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.
All Publications
1.
Hruska-Plochan, Marian; Betz, Katharina M; Ronchi, Silvia; Wiersma, Vera I; Maniecka, Zuzanna; Hock, Eva-Maria; Laferriere, Florent; Sahadevan, Sonu; Hoop, Vanessa; Delvendahl, Igor; Panatta, Martina; van der Bourg, Alexander; Bohaciakova, Dasa; Frontzek, Karl; Aguzzi, Adriano; Lashley, Tammaryn; Robinson, Mark D; Karayannis, Theofanis; Mueller, Martin; Hierlemann, Andreas; Polymenidou, Magdalini: Human neural networks with sparse TDP-43 pathology reveal NPTX2 misregulation in ALS/FTLD. In: BioRxiv, 2021.(Type: Journal Article | Abstract | Links | BibTeX)
@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 = {},
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{Kajiwara2020,
title = {Inhibitory neurons are a Central Controlling regulator in the effective cortical microconnectome},
author = {Motoki Kajiwara and Ritsuki Nomura and Felix Goetze and Tatsuya Akutsu and Masanori Shimono},
url = {https://www.biorxiv.org/content/10.1101/2020.02.18.954016v1},
doi = {10.1101/2020.02.18.954016},
year = {2020},
date = {2020-02-18},
journal = {bioRxiv },
abstract = {The brain is a network system in which excitatory and inhibitory neurons keep the activity balanced in the highly non-uniform connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons. So, in general, how the inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question.
We observed effective networks, reflecting causal interactions, of ~1000 neurons in cortical acute slices. Surprisingly, we found that inhibitory neurons are not only located at more central positions than excitatory neurons but also have stronger controlling ability of other neurons than excitatory neurons. Besides, we found that the precedence in centrality and controlling ability of inhibitory neurons are well observed in deep cortical layers by comparing with distribution of neurons coloured by NeuN immunostaining data. Preceding the observation, we also found that inhibitory neurons show higher firing rate than excitatory neurons, and that their firing rate also closely obey a log-normal distribution as previously known about excitatory neurons. Additionally, their connectivity strengths also obeyed a log-normal distribution.
In summary, within the network interaction of huge numbers of neurons, inhibitory neurons seem to produce a central controlling system that sustains the homeostatic behavior of the brain. A similar evaluation in different life stages and in disease states etc. will not only provide deeper understandings in the homeostasis of the brain, but also will provide a selective and effective way to stimulate individual neurons to modulate neuropsychiatry or neurodegeneration disease states.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The brain is a network system in which excitatory and inhibitory neurons keep the activity balanced in the highly non-uniform connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons. So, in general, how the inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question.
We observed effective networks, reflecting causal interactions, of ~1000 neurons in cortical acute slices. Surprisingly, we found that inhibitory neurons are not only located at more central positions than excitatory neurons but also have stronger controlling ability of other neurons than excitatory neurons. Besides, we found that the precedence in centrality and controlling ability of inhibitory neurons are well observed in deep cortical layers by comparing with distribution of neurons coloured by NeuN immunostaining data. Preceding the observation, we also found that inhibitory neurons show higher firing rate than excitatory neurons, and that their firing rate also closely obey a log-normal distribution as previously known about excitatory neurons. Additionally, their connectivity strengths also obeyed a log-normal distribution.
In summary, within the network interaction of huge numbers of neurons, inhibitory neurons seem to produce a central controlling system that sustains the homeostatic behavior of the brain. A similar evaluation in different life stages and in disease states etc. will not only provide deeper understandings in the homeostasis of the brain, but also will provide a selective and effective way to stimulate individual neurons to modulate neuropsychiatry or neurodegeneration disease states.
@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{Kajiwara2020,
title = {Inhibitory neurons are a Central Controlling regulator in the effective cortical microconnectome},
author = {Motoki Kajiwara and Ritsuki Nomura and Felix Goetze and Tatsuya Akutsu and Masanori Shimono},
url = {https://www.biorxiv.org/content/10.1101/2020.02.18.954016v1},
doi = {10.1101/2020.02.18.954016},
year = {2020},
date = {2020-02-18},
journal = {bioRxiv },
abstract = {The brain is a network system in which excitatory and inhibitory neurons keep the activity balanced in the highly non-uniform connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons. So, in general, how the inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question.
We observed effective networks, reflecting causal interactions, of ~1000 neurons in cortical acute slices. Surprisingly, we found that inhibitory neurons are not only located at more central positions than excitatory neurons but also have stronger controlling ability of other neurons than excitatory neurons. Besides, we found that the precedence in centrality and controlling ability of inhibitory neurons are well observed in deep cortical layers by comparing with distribution of neurons coloured by NeuN immunostaining data. Preceding the observation, we also found that inhibitory neurons show higher firing rate than excitatory neurons, and that their firing rate also closely obey a log-normal distribution as previously known about excitatory neurons. Additionally, their connectivity strengths also obeyed a log-normal distribution.
In summary, within the network interaction of huge numbers of neurons, inhibitory neurons seem to produce a central controlling system that sustains the homeostatic behavior of the brain. A similar evaluation in different life stages and in disease states etc. will not only provide deeper understandings in the homeostasis of the brain, but also will provide a selective and effective way to stimulate individual neurons to modulate neuropsychiatry or neurodegeneration disease states.},
keywords = {Inhibitory Neurons},
pubstate = {published},
tppubtype = {article}
}
The brain is a network system in which excitatory and inhibitory neurons keep the activity balanced in the highly non-uniform connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons. So, in general, how the inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question.
We observed effective networks, reflecting causal interactions, of ~1000 neurons in cortical acute slices. Surprisingly, we found that inhibitory neurons are not only located at more central positions than excitatory neurons but also have stronger controlling ability of other neurons than excitatory neurons. Besides, we found that the precedence in centrality and controlling ability of inhibitory neurons are well observed in deep cortical layers by comparing with distribution of neurons coloured by NeuN immunostaining data. Preceding the observation, we also found that inhibitory neurons show higher firing rate than excitatory neurons, and that their firing rate also closely obey a log-normal distribution as previously known about excitatory neurons. Additionally, their connectivity strengths also obeyed a log-normal distribution.
In summary, within the network interaction of huge numbers of neurons, inhibitory neurons seem to produce a central controlling system that sustains the homeostatic behavior of the brain. A similar evaluation in different life stages and in disease states etc. will not only provide deeper understandings in the homeostasis of the brain, but also will provide a selective and effective way to stimulate individual neurons to modulate neuropsychiatry or neurodegeneration disease states.
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