (VANs) serve as sensors for a variety of gut-derived signals. The gut is colonized by a large and diverse population of microorganisms that communicate via small (effector) molecules, which also act on the VAN terminals situated in the gut viscera and consequently influence many CNS processes. However, the convoluted in vivo environment makes it difficult to study the causative impact of the effector molecules on VAN activation or desensitization. Here, we report on a VAN culture and its proof-of-principle demonstration as a cell-based sensor to monitor the influence of gastrointestinal effector molecules on neuronal behavior. We initially compared the effect of surface coatings (poly-L-lysine vs. Matrigel) and culture media composition (serum vs. growth factor supplement) on neurite growth as a surrogate of VAN regeneration following tissue harvesting, where the Matrigel coating, but not the media composition, played a significant role in the increased neurite growth. We then used both live-cell calcium imaging and extracellular electrophysiological recordings to show that the VANs responded to classical effector molecules of endogenous and exogenous origin (cholecystokinin serotonin and capsaicin) in a complex fashion. We expect this study to enable platforms for screening various effector molecules and their influence on VAN activity, assessed by their information-rich electrophysiological fingerprints.},
keywords = {2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture},
pubstate = {published},
tppubtype = {article}
}
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.
@article{Bartram2023b,
title = {Parallel reconstruction of the excitatory and inhibitory inputs received by single neurons reveals the synaptic basis of recurrent spiking},
author = {Julian Bartram and Felix Franke and Sreedhar Saseendran Kumar and Alessio Paolo Buccino and Xiaohan Xue and Tobias Gänswein and Manuel Schröter and Taehoon Kim and Krishna Chaitanya Kasuba and Andreas Hierlemann},
url = {https://elifesciences.org/reviewed-preprints/86820},
doi = {10.7554/eLife.86820},
year = {2023},
date = {2023-05-17},
journal = {eLife},
abstract = {Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between the synaptic input patterns and the spiking output of individual neurons remains largely unresolved. Here, we developed, validated and applied a novel in vitro experimental platform and analytical procedures that provide – for individual neurons – simultaneous excitatory and inhibitory synaptic activity estimates during recurrent network activity. Our approach combines whole-network high-density microelectrode array (HD-MEA) recordings from rat neuronal cultures with patch clamping and enables a comprehensive mapping and characterization of active incoming connections to single postsynaptic neurons. We found that, during network states with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided precisely with the maxima of fast fluctuations in the input E/I ratio. These spike-associated E/I ratio escalations were largely due to a rapid bidirectional change in synaptic inhibition that was modulated by the network-activity level. Our approach also uncovered the underlying circuit architecture and we show that individual neurons received a few key inhibitory connections – often from special hub neurons – that were instrumental in controlling postsynaptic spiking. Balanced network theory predicts dynamical regimes governed by small and rapid input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of cortical networks in general.},
keywords = {HD-MEA, MaxOne, MEA Metrics, MEA Technology, Modeling, Primary Neuronal Cell Culture, Spike Sorting},
pubstate = {published},
tppubtype = {article}
}
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.
@article{Duru2023,
title = {Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays},
author = {Jens Duru and Benedikt Maurer and Ciara Giles Doran and Robert Jelitto and Joël Küchler and Stephan J. Ihle and Tobias Ruff and Robert John and Barbara Genocchi and János Vörös},
url = {https://www.ssrn.com/abstract=4427959},
doi = {DOI: 10.2139/ssrn.4427959},
year = {2023},
date = {2023-04-24},
journal = {SSRN},
abstract = {Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks’ early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.},
keywords = {HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Spike Sorting, Stimulation},
pubstate = {published},
tppubtype = {article}
}
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.
@article{Cerina2023,
title = {The potential of in vitro neuronal networks cultured on Micro Electrode Arrays for biomedical research},
author = {Marta Cerina and Maria Carla Piastra and Monica Frega},
url = {https://iopscience.iop.org/article/10.1088/2516-1091/acce12},
doi = {10.1088/2516-1091/acce12},
year = {2023},
date = {2023-04-18},
journal = {Progress in Biomedical Engineering},
abstract = {In vitro neuronal models have become an important tool to study healthy and diseased neuronal circuits. The growing interest of neuroscientists to explore the dynamics of neuronal systems and the increasing need to observe, measure and manipulate not only single neurons but populations of cells pushed for technological advancement. In this sense, Micro-Electrode Arrays (MEAs) emerged as a promising technique, made of cell culture dishes with embedded micro-electrodes allowing non-invasive and relatively simple measurement of the activity of neuronal cultures at the network level. In the past decade, MEAs popularity has rapidly grown. MEA devices have been extensively used to measure the activity of neuronal cultures mainly derived from rodents. Rodent neuronal cultures on MEAs have been employed to investigate physiological mechanisms, study the effect of chemicals in neurotoxicity screenings, and model the electrophysiological phenotype of neuronal networks in different pathological conditions. With the advancements in human induced pluripotent stem cells (hiPSCs) technology, the differentiation of human neurons from the cells of adult donors became possible. hiPSCsderived neuronal networks on MEAs have been employed to develop patient-specific in vitro platforms to characterize the pathophysiological phenotype and to test drugs, paving the way towards personalized medicine. In this review, we first describe MEA technology and the information that can be obtained from MEA recordings. Then, we give an overview of studies in which MEAs have been used in combination with different neuronal systems (i.e., rodent 2D and 3D neuronal cultures, organotypic brain slices, hiPSCs-derived 2D and 3D neuronal cultures, and brain organoids) for biomedical research, including physiology studies, neurotoxicity screenings, disease modeling, and drug testing. We end by discussing potential, challenges and future perspectives of MEA technology, and providing some guidance for the choice of the neuronal model and MEA device, experimental design, data analysis and reporting for scientific publications.},
keywords = {2D Neuronal Culture, 3D Culture, Brain Slice, IPSC, MEA Technology, Organoids, Primary Neuronal Cell Culture},
pubstate = {published},
tppubtype = {article}
}
In vitro neuronal models have become an important tool to study healthy and diseased neuronal circuits. The growing interest of neuroscientists to explore the dynamics of neuronal systems and the increasing need to observe, measure and manipulate not only single neurons but populations of cells pushed for technological advancement. In this sense, Micro-Electrode Arrays (MEAs) emerged as a promising technique, made of cell culture dishes with embedded micro-electrodes allowing non-invasive and relatively simple measurement of the activity of neuronal cultures at the network level. In the past decade, MEAs popularity has rapidly grown. MEA devices have been extensively used to measure the activity of neuronal cultures mainly derived from rodents. Rodent neuronal cultures on MEAs have been employed to investigate physiological mechanisms, study the effect of chemicals in neurotoxicity screenings, and model the electrophysiological phenotype of neuronal networks in different pathological conditions. With the advancements in human induced pluripotent stem cells (hiPSCs) technology, the differentiation of human neurons from the cells of adult donors became possible. hiPSCsderived neuronal networks on MEAs have been employed to develop patient-specific in vitro platforms to characterize the pathophysiological phenotype and to test drugs, paving the way towards personalized medicine. In this review, we first describe MEA technology and the information that can be obtained from MEA recordings. Then, we give an overview of studies in which MEAs have been used in combination with different neuronal systems (i.e., rodent 2D and 3D neuronal cultures, organotypic brain slices, hiPSCs-derived 2D and 3D neuronal cultures, and brain organoids) for biomedical research, including physiology studies, neurotoxicity screenings, disease modeling, and drug testing. We end by discussing potential, challenges and future perspectives of MEA technology, and providing some guidance for the choice of the neuronal model and MEA device, experimental design, data analysis and reporting for scientific publications.
@article{Xu2023,
title = {Generation of functional posterior spinal motor neurons from hPSCs-derived human spinal cord neural progenitor cells},
author = {He Jax Xu and Yao Yao and Fenyong Yao and Jiehui Chen and Meishi Li and Xianfa Yang and Sheng Li and Fangru Lu and Ping Hu and Shuijin He and Guangdun Peng and Naihe Jing},
url = {https://cellregeneration.springeropen.com/articles/10.1186/s13619-023-00159-6},
doi = {10.1186/s13619-023-00159-6},
year = {2023},
date = {2023-03-23},
journal = {Cell Regeneration},
abstract = {Spinal motor neurons deficiency results in a series of devastating disorders such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA) and spinal cord injury (SCI). These disorders are currently incurable, while human pluripotent stem cells (hPSCs)-derived spinal motor neurons are promising but suffered from inappropriate regional identity and functional immaturity for the study and treatment of posterior spinal cord related injuries. In this study, we have established human spinal cord neural progenitor cells (hSCNPCs) via hPSCs differentiated neuromesodermal progenitors (NMPs) and demonstrated the hSCNPCs can be continuously expanded up to 40 passages. hSCNPCs can be rapidly differentiated into posterior spinal motor neurons with high efficiency. The functional maturity has been examined in detail. Moreover, a co-culture scheme which is compatible for both neural and muscular differentiation is developed to mimic the neuromuscular junction (NMJ) formation in vitro. Together, these studies highlight the potential avenues for generating clinically relevant spinal motor neurons and modeling neuromuscular diseases through our defined hSCNPCs.},
keywords = {2D Neuronal Culture, Activity Scan Assay, Axon Tracking Assay, HD-MEA, IPSC, MaxOne, MEA Technology, Network Assay, Organoids},
pubstate = {published},
tppubtype = {article}
}
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.
@article{Radivojevic2023,
title = {Functional imaging of conduction dynamics in cortical and spinal axons},
author = {Milos Radivojevic and Anna Rostedt Punga},
url = {https://www.biorxiv.org/content/10.1101/2023.02.28.530461v1},
doi = {https://doi.org/10.1101/2023.02.28.530461},
year = {2023},
date = {2023-03-01},
journal = {BioRxiv},
abstract = {Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-centimeter-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 meters of cortical and spinal axons in total and found specific features in their structure and function.},
keywords = {MaxOne},
pubstate = {published},
tppubtype = {article}
}
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.
@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 = {HD-MEA, Machine Learning, MaxOne, MEA Technology, Modeling, Organoids, Stimulation},
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.
@article{Magliaro2023,
title = {To brain or not to brain organoids},
author = {Chiara Magliaro and Arti Ahluwalia},
url = {https://www.frontiersin.org/journals/science/articles/10.3389/fsci.2023.1148873},
doi = {10.3389/fsci.2023.1148873},
year = {2023},
date = {2023-02-28},
journal = {Frontiers in Science},
abstract = {- Brain organoids are a unique template for engineering a new era of bio-inspired supercomputer technology.
- The power requirements for exploiting brain organoids may be higher than those of the most powerful computers.
- Further research is needed to accelerate sustainable solutions in brain organoid-leveraged supercomputing technologies.},
keywords = {Organoids},
pubstate = {published},
tppubtype = {article}
}
- Brain organoids are a unique template for engineering a new era of bio-inspired supercomputer technology.
- The power requirements for exploiting brain organoids may be higher than those of the most powerful computers.
- Further research is needed to accelerate sustainable solutions in brain organoid-leveraged supercomputing technologies.
@article{Lin2023,
title = {Dendritic spine formation and synapse maturation in transcription factor-induced human iPSC-derived neurons},
author = {Waka Lin and Shusaku Shiomoto and Saki Yamada and Hikaru Watanabe and Yudai Kawashima and Yuichi Eguchi and Koichi Muramatsu and Yuko Sekino},
url = {https://pubmed.ncbi.nlm.nih.gov/37034988/},
year = {2023},
date = {2023-02-27},
journal = {iScience},
abstract = {Synaptic maturation is reportedly limited in human induced pluripotent stem cell (iPSC)-derived neurons. Notably, their ability to reach postnatal-like stages and form dendritic spines has been difficult to demonstrate unless using long-term cultured organoids. Recent transcription factor (TF)-based induction methods allow the accelerated generation of differentiated neurons, which offers an unprecedented opportunity to address further progression into late developmental stages. Herein, we report on a comprehensive time-course study of TF-induced iPSC neurons cultured in vitro through an intrinsic maturation program following neurogenesis. Moreover, we determined the transcriptional and morphological sequences of key developmental events associated with spinogenesis, including the conversion of drebrin to its brain-specific isoform A and the N-methyl-D-aspartate (NMDA) receptor subunit switch. TF-induced iPSC neurons successfully acquired structural and functional synaptic maturity, which will critically expand their utility in modeling higher brain functions and disorders.},
keywords = {Activity Scan Assay, MaxTwo, Network Assay},
pubstate = {published},
tppubtype = {article}
}
Synaptic maturation is reportedly limited in human induced pluripotent stem cell (iPSC)-derived neurons. Notably, their ability to reach postnatal-like stages and form dendritic spines has been difficult to demonstrate unless using long-term cultured organoids. Recent transcription factor (TF)-based induction methods allow the accelerated generation of differentiated neurons, which offers an unprecedented opportunity to address further progression into late developmental stages. Herein, we report on a comprehensive time-course study of TF-induced iPSC neurons cultured in vitro through an intrinsic maturation program following neurogenesis. Moreover, we determined the transcriptional and morphological sequences of key developmental events associated with spinogenesis, including the conversion of drebrin to its brain-specific isoform A and the N-methyl-D-aspartate (NMDA) receptor subunit switch. TF-induced iPSC neurons successfully acquired structural and functional synaptic maturity, which will critically expand their utility in modeling higher brain functions and disorders.
@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 = {MaxOne, microrobot, Organoids, Slices},
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.
@article{Whye2023,
title = {A Robust Pipeline for the Multi‐Stage Accelerated Differentiation of Functional 3D Cortical Organoids from Human Pluripotent Stem Cells},
author = {Dosh Whye and Delaney Wood and Wardiya Afshar Saber and Erika M. Norabuena and Nina R. Makhortova and Mustafa Sahin and Elizabeth D. Buttermore},
url = {https://currentprotocols.onlinelibrary.wiley.com/doi/10.1002/cpz1.641},
doi = {doi.org/10.1002/cpz1.641},
year = {2023},
date = {2023-01-12},
journal = {Current Protocols},
abstract = {Disordered cellular development, abnormal neuroanatomical formations, and dysfunction of neuronal circuitry are among the pathological manifestations of cortical regions in the brain that are often implicated in complex neurodevelopmental disorders. With the advancement of stem cell methodologies such as cerebral organoid generation, it is possible to study these processes in vitro using 3D cellular platforms that mirror key developmental stages occurring throughout embryonic neurogenesis. Patterning-based stem cell models of directed neuronal development offer one approach to accomplish this, but these protocols often require protracted periods of cell culture to generate diverse cell types and current methods are plagued by a lack of specificity, reproducibility, and temporal control over cell derivation. Although ectopic expression of transcription factors offers another avenue to rapidly generate neurons, this process of direct lineage conversion bypasses critical junctures of neurodevelopment during which disease-relevant manifestations may occur. Here, we present a directed differentiation approach for generating human pluripotent stem cell (hPSC)-derived cortical organoids with accelerated lineage specification to generate functionally mature cortical neurons in a shorter timeline than previously established protocols. This novel protocol provides precise guidance for the specification of neuronal cell type identity as well as temporal control over the pace at which cortical lineage trajectories are established. Furthermore, we present assays that can be used as tools to interrogate stage-specific developmental signaling mechanisms. By recapitulating major components of embryonic neurogenesis, this protocol allows for improved in vitro modeling of cortical development while providing a platform that can be utilized to uncover disease-specific mechanisms of disordered development at various stages across the differentiation timeline.},
keywords = {HD-MEA, IPSC, Organoids},
pubstate = {published},
tppubtype = {article}
}
Disordered cellular development, abnormal neuroanatomical formations, and dysfunction of neuronal circuitry are among the pathological manifestations of cortical regions in the brain that are often implicated in complex neurodevelopmental disorders. With the advancement of stem cell methodologies such as cerebral organoid generation, it is possible to study these processes in vitro using 3D cellular platforms that mirror key developmental stages occurring throughout embryonic neurogenesis. Patterning-based stem cell models of directed neuronal development offer one approach to accomplish this, but these protocols often require protracted periods of cell culture to generate diverse cell types and current methods are plagued by a lack of specificity, reproducibility, and temporal control over cell derivation. Although ectopic expression of transcription factors offers another avenue to rapidly generate neurons, this process of direct lineage conversion bypasses critical junctures of neurodevelopment during which disease-relevant manifestations may occur. Here, we present a directed differentiation approach for generating human pluripotent stem cell (hPSC)-derived cortical organoids with accelerated lineage specification to generate functionally mature cortical neurons in a shorter timeline than previously established protocols. This novel protocol provides precise guidance for the specification of neuronal cell type identity as well as temporal control over the pace at which cortical lineage trajectories are established. Furthermore, we present assays that can be used as tools to interrogate stage-specific developmental signaling mechanisms. By recapitulating major components of embryonic neurogenesis, this protocol allows for improved in vitro modeling of cortical development while providing a platform that can be utilized to uncover disease-specific mechanisms of disordered development at various stages across the differentiation timeline.
@article{Taehoon2023,
title = {Predicting in vitro single-neuron firing rates upon pharmacological perturbation using Graph Neural Networks},
author = {Taehoon Kim and Dexiong Chen and Philipp Hornauer and Vishalini Emmenegger and Julian Bartram and Silvia Ronchi and Andreas Hierlemann and Manuel Schröter and Damian Roqueiro},
url = {https://www.frontiersin.org/articles/10.3389/fninf.2022.1032538/full},
doi = {10.3389/fninf.2022.1032538},
year = {2023},
date = {2023-01-11},
journal = {Frontiers in Neuroinformatics},
abstract = {Modern Graph Neural Networks (GNNs) provide opportunities to study the determinants underlying the complex activity patterns of biological neuronal networks. In this study, we applied GNNs to a large-scale electrophysiological dataset of rodent primary neuronal networks obtained by means of high-density microelectrode arrays (HD-MEAs). HD-MEAs allow for long-term recording of extracellular spiking activity of individual neurons and networks and enable the extraction of physiologically relevant features at the single- neuron and population level. We employed established GNNs to generate a combined representation of single-neuron and connectivity features obtained from HD-MEA data, with the ultimate goal of predicting changes in single-neuron firing rate induced by a pharmacological perturbation. The aim of the main prediction task was to assess whether single-neuron and functional connectivity features, inferred under baseline conditions, were informative for predicting changes in neuronal activity in response to a perturbation with Bicuculline, a GABAA receptor antagonist. Our results suggest that the joint representation of node features and functional connectivity, extracted from a baseline recording, was informative for predicting firing rate changes of individual neurons after the perturbation. Specifically, our implementation of a GNN model with inductive learning capability (GraphSAGE) outperformed other prediction models that relied only on single-neuron features. We tested the generalizability of the results on two additional datasets of HD-MEA recordings–a second dataset with cultures perturbed with Bicuculline and a dataset perturbed with the GABAA receptor antagonist Gabazine. GraphSAGE models showed improved prediction accuracy over other prediction models. Our results demonstrate the added value of taking into account the functional connectivity between neurons and the potential of GNNs to study complex interactions between neurons.},
keywords = {MaxTwo, Primary Neuronal Cell Culture},
pubstate = {published},
tppubtype = {article}
}
Modern Graph Neural Networks (GNNs) provide opportunities to study the determinants underlying the complex activity patterns of biological neuronal networks. In this study, we applied GNNs to a large-scale electrophysiological dataset of rodent primary neuronal networks obtained by means of high-density microelectrode arrays (HD-MEAs). HD-MEAs allow for long-term recording of extracellular spiking activity of individual neurons and networks and enable the extraction of physiologically relevant features at the single- neuron and population level. We employed established GNNs to generate a combined representation of single-neuron and connectivity features obtained from HD-MEA data, with the ultimate goal of predicting changes in single-neuron firing rate induced by a pharmacological perturbation. The aim of the main prediction task was to assess whether single-neuron and functional connectivity features, inferred under baseline conditions, were informative for predicting changes in neuronal activity in response to a perturbation with Bicuculline, a GABAA receptor antagonist. Our results suggest that the joint representation of node features and functional connectivity, extracted from a baseline recording, was informative for predicting firing rate changes of individual neurons after the perturbation. Specifically, our implementation of a GNN model with inductive learning capability (GraphSAGE) outperformed other prediction models that relied only on single-neuron features. We tested the generalizability of the results on two additional datasets of HD-MEA recordings–a second dataset with cultures perturbed with Bicuculline and a dataset perturbed with the GABAA receptor antagonist Gabazine. GraphSAGE models showed improved prediction accuracy over other prediction models. Our results demonstrate the added value of taking into account the functional connectivity between neurons and the potential of GNNs to study complex interactions between neurons.
@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 = {MaxOne, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Neuronal networks in dissociated culture combined with cell engineering technology offer a pivotal platform to constructively explore the relationship between structure and function in living neuronal networks. Here, we fabricated defined neuronal networks possessing a modular architecture on high-density microelectrode arrays (HD-MEAs), a state-of-the-art electrophysiological tool for recording neural activity with high spatial and temporal resolutions. We first established a surface coating protocol using a cell-permissive hydrogel to stably attach 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.
@article{Bartram2023,
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://www.biorxiv.org/content/10.1101/2023.01.06.523018v2},
doi = {https://doi.org/10.1101/2023.01.06.523018},
year = {2023},
date = {2023-01-08},
journal = {bioRxiv},
abstract = {Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. However, the precise relationship between synaptic input patterns and spiking output of individual neurons remains unresolved during spontaneous network activity. Here, using whole-network high-density microelectrode array (HD-MEA) recordings and patch clamping, we developed a novel experimental approach and analytical tools that provide a comprehensive long-term input-output characterization of individual neurons in cortical cell cultures. We found that, during in vivo-like network activity with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided with the maxima of rapid, network state-dependent fluctuations in the input E/I ratio. Our approach also uncovered the underlying circuit architecture and we identified a few key inhibitory inputs – often from special hub neurons – that were instrumental in mediating these E/I ratio changes. Balanced network theory predicts dynamical regimes governed by 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 all cortical networks.},
keywords = {CMOS, HD-MEA, Modeling, Primary Neuronal Cell Culture, Spike Sorting},
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. However, the precise relationship between synaptic input patterns and spiking output of individual neurons remains unresolved during spontaneous network activity. Here, using whole-network high-density microelectrode array (HD-MEA) recordings and patch clamping, we developed a novel experimental approach and analytical tools that provide a comprehensive long-term input-output characterization of individual neurons in cortical cell cultures. We found that, during in vivo-like network activity with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided with the maxima of rapid, network state-dependent fluctuations in the input E/I ratio. Our approach also uncovered the underlying circuit architecture and we identified a few key inhibitory inputs – often from special hub neurons – that were instrumental in mediating these E/I ratio changes. Balanced network theory predicts dynamical regimes governed by 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 all cortical networks.
@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 = {HD-MEA, IPSC, MaxOne, Neuronal cell culture, Organoids, Primary Neuronal Cell Culture},
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.
@article{VanLent2022,
title = {Downregulation of PMP22 ameliorates myelin defects in iPSC-derived human organoid cultures of CMT1A},
author = {Jonas Van Lent and Leen Vendredy and Elias Adriaenssens and Tatiana Da Silva Authier and Bob Asselbergh and Marcus Kaji and Sarah Weckhuysen and Ludo Van Den Bosch and Jonathan Baets and Vincent Timmerman},
url = {https://academic.oup.com/brain/advance-article/doi/10.1093/brain/awac475/6895197?login=false},
doi = {https://doi.org/10.1093/brain/awac475},
year = {2022},
date = {2022-12-12},
journal = {Brain},
abstract = {Charcot-Marie-Tooth (CMT) disease is the most common inherited disorder of the peripheral nervous system. CMT1A accounts for 40-50% of all cases and is caused by a duplication of the PMP22 gene on chromosome 17, leading to dysmyelination in the peripheral nervous system. Patient-derived models to study such myelination defects are lacking as the in vitro generation of human myelinating Schwann cells has proven to be particularly challenging. Here, we present an iPSC-derived organoid culture, containing various cell types of the peripheral nervous system, including myelinating human Schwann cells, which mimics the human peripheral nervous system. Single-cell analysis confirmed the peripheral nervous system-like cellular composition and provides insight into the developmental trajectory. We used this organoid-model to study disease signatures of CMT1A, revealing early ultrastructural myelin alterations, including increased myelin periodic line distance and hypermyelination of small axons. Furthermore, we observed the presence of onion bulb-like formations in a later developmental stage. These hallmarks were not present in the for CMT1A-corrected isogenic line or in a CMT2A iPSC line, supporting the notion that these alterations are specific to CMT1A. Downregulation of PMP22 expression using short-hairpin RNAs or a combinatorial drug consisting of baclofen, naltrexone hydrochloride and D-sorbitol, was able to ameliorate the myelin defects in CMT1A-organoids. In summary, this self-organizing organoid model is able to capture biologically meaningful features of the disease and capture the physiological complexity, forms an excellent model to study demyelinating diseases, and supports the therapeutic approach of reducing PMP22 expression.},
keywords = {Activity Scan Assay, Axon Tracking Assay, MaxTwo, Network Assay, Organoids},
pubstate = {published},
tppubtype = {article}
}
Charcot-Marie-Tooth (CMT) disease is the most common inherited disorder of the peripheral nervous system. CMT1A accounts for 40-50% of all cases and is caused by a duplication of the PMP22 gene on chromosome 17, leading to dysmyelination in the peripheral nervous system. Patient-derived models to study such myelination defects are lacking as the in vitro generation of human myelinating Schwann cells has proven to be particularly challenging. Here, we present an iPSC-derived organoid culture, containing various cell types of the peripheral nervous system, including myelinating human Schwann cells, which mimics the human peripheral nervous system. Single-cell analysis confirmed the peripheral nervous system-like cellular composition and provides insight into the developmental trajectory. We used this organoid-model to study disease signatures of CMT1A, revealing early ultrastructural myelin alterations, including increased myelin periodic line distance and hypermyelination of small axons. Furthermore, we observed the presence of onion bulb-like formations in a later developmental stage. These hallmarks were not present in the for CMT1A-corrected isogenic line or in a CMT2A iPSC line, supporting the notion that these alterations are specific to CMT1A. Downregulation of PMP22 expression using short-hairpin RNAs or a combinatorial drug consisting of baclofen, naltrexone hydrochloride and D-sorbitol, was able to ameliorate the myelin defects in CMT1A-organoids. In summary, this self-organizing organoid model is able to capture biologically meaningful features of the disease and capture the physiological complexity, forms an excellent model to study demyelinating diseases, and supports the therapeutic approach of reducing PMP22 expression.
@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 = {MaxOne, Organoids},
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.
@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 = {MaxOne, MaxTwo, MEA Technology},
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.
@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 = {Machine Learning, MaxOne},
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.
@article{McSweeney2022b,
title = {CASK loss of function differentially regulates neuronal maturation and synaptic function in human induced cortical excitatory neurons},
author = {Danny McSweeney and Rafael Gabriel and Kang Jin and Zhiping P. Pang and Bruce Aronow and and ChangHui Pak},
url = {https://www.cell.com/iscience/fulltext/S2589-0042(22)01459-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2589004222014596%3Fshowall%3Dtrue},
doi = {https://doi.org/10.1016/j.isci.2022.105187},
year = {2022},
date = {2022-10-21},
journal = {iScience},
abstract = {Loss-of-function (LOF) mutations in CASK cause severe developmental pheno- types, including microcephaly with pontine and cerebellar hypoplasia, X-linked in- tellectual disability, and autism. Unraveling the pathological mechanisms of CASK-related disorders has been challenging owing to limited human cellular models to study the dynamic roles of this molecule during neuronal maturation and synapse development. Here, we investigate cell-autonomous functions of CASK in cortical excitatory induced neurons (iNs) generated from CASK knockout (KO) isogenic human embryonic stem cells (hESCs) using gene expression, mor- phometrics, and electrophysiology. While immature CASK KO iNs show robust neuronal outgrowth, mature CASK KO iNs display severe defects in syn- aptic transmission and synchronized network activity without compromising neuronal morphology and synapse numbers. In the developing human cortical excitatory neurons, CASK functions to promote both structural integrity and establishment of cortical excitatory neuronal networks. These results lay the foundation for future studies identifying suppressors of such phenotypes rele- vant to human patients.},
keywords = {2D Neuronal Culture, CMOS, CRISPR, HD-MEA, MaxOne, Synapses},
pubstate = {published},
tppubtype = {article}
}
Loss-of-function (LOF) mutations in CASK cause severe developmental pheno- types, including microcephaly with pontine and cerebellar hypoplasia, X-linked in- tellectual disability, and autism. Unraveling the pathological mechanisms of CASK-related disorders has been challenging owing to limited human cellular models to study the dynamic roles of this molecule during neuronal maturation and synapse development. Here, we investigate cell-autonomous functions of CASK in cortical excitatory induced neurons (iNs) generated from CASK knockout (KO) isogenic human embryonic stem cells (hESCs) using gene expression, mor- phometrics, and electrophysiology. While immature CASK KO iNs show robust neuronal outgrowth, mature CASK KO iNs display severe defects in syn- aptic transmission and synchronized network activity without compromising neuronal morphology and synapse numbers. In the developing human cortical excitatory neurons, CASK functions to promote both structural integrity and establishment of cortical excitatory neuronal networks. These results lay the foundation for future studies identifying suppressors of such phenotypes rele- vant to human patients.
@article{Kagan2022,
title = {In vitro neurons learn and exhibit sentience when embodied in a simulated game-world},
author = {Brett J. Kagan and Andy C. Kitchen and Nhi T. Tran and Forough Habibollahi and Moein Khajehnejad and Bradyn J. Parker and Anjali Bhat and Ben Rollo and Adeel Razi and Karl J Friston
},
url = {https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627322008066%3Fshowall%3Dtrue},
doi = {https://doi.org/10.1016/j.neuron.2022.09.001},
year = {2022},
date = {2022-10-12},
journal = {Neuron},
abstract = {Integrating neurons into digital systems may enable performance infeasible with silicon alone. Here, we develop DishBrain, a system that harnesses the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins are integrated with in silico computing via a high-density multielectrode array. Through electrophysiological stimulation and recording, cultures are embedded in a simulated game-world, mimicking the arcade game “Pong.” Applying implications from the theory of active inference via the free energy principle, we find apparent learning within five minutes of real-time gameplay not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organize activity in a goal-directed manner in response to sparse sensory information about the consequences of their actions, which we term synthetic biological intelligence. Future applications may provide further insights into the cellular correlates of intelligence.},
keywords = {2D Neuronal Culture, Activity Scan Assay, closed loop stimulation, HD-MEA, IPSC, MaxOne, MEA Metrics, MEA Technology, Primary Neuronal Cell Culture},
pubstate = {published},
tppubtype = {article}
}
Integrating neurons into digital systems may enable performance infeasible with silicon alone. Here, we develop DishBrain, a system that harnesses the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins are integrated with in silico computing via a high-density multielectrode array. Through electrophysiological stimulation and recording, cultures are embedded in a simulated game-world, mimicking the arcade game “Pong.” Applying implications from the theory of active inference via the free energy principle, we find apparent learning within five minutes of real-time gameplay not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organize activity in a goal-directed manner in response to sparse sensory information about the consequences of their actions, which we term synthetic biological intelligence. Future applications may provide further insights into the cellular correlates of intelligence.
@article{Habibey2022,
title = {Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays},
author = {Rouhollah Habibey and Johannes Striebel and Felix Schmieder and Jürgen Czarske and Volker Busskamp},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2022.951964/full},
doi = {10.3389/fnins.2022.951964},
year = {2022},
date = {2022-10-04},
journal = {Frontiers in Neuroscience},
abstract = {Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.},
keywords = {2D Neuronal Culture, CMOS, HD-MEA, IPSC, MaxOne, MEA Metrics, Modeling, Spike Sorting},
pubstate = {published},
tppubtype = {article}
}
Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.
@article{Kumar2022,
title = {Tracking axon initial segment plasticity using high-density microelectrode arrays: A computational study},
author = {Sreedhar S. Kumar and Tobias Gänswein and Alessio P. Buccino and Xiaohan Xue and Julian Bartram and Vishalini Emmenegger and Andreas Hierlemann},
url = {https://www.frontiersin.org/articles/10.3389/fninf.2022.957255/full},
doi = {10.3389/fninf.2022.957255},
year = {2022},
date = {2022-10-03},
journal = {Frontiers in Neuroinformatics},
abstract = {Despite being composed of highly plastic neurons with extensive positive feedback, the nervous system maintains stable overall function. To keep activity within bounds, it relies on a set of negative feedback mechanisms that can induce stabilizing adjustments and that are collectively termed “homeostatic plasticity.” Recently, a highly excitable microdomain, located at the proximal end of the axon—the axon initial segment (AIS)—was found to exhibit structural modifications in response to activity perturbations. Though AIS plasticity appears to serve a homeostatic purpose, many aspects governing its expression and its functional role in regulating neuronal excitability remain elusive. A central challenge in studying the phenomenon is the rich heterogeneity of its expression (distal/proximal relocation, shortening, lengthening) and the variability of its functional role. A potential solution is to track AISs of a large number of neurons over time and attempt to induce structural plasticity in them. To this end, a promising approach is to use extracellular electrophysiological readouts to track a large number of neurons at high spatiotemporal resolution by means of high-density microelectrode arrays (HD-MEAs). However, an analysis framework that reliably identifies specific activity signatures that uniquely map on to underlying microstructural changes is missing. In this study, we assessed the feasibility of such a task and used the distal relocation of the AIS as an exemplary problem. We used sophisticated computational models to systematically explore the relationship between incremental changes in AIS positions and the specific consequences observed in simulated extracellular field potentials. An ensemble of feature changes in the extracellular fields that reliably characterize AIS plasticity was identified. We trained models that could detect these signatures with remarkable accuracy. Based on these findings, we propose a hybrid analysis framework that could potentially enable high-throughput experimental studies of activity-dependent AIS plasticity using HD-MEAs.},
keywords = {CMOS, HD-MEA, MEA Technology},
pubstate = {published},
tppubtype = {article}
}
Despite being composed of highly plastic neurons with extensive positive feedback, the nervous system maintains stable overall function. To keep activity within bounds, it relies on a set of negative feedback mechanisms that can induce stabilizing adjustments and that are collectively termed “homeostatic plasticity.” Recently, a highly excitable microdomain, located at the proximal end of the axon—the axon initial segment (AIS)—was found to exhibit structural modifications in response to activity perturbations. Though AIS plasticity appears to serve a homeostatic purpose, many aspects governing its expression and its functional role in regulating neuronal excitability remain elusive. A central challenge in studying the phenomenon is the rich heterogeneity of its expression (distal/proximal relocation, shortening, lengthening) and the variability of its functional role. A potential solution is to track AISs of a large number of neurons over time and attempt to induce structural plasticity in them. To this end, a promising approach is to use extracellular electrophysiological readouts to track a large number of neurons at high spatiotemporal resolution by means of high-density microelectrode arrays (HD-MEAs). However, an analysis framework that reliably identifies specific activity signatures that uniquely map on to underlying microstructural changes is missing. In this study, we assessed the feasibility of such a task and used the distal relocation of the AIS as an exemplary problem. We used sophisticated computational models to systematically explore the relationship between incremental changes in AIS positions and the specific consequences observed in simulated extracellular field potentials. An ensemble of feature changes in the extracellular fields that reliably characterize AIS plasticity was identified. We trained models that could detect these signatures with remarkable accuracy. Based on these findings, we propose a hybrid analysis framework that could potentially enable high-throughput experimental studies of activity-dependent AIS plasticity using HD-MEAs.
@article{Lee2022,
title = {Repeated and On-Demand Intracellular Recordings of Cardiomyocytes Derived from Human Induced Pluripotent Stem Cells},
author = {Jihyun Lee and Tobias Gänswein and Hasan Ulusan and Vishalini Emmenegger and Ardan M. Saguner and Firat Duru and and Andreas Hierlemann},
url = {https://pubs.acs.org/doi/10.1021/acssensors.2c01678},
doi = {https://doi.org/10.1021/acssensors.2c01678},
year = {2022},
date = {2022-09-27},
journal = {ACS Sensors},
abstract = {Pharmaceutical compounds may have cardiotoxic properties, triggering potentially life-threatening arrhythmi- as. To investigate proarrhythmic effects of drugs, the patch clamp technique has been used as the gold standard for charac- terizing the electrophysiology of cardiomyocytes in vitro. However, the applicability of this technology for drug screening is limited, as it is complex to use and features low throughput. Recent studies have demonstrated that 3D-nanostructured electrodes enable to obtain intracellular signals from many cardiomyocytes in parallel; however, the tedious electrode fab- rication and limited measurement duration still remain major issues for cardiotoxicity testing. Here, we demonstrate how porous Pt-black electrodes, arranged in high-density microelectrode arrays, can be used to record intracellular-like signals of cardiomyocytes at large-scale repeatedly over an extended period of time. The developed technique, which yields highly parallelized electroporations by using stimulation voltages around 1 Volt peak-to-peak amplitude, enabled intracellular-like recordings at high success rates without causing significant alteration in key electrophysiological features. In a proof of concept study, we investigated electrophysiological modulations induced by two clinically applied drugs, nifedipine and quinidine. As the obtained results were in good agreement with previously published data, we are confident that the devel- oped technique has the potential to be routinely used in in vitro platforms for cardiotoxicity screening.},
keywords = {Cardiomyocytes, CMOS, HD-MEA, MaxOne, MEA Technology},
pubstate = {published},
tppubtype = {article}
}
Pharmaceutical compounds may have cardiotoxic properties, triggering potentially life-threatening arrhythmi- as. To investigate proarrhythmic effects of drugs, the patch clamp technique has been used as the gold standard for charac- terizing the electrophysiology of cardiomyocytes in vitro. However, the applicability of this technology for drug screening is limited, as it is complex to use and features low throughput. Recent studies have demonstrated that 3D-nanostructured electrodes enable to obtain intracellular signals from many cardiomyocytes in parallel; however, the tedious electrode fab- rication and limited measurement duration still remain major issues for cardiotoxicity testing. Here, we demonstrate how porous Pt-black electrodes, arranged in high-density microelectrode arrays, can be used to record intracellular-like signals of cardiomyocytes at large-scale repeatedly over an extended period of time. The developed technique, which yields highly parallelized electroporations by using stimulation voltages around 1 Volt peak-to-peak amplitude, enabled intracellular-like recordings at high success rates without causing significant alteration in key electrophysiological features. In a proof of concept study, we investigated electrophysiological modulations induced by two clinically applied drugs, nifedipine and quinidine. As the obtained results were in good agreement with previously published data, we are confident that the devel- oped technique has the potential to be routinely used in in vitro platforms for cardiotoxicity screening.
@article{Al-Absi2022,
title = {Df(h22q11)/+ mouse model exhibits reduced binding levels of GABAA receptors and structural and functional dysregulation in the inhibitory and excitatory networks of hippocampus},
author = {Abdel-Rahman Al-Absi and Sakeerthi Kethees Thambiappaa and Ahmad Raza Khanc and Simon Glerup and Connie Sanchez and Anne M. Landau and Jens R. Nyengaard},
url = {https://www.sciencedirect.com/science/article/pii/S1044743122000756?via%3Dihub},
doi = {https://doi.org/10.1016/j.mcn.2022.103769},
year = {2022},
date = {2022-08-18},
journal = {Molecular and Cellular Neuroscience},
abstract = {The 22q11.2 hemizygous deletion confers high risk for multiple neurodevelopmental disorders. Inhibitory signaling, largely regulated through GABAA receptors, is suggested to serve a multitude of brain functions that are disrupted in the 22q11.2 deletion syndrome.
We investigated the putative deficit of GABAA receptors and the potential substrates contributing to the inhibitory and excitatory dysregulations in hippocampal networks of the Df(h22q11)/+ mouse model of the 22q11.2 hemizygous deletion. The Df(h22q11)/+ mice exhibited impairments in several hippocampus-related functional domains, represented by impaired spatial memory and sensory gating functions. Autoradiography using the [3H]muscimol tracer revealed a significant reduction in GABAA receptor binding in the CA1 and CA3 subregions, together with a loss of GAD67+ interneurons in CA1 of Df(h22q11)/+ mice. Furthermore, electro- physiology recordings exhibited significantly higher neuronal activity in CA3, in response to the GABAA receptor antagonist, bicuculline, as compared with wild type mice. Density and volume of dendritic spines in pyramidal neurons were reduced and Sholl analysis also showed a reduction in the complexity of basal dendritic tree in CA1 and CA3 subregions of Df(h22q11)/+ mice.
Overall, our findings demonstrate that hemizygous deletion in the 22q11.2 locus leads to dysregulations in the inhibitory circuits, involving reduced binding levels of GABAA receptors, in addition to functional and structural modulations of the excitatory networks of hippocampus.},
keywords = {Brain Slice, CMOS, HD-MEA, MaxOne},
pubstate = {published},
tppubtype = {article}
}
The 22q11.2 hemizygous deletion confers high risk for multiple neurodevelopmental disorders. Inhibitory signaling, largely regulated through GABAA receptors, is suggested to serve a multitude of brain functions that are disrupted in the 22q11.2 deletion syndrome.
We investigated the putative deficit of GABAA receptors and the potential substrates contributing to the inhibitory and excitatory dysregulations in hippocampal networks of the Df(h22q11)/+ mouse model of the 22q11.2 hemizygous deletion. The Df(h22q11)/+ mice exhibited impairments in several hippocampus-related functional domains, represented by impaired spatial memory and sensory gating functions. Autoradiography using the [3H]muscimol tracer revealed a significant reduction in GABAA receptor binding in the CA1 and CA3 subregions, together with a loss of GAD67+ interneurons in CA1 of Df(h22q11)/+ mice. Furthermore, electro- physiology recordings exhibited significantly higher neuronal activity in CA3, in response to the GABAA receptor antagonist, bicuculline, as compared with wild type mice. Density and volume of dendritic spines in pyramidal neurons were reduced and Sholl analysis also showed a reduction in the complexity of basal dendritic tree in CA1 and CA3 subregions of Df(h22q11)/+ mice.
Overall, our findings demonstrate that hemizygous deletion in the 22q11.2 locus leads to dysregulations in the inhibitory circuits, involving reduced binding levels of GABAA receptors, in addition to functional and structural modulations of the excitatory networks of hippocampus.
@article{Buccino2022,
title = {A multi-modal fitting approach to construct single-neuron models with patch clamp and high-density microelectrode arrays},
author = {Buccino, Alessio Paolo; Damart, Tanguy; Bartram, Julian; Mandge, Darshan; Xue, Xiaohan; Zbili, Mickael; Gänswein, Tobias; Jaquier, Aurélien; Emmenegger, Vishalini; Markram, Henry; Hierlemann, Andreas; Van Geit, Werner.},
doi = {https://doi.org/10.1101/2022.08.03.502468},
year = {2022},
date = {2022-08-11},
journal = {bioRxiv},
abstract = {In computational neuroscience, multicompartment models are among the most biophysically realistic representations of single neurons. Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions. The experimental data are then used to fit the many parameters of the model. While patching of the soma is currently the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections. Recording from the soma alone makes it hard to observe and correctly parameterize the activity of non-somatic compartments.
In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density micro-electrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at sub-cellular resolution.
In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models. We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone. We also demonstrate our procedure using experimental data by constructing cell models from in vitro cell cultures.
The proposed multi-modal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and to provide the field with neuronal models that are more realistic and can be better validated.
Author Summary Multicompartment models are one of the most biophysically detailed representations of single neurons. The vast majority of these models are built using experimental data from somatic recordings. However, neurons are much more than just their soma and one needs recordings from distal neurites to build an accurate model. In this article, we combine the patch-clamp technique with extracellular high-density microelectrode arrays (HD-MEAs) to compensate this shortcoming. In fact, HD-MEAs readouts allow one to record the neuronal signal in the entire axonal arbor. We show that the proposed multi-modal strategy is superior to the use of patch clamp alone using an existing model as ground-truth. Finally, we show an application of this strategy on experimental data from cultured neurons.},
keywords = {2D Neuronal Culture, Activity Scan Assay, Axon Tracking Assay, HD-MEA, MaxOne, Other Tissues, Publication, Stimulation Assay},
pubstate = {published},
tppubtype = {article}
}
In computational neuroscience, multicompartment models are among the most biophysically realistic representations of single neurons. Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions. The experimental data are then used to fit the many parameters of the model. While patching of the soma is currently the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections. Recording from the soma alone makes it hard to observe and correctly parameterize the activity of non-somatic compartments.
In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density micro-electrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at sub-cellular resolution.
In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models. We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone. We also demonstrate our procedure using experimental data by constructing cell models from in vitro cell cultures.
The proposed multi-modal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and to provide the field with neuronal models that are more realistic and can be better validated.
Author Summary Multicompartment models are one of the most biophysically detailed representations of single neurons. The vast majority of these models are built using experimental data from somatic recordings. However, neurons are much more than just their soma and one needs recordings from distal neurites to build an accurate model. In this article, we combine the patch-clamp technique with extracellular high-density microelectrode arrays (HD-MEAs) to compensate this shortcoming. In fact, HD-MEAs readouts allow one to record the neuronal signal in the entire axonal arbor. We show that the proposed multi-modal strategy is superior to the use of patch clamp alone using an existing model as ground-truth. Finally, we show an application of this strategy on experimental data from cultured neurons.
@article{Xue2022b,
title = {Inferring monosynaptic connections from paired dendritic spine Ca2+ imaging and large-scale recording of extracellular spiking},
author = {Xiaohan Xue and Alessio Paolo Buccino and Sreedhar Saseendran Kumar and Andreas Hierlemann and Julian Bartram},
doi = {https://doi.org/10.1088/1741-2552/ac8765},
year = {2022},
date = {2022-08-11},
journal = {Journal of Neural Engineering},
abstract = {Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+ imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays (HD-MEAs). We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it on in vitro recordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+ transients based on measured spike trains in order to obtain simulated ground-truth connections. The proposed approach offers unique advantages as i) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, ii) it provides precise information of presynaptic spiking, and iii) postsynaptic spine Ca2+ signals and, finally, iv) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community.},
keywords = {2D Neuronal Culture, Activity Assay, HD-MEA, MaxOne, Network Assay, Primary Neuronal Cell Culture, Publication},
pubstate = {published},
tppubtype = {article}
}
Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+ imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays (HD-MEAs). We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it on in vitro recordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+ transients based on measured spike trains in order to obtain simulated ground-truth connections. The proposed approach offers unique advantages as i) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, ii) it provides precise information of presynaptic spiking, and iii) postsynaptic spine Ca2+ signals and, finally, iv) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community.
@article{Sharf2022,
title = {Functional neuronal circuitry and oscillatory dynamics in human brain organoids},
author = {Sharf, Tal; Molen, Tjitse; Glasauer, Stella; Guzman, Elmer; Buccino, Alessio; Luna, Gabriel; Cheng, Zhuowei; Audouard, Morgane; Ranasinghe, Kamalini; Kudo, Kiwamu; Nagarajan, Srikantan; Tovar, Kenneth; Petzold, Linda; Hierlemann, Andreas; Hansma, Paul; and Kosik, Kenneth;
},
doi = {https://doi.org/10.1038/s41467-022-32115-4},
year = {2022},
date = {2022-07-29},
journal = {Nature Communications},
abstract = {Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiology of neuronal circuits within organoids remains under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we captured spontaneous extracellular activity from brain organoids derived from human induced pluripotent stem cells. We inferred functional connectivity from spike timing, revealing a large number of weak connections within a skeleton of significantly fewer strong connections. A benzodiazepine increased the uniformity of firing patterns and decreased the relative fraction of weakly connected edges. Our analysis of the local field potential demonstrate that brain organoids contain neuronal assemblies of sufficient size and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug action, and the effects of external stimuli upon neuronal networks.},
keywords = {MaxOne, Neuronal Networks, Organoids},
pubstate = {published},
tppubtype = {article}
}
Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiology of neuronal circuits within organoids remains under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we captured spontaneous extracellular activity from brain organoids derived from human induced pluripotent stem cells. We inferred functional connectivity from spike timing, revealing a large number of weak connections within a skeleton of significantly fewer strong connections. A benzodiazepine increased the uniformity of firing patterns and decreased the relative fraction of weakly connected edges. Our analysis of the local field potential demonstrate that brain organoids contain neuronal assemblies of sufficient size and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug action, and the effects of external stimuli upon neuronal networks.
Idrees, Saad; Baumann, Matthias-Philipp; Korympidou, Maria M; Schubert, Timm; Kling, Alexandra; Franke, Katrin; Hafed, Ziad M; Franke, Felix; Münch, Thomas A
@article{Idrees2022,
title = {Suppression without inhibition: how retinal computation contributes to saccadic suppression},
author = {Saad Idrees and Matthias-Philipp Baumann and Maria M. Korympidou and Timm Schubert and Alexandra Kling and Katrin Franke and Ziad M. Hafed and Felix Franke and Thomas A. Münch },
url = {https://www.nature.com/articles/s42003-022-03526-2},
year = {2022},
date = {2022-07-12},
journal = {Communications Biology},
abstract = {Visual perception remains stable across saccadic eye movements, despite the concurrent strongly disruptive visual flow. This stability is partially associated with a reduction in visual sensitivity, known as saccadic suppression, which already starts in the retina with reduced ganglion cell sensitivity. However, the retinal circuit mechanisms giving rise to such sup- pression remain unknown. Here, we describe these mechanisms using electrophysiology in mouse, pig, and macaque retina, 2-photon calcium imaging, computational modeling, and human psychophysics. We find that sequential stimuli, like those that naturally occur during saccades, trigger three independent suppressive mechanisms in the retina. The main mechanism is triggered by contrast-reversing sequential stimuli and originates within the receptive field center of ganglion cells. It does not involve inhibition or other known sup- pressive mechanisms like saturation or adaptation. Instead, it relies on temporal filtering of the inherently slow response of cone photoreceptors coupled with downstream non- linearities. Two further mechanisms of suppression are present predominantly in ON ganglion cells and originate in the receptive field surround, highlighting another disparity between ON and OFF ganglion cells. The mechanisms uncovered here likely play a role in shaping the retinal output following eye movements and other natural viewing conditions where sequential stimulation is ubiquitous.},
keywords = {HD-MEA, MaxOne, Retina},
pubstate = {published},
tppubtype = {article}
}
Visual perception remains stable across saccadic eye movements, despite the concurrent strongly disruptive visual flow. This stability is partially associated with a reduction in visual sensitivity, known as saccadic suppression, which already starts in the retina with reduced ganglion cell sensitivity. However, the retinal circuit mechanisms giving rise to such sup- pression remain unknown. Here, we describe these mechanisms using electrophysiology in mouse, pig, and macaque retina, 2-photon calcium imaging, computational modeling, and human psychophysics. We find that sequential stimuli, like those that naturally occur during saccades, trigger three independent suppressive mechanisms in the retina. The main mechanism is triggered by contrast-reversing sequential stimuli and originates within the receptive field center of ganglion cells. It does not involve inhibition or other known sup- pressive mechanisms like saturation or adaptation. Instead, it relies on temporal filtering of the inherently slow response of cone photoreceptors coupled with downstream non- linearities. Two further mechanisms of suppression are present predominantly in ON ganglion cells and originate in the receptive field surround, highlighting another disparity between ON and OFF ganglion cells. The mechanisms uncovered here likely play a role in shaping the retinal output following eye movements and other natural viewing conditions where sequential stimulation is ubiquitous.
@article{Wang2022,
title = {P97/VCP ATPase inhibitors can rescue p97 mutation-linked motor neuron degeneration},
author = {F. Wang and S. Li and T. Y. Wang and G. A. Lopez and I. Antoshechkin and T.F. Chou},
url = {https://academic.oup.com/braincomms/article/4/4/fcac176/6632805},
doi = {https://doi.org/10.1093/braincomms/fcac176},
year = {2022},
date = {2022-07-06},
journal = {Brain Communications},
abstract = {Mutations in p97/VCP cause two motor neuron diseases: inclusion body myopathy associated with Paget disease of bone and frontotemporal dementia and familial amyotrophic lateral sclerosis. How p97 mutations lead to motor neuron degeneration is, however, unknown. Here we used patient-derived induced pluripotent stem cells to generate p97 mutant motor neurons. We reduced the genetic background variation by comparing mutant motor neurons to its isogenic wild type lines. Proteomic analysis reveals that p97R155H/+ motor neurons upregulate several cell cycle proteins at Day 14, but this effect diminishes by Day 20. Molecular changes linked to delayed cell cycle exit are observed in p97 mutant motor neurons. We also find that two p97 inhibitors, CB-5083 and NMS-873, restore some dysregulated protein levels. In addition, two p97 inhibitors and a food and drug administration-approved cyclin-dependent kinase 4/6 inhibitor, Abemaciclib, can rescue motor neuron death. Overall, we successfully used iPSC-derived motor neurons, identified dysregulated proteome and transcriptome and showed that p97 inhibitors rescue phenotypes in this disease model.},
keywords = {MaxTwo},
pubstate = {published},
tppubtype = {article}
}
Mutations in p97/VCP cause two motor neuron diseases: inclusion body myopathy associated with Paget disease of bone and frontotemporal dementia and familial amyotrophic lateral sclerosis. How p97 mutations lead to motor neuron degeneration is, however, unknown. Here we used patient-derived induced pluripotent stem cells to generate p97 mutant motor neurons. We reduced the genetic background variation by comparing mutant motor neurons to its isogenic wild type lines. Proteomic analysis reveals that p97R155H/+ motor neurons upregulate several cell cycle proteins at Day 14, but this effect diminishes by Day 20. Molecular changes linked to delayed cell cycle exit are observed in p97 mutant motor neurons. We also find that two p97 inhibitors, CB-5083 and NMS-873, restore some dysregulated protein levels. In addition, two p97 inhibitors and a food and drug administration-approved cyclin-dependent kinase 4/6 inhibitor, Abemaciclib, can rescue motor neuron death. Overall, we successfully used iPSC-derived motor neurons, identified dysregulated proteome and transcriptome and showed that p97 inhibitors rescue phenotypes in this disease model.
@article{Schroter2022,
title = {Functional imaging of brain organoids using high-density microelectrode arrays},
author = {Schröter, Manuel; Wang, Congwei; Terrigno, Marco; Hornauer, Philipp; Huang, Ziqiang; Jagasia, Ravi; Hierlemann, Andreas},
url = {https://link.springer.com/article/10.1557/s43577-022-00282-w},
year = {2022},
date = {2022-06-30},
journal = {MRS Bulletin},
abstract = {Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization.},
keywords = {HD-MEA, MaxOne, MaxTwo, Organoids},
pubstate = {published},
tppubtype = {article}
}
Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization.
@article{Xu2022,
title = {Generation of functional posterior spinal motor neurons from hPSCs-derived human spinal cord neural progenitor cells},
author = {Jax H. Xu and Yao Yao and Fenyong Yao and Jiehui Chen and Meishi Li and Xianfa and Yang and Sheng Li and Fangru Lu and Ping Hu and Shuijin He and Guangdun Peng and Naihe Jing},
url = {https://www.biorxiv.org/content/10.1101/2022.06.26.495599v1},
doi = {https://doi.org/10.1101/2022.06.26.495599},
year = {2022},
date = {2022-06-27},
journal = {BioRxiv},
abstract = {Spinal motor neurons deficiency results in a series of devastating disorders such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA) and spinal cord injury (SCI). These disorders are currently incurable, while human pluripotent stem cells (hPSCs)-derived spinal motor neurons are promising but suffered from low-efficiency, functional immaturity and lacks of posterior cellular identity. In this study, we have established human spinal cord neural progenitor cells (hSCNPCs) via hPSCs differentiated neuromesodermal progenitors (NMPs) and demonstrated the hSCNPCs can be continuously expanded up to 40 passages. hSCNPCs can be rapidly differentiated into posterior spinal motor neurons with high efficiency. The functional maturity has been examined in detail. Moreover, a co-culture scheme which is compatible for both neural and muscular differentiation is developed to mimic the neuromuscular junction (NMJ) formation in vitro. Together, these studies highlight the potential avenues for generating clinically relevant spinal motor neurons and modeling neuromuscular diseases through our defined hSCNPCs.},
keywords = {2D Neuronal Culture, CMOS, HD-MEA, IPSC, MaxOne},
pubstate = {published},
tppubtype = {article}
}
Spinal motor neurons deficiency results in a series of devastating disorders such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA) and spinal cord injury (SCI). These disorders are currently incurable, while human pluripotent stem cells (hPSCs)-derived spinal motor neurons are promising but suffered from low-efficiency, functional immaturity and lacks of posterior cellular identity. In this study, we have established human spinal cord neural progenitor cells (hSCNPCs) via hPSCs differentiated neuromesodermal progenitors (NMPs) and demonstrated the hSCNPCs can be continuously expanded up to 40 passages. hSCNPCs can be rapidly differentiated into posterior spinal motor neurons with high efficiency. The functional maturity has been examined in detail. Moreover, a co-culture scheme which is compatible for both neural and muscular differentiation is developed to mimic the neuromuscular junction (NMJ) formation in vitro. Together, these studies highlight the potential avenues for generating clinically relevant spinal motor neurons and modeling neuromuscular diseases through our defined hSCNPCs.
@article{Sommer2022,
title = {Aging-Dependent Altered Transcriptional Programs Underlie Activity Impairments in Human C9orf72-Mutant Motor Neurons},
author = {Sommer, Daniel ; Rajkumar, Sandeep; Seidel, Mira; Aly, Amr; Ludolph, Albert; Ho, Ritchie; Boeckers, Tobias; Catanese, Alberto.},
url = {https://www.frontiersin.org/articles/10.3389/fnmol.2022.894230/full},
year = {2022},
date = {2022-06-14},
journal = {Frontiers in Molecular Neuroscience},
abstract = {Amyotrophic Lateral Sclerosis (ALS) is an incurable neurodegenerative disease characterized by dysfunction and loss of upper and lower motor neurons (MN). Despite several studies identifying drastic alterations affecting synaptic composition and functionality in different experimental models, the specific contribution of impaired activity to the neurodegenerative processes observed in ALS-related MN remains controversial. In particular, contrasting lines of evidence have shown both hyper- as well as hypoexcitability as driving pathomechanisms characterizing this specific neuronal population. In this study, we combined high definition multielectrode array (HD-MEA) techniques with transcriptomic analysis to longitudinally monitor and untangle the activity-dependent alterations arising in human C9orf72-mutant MN. We found a time-dependent reduction of neuronal activity in ALSC9orf72 cultures occurring as synaptic contacts undergo maturation and matched by a significant loss of mutant MN upon aging. Notably, ALS-related neurons displayed reduced network synchronicity most pronounced at later stages of culture, suggesting synaptic imbalance. In concordance with the HD-MEA data, transcriptomic analysis revealed an early up-regulation of synaptic terms in ALSC9orf72 MN, whose expression was decreased in aged cultures. In addition, treatment of older mutant cells with Apamin, a K+ channel blocker previously shown to be neuroprotective in ALS, rescued the time-dependent loss of firing properties observed in ALSC9orf72 MN as well as the expression of maturity-related synaptic genes. All in all, this study broadens the understanding of how impaired synaptic activity contributes to MN degeneration in ALS by correlating electrophysiological alterations to aging-dependent transcriptional programs.
},
keywords = {HD-MEA, MaxOne, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Amyotrophic Lateral Sclerosis (ALS) is an incurable neurodegenerative disease characterized by dysfunction and loss of upper and lower motor neurons (MN). Despite several studies identifying drastic alterations affecting synaptic composition and functionality in different experimental models, the specific contribution of impaired activity to the neurodegenerative processes observed in ALS-related MN remains controversial. In particular, contrasting lines of evidence have shown both hyper- as well as hypoexcitability as driving pathomechanisms characterizing this specific neuronal population. In this study, we combined high definition multielectrode array (HD-MEA) techniques with transcriptomic analysis to longitudinally monitor and untangle the activity-dependent alterations arising in human C9orf72-mutant MN. We found a time-dependent reduction of neuronal activity in ALSC9orf72 cultures occurring as synaptic contacts undergo maturation and matched by a significant loss of mutant MN upon aging. Notably, ALS-related neurons displayed reduced network synchronicity most pronounced at later stages of culture, suggesting synaptic imbalance. In concordance with the HD-MEA data, transcriptomic analysis revealed an early up-regulation of synaptic terms in ALSC9orf72 MN, whose expression was decreased in aged cultures. In addition, treatment of older mutant cells with Apamin, a K+ channel blocker previously shown to be neuroprotective in ALS, rescued the time-dependent loss of firing properties observed in ALSC9orf72 MN as well as the expression of maturity-related synaptic genes. All in all, this study broadens the understanding of how impaired synaptic activity contributes to MN degeneration in ALS by correlating electrophysiological alterations to aging-dependent transcriptional programs.
@article{Cheng2023,
title = {Automated detection of extracellular action potentials from single neurons},
author = {Zhuowei Cheng and Elmer Guzman and Tjitse van der Molen and Tal Sharf and Paul K. Hansma and Kenneth S Kosik and Linda Petzold and Kenneth R Tovar},
url = {https://www.biorxiv.org/content/10.1101/2022.06.06.494896v1.abstract},
doi = {https://doi.org/10.1101/2022.06.06.494896},
year = {2022},
date = {2022-06-06},
journal = {bioRxiv},
abstract = {Multi-electrode arrays (MEAs) non-invasively record extracellular action potentials (eAPs, also known as spikes) from hundreds of neurons simultaneously. However, because extracellular electrodes sample from the local electrical field, each electrode can detect eAPs from multiple nearby neurons. Interpreting spike trains at individual electrodes of high-density arrays requires spike sorting, a computational process which groups eAPs from single ’units’ based on assumptions of how spike waveforms correlate with different neuronal sources. Additionally, when experimental conditions result in changes to eAP waveforms, spike sorting routines may have difficulty correlating eAPs from multiple neurons at single electrodes before and after such waveform changes. We present here a novel, empirical method for unambiguously isolating eAPs from individual, uniquely identifiable neurons, based on automated multi- point detection of action potential propagation. This method is insensitive to changes in eAP waveform morphology because it makes no assumptions about the relationship between spike waveform and neuronal source. Our algorithm for automated detection of action potential propagation produces a ’fingerprint’ that uniquely identifies those spikes from each neuron. By unambiguously isolating eAPs from multiple neurons in each recording, on a range of platforms and experimental preparations, our method now enables high-content screening with contemporary MEAs. We outline the limitations and strengths of propagation-based isolation of eAPs from single neurons and propose how our automated method complements spike sorting and could be adapted to in vivo use.},
keywords = {Action Potential, HD-MEA, MaxOne},
pubstate = {published},
tppubtype = {article}
}
Multi-electrode arrays (MEAs) non-invasively record extracellular action potentials (eAPs, also known as spikes) from hundreds of neurons simultaneously. However, because extracellular electrodes sample from the local electrical field, each electrode can detect eAPs from multiple nearby neurons. Interpreting spike trains at individual electrodes of high-density arrays requires spike sorting, a computational process which groups eAPs from single ’units’ based on assumptions of how spike waveforms correlate with different neuronal sources. Additionally, when experimental conditions result in changes to eAP waveforms, spike sorting routines may have difficulty correlating eAPs from multiple neurons at single electrodes before and after such waveform changes. We present here a novel, empirical method for unambiguously isolating eAPs from individual, uniquely identifiable neurons, based on automated multi- point detection of action potential propagation. This method is insensitive to changes in eAP waveform morphology because it makes no assumptions about the relationship between spike waveform and neuronal source. Our algorithm for automated detection of action potential propagation produces a ’fingerprint’ that uniquely identifies those spikes from each neuron. By unambiguously isolating eAPs from multiple neurons in each recording, on a range of platforms and experimental preparations, our method now enables high-content screening with contemporary MEAs. We outline the limitations and strengths of propagation-based isolation of eAPs from single neurons and propose how our automated method complements spike sorting and could be adapted to in vivo use.
Noh Seungmin ; Jeon, Sungwoong; Kim Eunhee; Oh Untaek; Park Danbi; Park Sun Hwa; Kim Sung Won; Pané Salvador; Nelson Bradley; Kim Jin-young; Choi Hongsoo;
@article{Noh2022,
title = {A Biodegradable Magnetic Microrobot Based on Gelatin Methacrylate for Precise Delivery of Stem Cells with Mass Production Capability},
author = {Noh, Seungmin ; Jeon, Sungwoong; Kim, Eunhee; Oh, Untaek; Park, Danbi; Park, Sun Hwa; Kim, Sung Won; Pané, Salvador; Nelson, Bradley; Kim, Jin-young; Choi, Hongsoo;},
url = {https://onlinelibrary.wiley.com/doi/10.1002/smll.202107888},
doi = {10.1002/smll.202107888},
year = {2022},
date = {2022-05-23},
journal = {Small},
abstract = {A great deal of research has focused on small-scale robots for biomedical applications and minimally invasive delivery of therapeutics (e.g., cells, drugs, and genes) to a target area. Conventional fabrication methods, such as two-photon polymerization, can be used to build sophisticated micro- and nanorobots, but the long fabrication cycle for a single microrobot has limited its practical use. This study proposes a biodegradable spherical gelatin methacrylate (GelMA) microrobot for mass production in a microfluidic channel. The proposed microrobot is fabricated in a flow-focusing droplet generator by shearing a mixture of GelMA, photoinitiator, and superparamagnetic iron oxide nanoparticles (SPIONs) with a mixture of oil and surfactant. Human nasal turbinate stem cells (hNTSCs) are loaded on the GelMA microrobot, and the hNTSC-loaded microrobot shows precise rolling motion in response to an external rotating magnetic field. The microrobot is enzymatically degraded by collagenase, and released hNTSCs are proliferated and differentiated into neuronal cells. In addition, the feasibility of the GelMA microrobot as a cell therapeutic delivery system is investigated by measuring electrophysiological activity on a multielectrode array. Such a versatile and fully biodegradable microrobot has the potential for targeted stem cell delivery, proliferation, and differentiation for stem cell-based therapy.},
keywords = {MaxOne},
pubstate = {published},
tppubtype = {article}
}
A great deal of research has focused on small-scale robots for biomedical applications and minimally invasive delivery of therapeutics (e.g., cells, drugs, and genes) to a target area. Conventional fabrication methods, such as two-photon polymerization, can be used to build sophisticated micro- and nanorobots, but the long fabrication cycle for a single microrobot has limited its practical use. This study proposes a biodegradable spherical gelatin methacrylate (GelMA) microrobot for mass production in a microfluidic channel. The proposed microrobot is fabricated in a flow-focusing droplet generator by shearing a mixture of GelMA, photoinitiator, and superparamagnetic iron oxide nanoparticles (SPIONs) with a mixture of oil and surfactant. Human nasal turbinate stem cells (hNTSCs) are loaded on the GelMA microrobot, and the hNTSC-loaded microrobot shows precise rolling motion in response to an external rotating magnetic field. The microrobot is enzymatically degraded by collagenase, and released hNTSCs are proliferated and differentiated into neuronal cells. In addition, the feasibility of the GelMA microrobot as a cell therapeutic delivery system is investigated by measuring electrophysiological activity on a multielectrode array. Such a versatile and fully biodegradable microrobot has the potential for targeted stem cell delivery, proliferation, and differentiation for stem cell-based therapy.
@article{Sato2022,
title = {Microfluidic cell engineering on high-density microelectrode arrays for assessing structure-function relationships in living neuronal networks},
author = {Sato, Yuya; Yamamoto, Hideaki; Kato, Hideyuki; Tanii, Takashi; Sato, Shigeo; Hirano-Iwata, Ayumi},
url = {https://arxiv.org/abs/2205.04342},
year = {2022},
date = {2022-05-11},
abstract = {Neuronal networks in dissociated culture combined with cell engineering technology offer a pivotal platform to constructively explore the relationship between structure and function in living neuronal networks. Here, we fabricated defined neuronal networks possessing a modular architecture on high-density microelectrode arrays (HD-MEAs), a state-of-the-art electrophysiological tool for recording neural activity with high spatial and temporal resolutions. We first established a surface coating protocol using a cell-permissive hydrogel to stably attach polydimethylsiloxane microfluidic film on the HD-MEA. We then recorded the spontaneous neural activity of the engineered neuronal network, which revealed an important portrait of the engineered neuronal network--modular architecture enhances functional complexity by reducing the excessive neural correlation between spatially segregated modules. The results of this study highlight the impact of HD-MEA recordings combined with cell engineering technologies as a novel tool in neuroscience to constructively assess the structure-function relationships in neuronal networks.},
keywords = {HD-MEA, MaxOne, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Neuronal networks in dissociated culture combined with cell engineering technology offer a pivotal platform to constructively explore the relationship between structure and function in living neuronal networks. Here, we fabricated defined neuronal networks possessing a modular architecture on high-density microelectrode arrays (HD-MEAs), a state-of-the-art electrophysiological tool for recording neural activity with high spatial and temporal resolutions. We first established a surface coating protocol using a cell-permissive hydrogel to stably attach polydimethylsiloxane microfluidic film on the HD-MEA. We then recorded the spontaneous neural activity of the engineered neuronal network, which revealed an important portrait of the engineered neuronal network--modular architecture enhances functional complexity by reducing the excessive neural correlation between spatially segregated modules. The results of this study highlight the impact of HD-MEA recordings combined with cell engineering technologies as a novel tool in neuroscience to constructively assess the structure-function relationships in neuronal networks.
@article{Shimba2022,
title = {Recording Saltatory Conduction Along Sensory Axons Using a High-Density Microelectrode Array},
author = {Shimba, Kenta; Asahina, Takahiro; Sakai, Koji; Kotani, Kiyoshi; Jimbo, Yasuhiko},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2022.854637/full},
year = {2022},
date = {2022-04-18},
journal = {Frontiers in Neuroscience},
abstract = {In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network topology can be controlled by culturing neurons within polydimethylsiloxane (PDMS) microstructures that are combined with microelectrode arrays (MEAs) for electric access to the network. However, currently used glass MEAs are limited to 256 electrodes and pose a limitation to the spatial resolution as well as the design of more complex microstructures. The use of high density complementary metal-oxide-semiconductor (CMOS) MEAs greatly increases the spatial resolution, enabling sub-cellular readout and stimulation of neurons in defined neural networks. Unfortunately, the non-planar surface of CMOS MEAs complicates the attachment of PDMS microstructures. To overcome the problem of axons escaping the microstructures through the ridges of the CMOS MEA, we stamp-transferred a thin film of hexane-diluted PDMS onto the array such that the PDMS filled the ridges at the contact surface of the microstructures without clogging the axon guidance channels. This method resulted in 23 % of structurally fully connected but sealed networks on the CMOS MEA of which about 45 % showed spiking activity in all channels. Moreover, we provide an impedance-based method to visualize the exact location of the microstructures on the MEA and show that our method can confine axonal growth within the PDMS microstructures. Finally, the high spatial resolution of the CMOS MEA enabled us to show that action potentials follow the unidirectional topology of our circular multi-node microstructure.},
keywords = {HD-MEA, MaxOne, Neuronal cell culture},
pubstate = {published},
tppubtype = {article}
}
In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network topology can be controlled by culturing neurons within polydimethylsiloxane (PDMS) microstructures that are combined with microelectrode arrays (MEAs) for electric access to the network. However, currently used glass MEAs are limited to 256 electrodes and pose a limitation to the spatial resolution as well as the design of more complex microstructures. The use of high density complementary metal-oxide-semiconductor (CMOS) MEAs greatly increases the spatial resolution, enabling sub-cellular readout and stimulation of neurons in defined neural networks. Unfortunately, the non-planar surface of CMOS MEAs complicates the attachment of PDMS microstructures. To overcome the problem of axons escaping the microstructures through the ridges of the CMOS MEA, we stamp-transferred a thin film of hexane-diluted PDMS onto the array such that the PDMS filled the ridges at the contact surface of the microstructures without clogging the axon guidance channels. This method resulted in 23 % of structurally fully connected but sealed networks on the CMOS MEA of which about 45 % showed spiking activity in all channels. Moreover, we provide an impedance-based method to visualize the exact location of the microstructures on the MEA and show that our method can confine axonal growth within the PDMS microstructures. Finally, the high spatial resolution of the CMOS MEA enabled us to show that action potentials follow the unidirectional topology of our circular multi-node microstructure.
@article{Hornauer2022,
title = {Downregulating α-synuclein in iPSC-derived dopaminergic neurons mimics 2 electrophysiological phenotype of the A53T mutation},
author = {Hornauer, Philipp; Prack, Gustavo; Anastasi, Nadia; Ronchi, Silvia; Kim, Taehoon; Donner, Christian; Fiscella, Michele; Borgwardt, Karsten; Taylor, Verdon; Jagasia, Ravi; Roqueiro, Damian; Hierlemann, Andreas;},
url = {https://www.biorxiv.org/content/10.1101/2022.03.31.486582v1.full},
year = {2022},
date = {2022-04-01},
journal = {bioRxiv},
abstract = {Parkinson’s disease (PD) is a common debilitating neurodegenerative disorder, characterized by a progressive loss of dopaminergic (DA) neurons. Mutations, gene dosage increase, and single nucleotide polymorphisms in the α-synuclein-encoding gene SNCA either cause or increase the risk for PD. However, neither the function of α-synuclein in health and disease, nor its role throughout development is fully understood. Here, we introduce DeePhys, a new tool that allows for data-driven functional phenotyping of neuronal cell lines by combining electrophysiological features inferred from high-density microelectrode array (HD-MEA) recordings with a robust machine learning workflow. We apply DeePhys to human induced pluripotent stem cell (iPSC)-derived DA neuron-astrocyte co-cultures harboring the prominent SNCA mutation A53T and an isogenic control line. Moreover, we demonstrate how DeePhys can facilitate the assessment of cellular and network-level electrophysiological features to build functional phenotypes and to evaluate potential treatment interventions. We find that electrophysiological features across all scales proved to be highly specific for the A53T phenotype, enabled to predict the genotype and age of individual cultures with high accuracy, and revealed a mutant-like phenotype after downregulation of α-synuclein.},
keywords = {HD-MEA, MaxOne, Neuronal cell culture},
pubstate = {published},
tppubtype = {article}
}
Parkinson’s disease (PD) is a common debilitating neurodegenerative disorder, characterized by a progressive loss of dopaminergic (DA) neurons. Mutations, gene dosage increase, and single nucleotide polymorphisms in the α-synuclein-encoding gene SNCA either cause or increase the risk for PD. However, neither the function of α-synuclein in health and disease, nor its role throughout development is fully understood. Here, we introduce DeePhys, a new tool that allows for data-driven functional phenotyping of neuronal cell lines by combining electrophysiological features inferred from high-density microelectrode array (HD-MEA) recordings with a robust machine learning workflow. We apply DeePhys to human induced pluripotent stem cell (iPSC)-derived DA neuron-astrocyte co-cultures harboring the prominent SNCA mutation A53T and an isogenic control line. Moreover, we demonstrate how DeePhys can facilitate the assessment of cellular and network-level electrophysiological features to build functional phenotypes and to evaluate potential treatment interventions. We find that electrophysiological features across all scales proved to be highly specific for the A53T phenotype, enabled to predict the genotype and age of individual cultures with high accuracy, and revealed a mutant-like phenotype after downregulation of α-synuclein.
@article{Sawada2022,
title = {Design strategies for controlling neuron-connected robots using reinforcement learning},
author = {Haruto Sawada and Naoki Wake and Kazuhiro Sasabuchi and Jun Takamatsu and Hirokazu Takahashi and Katsushi Ikeuchi},
url = {https://arxiv.org/abs/2203.15290},
doi = {https://doi.org/10.48550/arXiv.2203.15290},
year = {2022},
date = {2022-03-29},
journal = {arXiv},
abstract = {Despite the growing interest in robot control utilizing the computation of biological neurons, context-dependent behavior by neuron-connected robots remains a challenge. Context-dependent behavior here is defined as behavior that is not the result of a simple sensory-motor coupling, but rather based on an understanding of the task goal. This paper proposes design principles for training neuron-connected robots based on task goals to achieve context-dependent behavior. First, we employ deep reinforcement learning (RL) to enable training that accounts for goal achievements. Second, we propose a neuron simulator as a probability distribution based on recorded neural data, aiming to represent physiologically valid neural dynamics while avoiding complex modeling with high computational costs. Furthermore, we propose to update the simulators during the training to bridge the gap between the simulation and the real settings. The experiments showed that the robot gradually learned context-dependent behaviors in pole balancing and robot navigation tasks. Moreover, the learned policies were valid for neural simulators based on novel neural data, and the task performance increased by updating the simulators during training. These results suggest the effectiveness of the proposed design principle for the context-dependent behavior of neuron-connected robots.},
keywords = {Machine Learning, MaxOne, Stimulation},
pubstate = {published},
tppubtype = {article}
}
Despite the growing interest in robot control utilizing the computation of biological neurons, context-dependent behavior by neuron-connected robots remains a challenge. Context-dependent behavior here is defined as behavior that is not the result of a simple sensory-motor coupling, but rather based on an understanding of the task goal. This paper proposes design principles for training neuron-connected robots based on task goals to achieve context-dependent behavior. First, we employ deep reinforcement learning (RL) to enable training that accounts for goal achievements. Second, we propose a neuron simulator as a probability distribution based on recorded neural data, aiming to represent physiologically valid neural dynamics while avoiding complex modeling with high computational costs. Furthermore, we propose to update the simulators during the training to bridge the gap between the simulation and the real settings. The experiments showed that the robot gradually learned context-dependent behaviors in pole balancing and robot navigation tasks. Moreover, the learned policies were valid for neural simulators based on novel neural data, and the task performance increased by updating the simulators during training. These results suggest the effectiveness of the proposed design principle for the context-dependent behavior of neuron-connected robots.
@article{Duru2022,
title = {Engineered Biological Neural Networks on High Density CMOS Microelectrode Arrays},
author = {Duru, Jens; Küchler, Joël; Ihle, Stephan J.;, Forró, Csaba; Bernardi, Aeneas; Girardin, Sophie; Hengsteler, Julian; Wheeler, Stephen; Vörös, János; Ruff, Tobias;},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2022.829884/full},
year = {2022},
date = {2022-02-21},
abstract = {In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network topology can be controlled by culturing neurons within polydimethylsiloxane (PDMS) microstructures that are combined with microelectrode arrays (MEAs) for electric access to the network. However, currently used glass MEAs are limited to 256 electrodes and pose a limitation to the spatial resolution as well as the design of more complex microstructures. The use of high density complementary metal-oxide-semiconductor (CMOS) MEAs greatly increases the spatial resolution, enabling sub-cellular readout and stimulation of neurons in defined neural networks. Unfortunately, the non-planar surface of CMOS MEAs complicates the attachment of PDMS microstructures. To overcome the problem of axons escaping the microstructures through the ridges of the CMOS MEA, we stamp-transferred a thin film of hexane-diluted PDMS onto the array such that the PDMS filled the ridges at the contact surface of the microstructures without clogging the axon guidance channels. This method resulted in 23 % of structurally fully connected but sealed networks on the CMOS MEA of which about 45 % showed spiking activity in all channels. Moreover, we provide an impedance-based method to visualize the exact location of the microstructures on the MEA and show that our method can confine axonal growth within the PDMS microstructures. Finally, the high spatial resolution of the CMOS MEA enabled us to show that action potentials follow the unidirectional topology of our circular multi-node microstructure.},
keywords = {HD-MEA, MaxOne, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network topology can be controlled by culturing neurons within polydimethylsiloxane (PDMS) microstructures that are combined with microelectrode arrays (MEAs) for electric access to the network. However, currently used glass MEAs are limited to 256 electrodes and pose a limitation to the spatial resolution as well as the design of more complex microstructures. The use of high density complementary metal-oxide-semiconductor (CMOS) MEAs greatly increases the spatial resolution, enabling sub-cellular readout and stimulation of neurons in defined neural networks. Unfortunately, the non-planar surface of CMOS MEAs complicates the attachment of PDMS microstructures. To overcome the problem of axons escaping the microstructures through the ridges of the CMOS MEA, we stamp-transferred a thin film of hexane-diluted PDMS onto the array such that the PDMS filled the ridges at the contact surface of the microstructures without clogging the axon guidance channels. This method resulted in 23 % of structurally fully connected but sealed networks on the CMOS MEA of which about 45 % showed spiking activity in all channels. Moreover, we provide an impedance-based method to visualize the exact location of the microstructures on the MEA and show that our method can confine axonal growth within the PDMS microstructures. Finally, the high spatial resolution of the CMOS MEA enabled us to show that action potentials follow the unidirectional topology of our circular multi-node microstructure.
@article{Xue2022,
title = {Inferring monosynaptic connections from paired dendritic spine Ca2+ imaging and large-scale recording of extracellular spiking},
author = {Xue, Xiaohan and Buccino, Alessio Paolo and Kumar, Sreedhar Saseendran and Hierlemann, Andreas and Bartram, Julian},
doi = {10.1101/2022.02.16.480643},
year = {2022},
date = {2022-02-16},
journal = {bioRxiv},
abstract = {Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+ imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays (HD-MEAs). We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it on in vitro recordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+ transients based on measured spike trains in order to obtain simulated ground-truth connections. The proposed approach offers unique advantages as i) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, ii) it provides precise information of presynaptic spiking, and iii) postsynaptic spine Ca2+ signals and, finally, iv) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community.},
keywords = {ETH-CMOS-MEA, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+ imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays (HD-MEAs). We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it on in vitro recordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+ transients based on measured spike trains in order to obtain simulated ground-truth connections. The proposed approach offers unique advantages as i) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, ii) it provides precise information of presynaptic spiking, and iii) postsynaptic spine Ca2+ signals and, finally, iv) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community.
@article{McSweeney2022,
title = {Loss of Neurodevelopmental Gene CASK Disrupts Neural Connectivity in Human Cortical Excitatory Neurons},
author = {Danny McSweeney and Rafael Gabriel and Kang Jin and Zhiping P. Pang and Bruce Aronow and ChangHui Pak},
url = {https://doi.org/10.1101/2022.02.14.480404},
doi = {10.1101/2022.02.14.480404},
year = {2022},
date = {2022-02-15},
journal = {BioRxiv},
abstract = {Loss-of-function (LOF) mutations in CASK cause severe developmental phenotypes, including microcephaly with pontine and cerebellar hypoplasia, X-linked intellectual disability, and autism. Unraveling the pathogenesis of CASK-related disorders has been challenging due to limited human cellular models to study the dynamic roles of this molecule during neuronal and synapse development. Here, we generated CASK knockout (KO) isogenic cell lines from human embryonic stem cells (hESCs) using CRISPR/Cas9 and examined gene expression, morphometrics and synaptic function of induced neuronal cells during development. While young (immature) CASK KO neurons show robust neuronal outgrowth, mature CASK KO neurons displayed severe defects in synaptic transmission and synchronized burst activity without compromising neuronal morphology and synapse numbers. In developing human cortical neurons, CASK functions to promote both structural integrity and establishment of cortical excitatory neuronal networks. These results lay the foundation for future studies identifying suppressors of such phenotypes relevant to human patients.},
keywords = {IPSC, MaxOne, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Loss-of-function (LOF) mutations in CASK cause severe developmental phenotypes, including microcephaly with pontine and cerebellar hypoplasia, X-linked intellectual disability, and autism. Unraveling the pathogenesis of CASK-related disorders has been challenging due to limited human cellular models to study the dynamic roles of this molecule during neuronal and synapse development. Here, we generated CASK knockout (KO) isogenic cell lines from human embryonic stem cells (hESCs) using CRISPR/Cas9 and examined gene expression, morphometrics and synaptic function of induced neuronal cells during development. While young (immature) CASK KO neurons show robust neuronal outgrowth, mature CASK KO neurons displayed severe defects in synaptic transmission and synchronized burst activity without compromising neuronal morphology and synapse numbers. In developing human cortical neurons, CASK functions to promote both structural integrity and establishment of cortical excitatory neuronal networks. These results lay the foundation for future studies identifying suppressors of such phenotypes relevant to human patients.
@article{Paulsen2022,
title = {Autism genes converge on asynchronous development of shared neuron classes},
author = {Bruna Paulsen and Silvia Velasco and Amanda J. Kedaigle and Martina Pigoni and Giorgia Quadrato and Anthony J. Deo and Xian Adiconis and Ana Uzquiano and Rafaela Sartore and Sung Min Yang and Sean K. Simmons and Panagiotis Symvoulidis and Kwanho Kim and Kalliopi Tsafou and Archana Podury and Catherine Abbate and Ashley Tucewicz and Samantha N. Smith and Alexandre Albanese and Lindy Barrett and Neville E. Sanjana and Xi Shi and Kwanghun Chung and Kasper Lage and Edward S. Boyden and Aviv Regev andJoshua Z. Levin and Paola Arlotta },
url = {https://www.nature.com/articles/s41586-021-04358-6},
doi = {10.1038/s41586-021-04358-6},
year = {2022},
date = {2022-02-02},
journal = {Nature},
volume = {602},
pages = {268–273},
abstract = {Genetic risk for autism spectrum disorder (ASD) is associated with hundreds of genes spanning a wide range of biological functions1,2,3,4,5,6. The alterations in the human brain resulting from mutations in these genes remain unclear. Furthermore, their phenotypic manifestation varies across individuals7,8. Here we used organoid models of the human cerebral cortex to identify cell-type-specific developmental abnormalities that result from haploinsufficiency in three ASD risk genes—SUV420H1 (also known as KMT5B), ARID1B and CHD8—in multiple cell lines from different donors, using single-cell RNA-sequencing (scRNA-seq) analysis of more than 745,000 cells and proteomic analysis of individual organoids, to identify phenotypic convergence. Each of the three mutations confers asynchronous development of two main cortical neuronal lineages—γ-aminobutyric-acid-releasing (GABAergic) neurons and deep-layer excitatory projection neurons—but acts through largely distinct molecular pathways. Although these phenotypes are consistent across cell lines, their expressivity is influenced by the individual genomic context, in a manner that is dependent on both the risk gene and the developmental defect. Calcium imaging in intact organoids shows that these early-stage developmental changes are followed by abnormal circuit activity. This research uncovers cell-type-specific neurodevelopmental abnormalities that are shared across ASD risk genes and are finely modulated by human genomic context, finding convergence in the neurobiological basis of how different risk genes contribute to ASD pathology.},
keywords = {HD-MEA, MaxOne, Organoids},
pubstate = {published},
tppubtype = {article}
}
Genetic risk for autism spectrum disorder (ASD) is associated with hundreds of genes spanning a wide range of biological functions1,2,3,4,5,6. The alterations in the human brain resulting from mutations in these genes remain unclear. Furthermore, their phenotypic manifestation varies across individuals7,8. Here we used organoid models of the human cerebral cortex to identify cell-type-specific developmental abnormalities that result from haploinsufficiency in three ASD risk genes—SUV420H1 (also known as KMT5B), ARID1B and CHD8—in multiple cell lines from different donors, using single-cell RNA-sequencing (scRNA-seq) analysis of more than 745,000 cells and proteomic analysis of individual organoids, to identify phenotypic convergence. Each of the three mutations confers asynchronous development of two main cortical neuronal lineages—γ-aminobutyric-acid-releasing (GABAergic) neurons and deep-layer excitatory projection neurons—but acts through largely distinct molecular pathways. Although these phenotypes are consistent across cell lines, their expressivity is influenced by the individual genomic context, in a manner that is dependent on both the risk gene and the developmental defect. Calcium imaging in intact organoids shows that these early-stage developmental changes are followed by abnormal circuit activity. This research uncovers cell-type-specific neurodevelopmental abnormalities that are shared across ASD risk genes and are finely modulated by human genomic context, finding convergence in the neurobiological basis of how different risk genes contribute to ASD pathology.
@article{McCready2022,
title = {Multielectrode Arrays for Functional Phenotyping of Neurons from Induced Pluripotent Stem Cell Models of Neurodevelopmental Disorders},
author = {Fraser P. McCready and Sara Gordillo-Sampedro and Kartik Pradeepan and Julio Martinez-Trujillo and James Ellis},
url = {https://www.mdpi.com/2079-7737/11/2/316},
doi = {10.3390/biology11020316},
year = {2022},
date = {2022-01-11},
journal = {Biology},
abstract = {In vitro multielectrode array (MEA) systems are increasingly used as higher-throughput platforms for functional phenotyping studies of neurons in induced pluripotent stem cell (iPSC) disease models. While MEA systems generate large amounts of spatiotemporal activity data from networks of iPSC-derived neurons, the downstream analysis and interpretation of such high-dimensional data often pose a significant challenge to researchers. In this review, we examine how MEA technology is currently deployed in iPSC modeling studies of neurodevelopmental disorders. We first highlight the strengths of in vitro MEA technology by reviewing the history of its development and the original scientific questions MEAs were intended to answer. Methods of generating patient iPSCderived neurons and astrocytes for MEA co-cultures are summarized. We then discuss challenges associated with MEA data analysis in a disease modeling context, and present novel computational methods used to better interpret network phenotyping data. We end by suggesting best practices for presenting MEA data in research publications, and propose that the creation of a public MEA data repository to enable collaborative data sharing would be of great benefit to the iPSC disease modeling community.},
keywords = {HD-MEA, IPSC, MaxOne, MEA Technology},
pubstate = {published},
tppubtype = {article}
}
In vitro multielectrode array (MEA) systems are increasingly used as higher-throughput platforms for functional phenotyping studies of neurons in induced pluripotent stem cell (iPSC) disease models. While MEA systems generate large amounts of spatiotemporal activity data from networks of iPSC-derived neurons, the downstream analysis and interpretation of such high-dimensional data often pose a significant challenge to researchers. In this review, we examine how MEA technology is currently deployed in iPSC modeling studies of neurodevelopmental disorders. We first highlight the strengths of in vitro MEA technology by reviewing the history of its development and the original scientific questions MEAs were intended to answer. Methods of generating patient iPSCderived neurons and astrocytes for MEA co-cultures are summarized. We then discuss challenges associated with MEA data analysis in a disease modeling context, and present novel computational methods used to better interpret network phenotyping data. We end by suggesting best practices for presenting MEA data in research publications, and propose that the creation of a public MEA data repository to enable collaborative data sharing would be of great benefit to the iPSC disease modeling community.
@article{Hruska-Plochan2021,
title = {Human neural networks with sparse TDP-43 pathology reveal NPTX2 misregulation in ALS/FTLD},
author = {Marian Hruska-Plochan and Katharina M. Betz and Silvia Ronchi and Vera I. Wiersma and Zuzanna Maniecka and Eva-Maria Hock and Florent Laferriere and Sonu Sahadevan and Vanessa Hoop and Igor Delvendahl and Martina Panatta and Alexander van der Bourg and Dasa Bohaciakova and Karl Frontzek and Adriano Aguzzi and Tammaryn Lashley and Mark D. Robinson and Theofanis Karayannis and Martin Mueller and Andreas Hierlemann and Magdalini Polymenidou},
url = {https://doi.org/10.1101/2021.12.08.471089},
doi = {10.1101/2021.12.08.471089},
year = {2021},
date = {2021-12-09},
journal = {BioRxiv},
abstract = {Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating these age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1,2, which involve human-specific mechanisms3–6 that cannot be directly studied in animal models. To explore the emergence and consequences of TDP-43 pathologies, we generated iPSC-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors7. Single-cell transcriptomics (scRNA-seq) and comparison to independent NSCs8, showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks. Neuronal and glial maturation in iCoMoNSC-derived cultures was similar to that of cortical organoids9. Overexpression of wild-type TDP-43 in a minority of iCoMoNSC-derived neurons led to progressive fragmentation and aggregation, resulting in loss of function and neurotoxicity. scRNA-seq revealed a novel set of misregulated RNA targets coinciding in both TDP-43 overexpressing neurons and patient brains exhibiting loss of nuclear TDP-43. The strongest misregulated target encoded for the synaptic protein NPTX2, which was consistently misaccumulated in ALS and FTLD patient neurons with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby highlighting a new pathway of neurotoxicity.},
keywords = {Inhibitory Neurons, MEA Technology, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating these age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1,2, which involve human-specific mechanisms3–6 that cannot be directly studied in animal models. To explore the emergence and consequences of TDP-43 pathologies, we generated iPSC-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors7. Single-cell transcriptomics (scRNA-seq) and comparison to independent NSCs8, showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks. Neuronal and glial maturation in iCoMoNSC-derived cultures was similar to that of cortical organoids9. Overexpression of wild-type TDP-43 in a minority of iCoMoNSC-derived neurons led to progressive fragmentation and aggregation, resulting in loss of function and neurotoxicity. scRNA-seq revealed a novel set of misregulated RNA targets coinciding in both TDP-43 overexpressing neurons and patient brains exhibiting loss of nuclear TDP-43. The strongest misregulated target encoded for the synaptic protein NPTX2, which was consistently misaccumulated in ALS and FTLD patient neurons with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby highlighting a new pathway of neurotoxicity.
@article{Kagan2021b,
title = {In vitro neurons learn and exhibit sentience when embodied in a simulated game-world},
author = {Brett J. Kagan and Andy C. Kitchen and Nhi T. Tran and Bradyn J. Parker and Anjali Bhat and Ben Rollo and Adeel Razi and Karl J. Friston},
url = {https://www.biorxiv.org/content/10.1101/2021.12.02.471005v2},
doi = {10.1101/2021.12.02.471005},
year = {2021},
date = {2021-12-03},
journal = {bioRxiv},
abstract = {Integrating neurons into digital systems to leverage their innate intelligence may enable performance infeasible with silicon alone, along with providing insight into the cellular origin of intelligence. We developed DishBrain, a system which exhibits natural intelligence by harnessing the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins, are integrated with in silico computing via high-density multielectrode array. Through electrophysiological stimulation and recording, cultures were embedded in a simulated game-world, mimicking the arcade game ‘Pong’. Applying a previously untestable theory of active inference via the Free Energy Principle, we found that learning was apparent within five minutes of real-time gameplay, not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organise in a goal-directed manner in response to sparse sensory information about the consequences of their actions.},
keywords = {2D Neuronal Culture, Activity Scan Assay, closed loop stimulation, HD-MEA, In-Vitro, IPSC, MaxOne, MEA Technology, Network Assay, Neuronal Networks, Primary Neuronal Cell Culture, Stimulation},
pubstate = {published},
tppubtype = {article}
}
Integrating neurons into digital systems to leverage their innate intelligence may enable performance infeasible with silicon alone, along with providing insight into the cellular origin of intelligence. We developed DishBrain, a system which exhibits natural intelligence by harnessing the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins, are integrated with in silico computing via high-density multielectrode array. Through electrophysiological stimulation and recording, cultures were embedded in a simulated game-world, mimicking the arcade game ‘Pong’. Applying a previously untestable theory of active inference via the Free Energy Principle, we found that learning was apparent within five minutes of real-time gameplay, not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organise in a goal-directed manner in response to sparse sensory information about the consequences of their actions.
Presenting measurements of neuronal preparations with a novel CMOS-based microelectrode array at high-spatiotemporal-resolution on subcellular, cellular, and network level.
J. Müller, M. Ballini, P. Livi, Y. Chen, M. Radivojevic, A. Shadmani, V. Viswam, I. L. Jones, M. Fiscella, R. Diggelmann, A. Stettler, U. Frey, D. J. Bakkum, and A. Hierlemann, “High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels,” Lab Chip, vol. 15, no. 13, pp. 2767–2780, May 2015.
Reviewing the current understanding of microelectrode signals and the techniques for analyzing them, with focus on the ongoing advancements in microelectrode technology (in vivo and in vitro) and recent advanced microelectrode array measurement methods that facilitate the understanding of single neurons and network function.
M. E. J. Obien, K. Deligkaris, T. Bullmann, D. J. Bakkum, and U. Frey, “Revealing Neuronal Function through Microelectrode Array Recordings,” Front. Neurosci., 8:423, Jan 2015.
A high-resolution CMOS-based microelectrode array featuring 1,024 low-noise readout channels, 26,400 electrodes at a density of 3,265 electrodes per mm2, including on-chip 10bit ADCs and consuming only 75 mW.
M. Ballini, J. Muller, P. Livi, Y. Chen, U. Frey, A. Stettler, A. Shadmani, V. Viswam, I. L. Jones, D. Jackel, M. Radivojevic, M. K. Lewandowska, W. Gong, M. Fiscella, D. J. Bakkum, F. Heer, and A. Hierlemann, “A 1024-Channel CMOS Microelectrode Array With 26,400 Electrodes for Recording and Stimulation of Electrogenic Cells In Vitro,” IEEE Journal of Solid-State Circuits, vol. 49, no. 11, pp. 2705-2719, 2014.
Demonstrating a method to electrically visualize action potential propagation on axons and revealing
large variations in velocity.
D. J. Bakkum, U. Frey, M. Radivojevic, T. L. Russell, J. Muller, M. Fiscella, H. Takahashi, and A. Hierlemann, “Tracking axonal action potential propagation on a high-density microelectrode array across hundreds of sites,” Nature Communications, 4:2181, Jul 2013.
Recording and modeling extracellular action potentials of Purkinje cells at subcellular resolution.
U. Frey, U. Egert, F. Heer, S. Hafizovic, and A. Hierlemann, “Microelectronic System for High-Resolution Mapping of Extracellular Electric Fields Applied to Brain Slices,” Biosensors and Bioelectronics, vol. 24, no. 7, pp. 2191-2198, 2009.
Controlling BMP-2 expression to modulate the electrophysiological properties of cardiomyocytes using an HD-MEA for detailed monitoring.
C. D. Sanchez-Bustamante, U. Frey, J. M. Kelm, A. Hierlemann, and M. Fussenegger,
“Modulation of Cardiomyocyte Electrical Properties Using Regulated Bone Morphogenetic Protein-2 Expression,” Tissue Engineering Part A, vol. 14, no. 12, pp. 1969-1988, 2008.
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