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.
@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 = {},
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.
@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 = {},
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 = {},
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 = {},
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{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 = {},
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{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 = {},
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{Kubota2023,
title = {Unifying framework for information processing in stochastically driven dynamical systems},
author = {Tomoyuki Kubota and Hirokazu Takahashi and and Kohei Nakajima},
url = {https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.3.043135},
doi = {https://doi.org/10.1103/PhysRevResearch.3.043135},
year = {2021},
date = {2021-11-23},
journal = {Physical Review Research},
abstract = {A dynamical system is an information processing apparatus that encodes input streams from the external environment to its state and processes them through state transitions. The information processing capacity (IPC) is an excellent tool that comprehensively evaluates these processed inputs, providing details of unknown information processing in black box systems; however, this measure can be applied only to time-invariant systems. This paper extends the applicable range to time-variant systems and further reveals that the IPC is equivalent to coefficients of polynomial chaos (PC) expansion in more general dynamical systems. To achieve this objective, we tackle three issues. First, we establish a connection between the IPC for time-invariant systems and PC expansion, which is a type of polynomial expansion using orthogonal functions of input history as bases. We prove that the IPC corresponds to the squared norm of the coefficient vector of the basis in the PC expansion. Second, we show that an input following an arbitrary distribution can be used for the IPC, removing previous restrictions to specific input distributions. Third, we extend the conventional orthogonal bases to functions of both time and input history and propose the IPC for time-variant systems. To show the significance of our approach, we demonstrate that our measure can reveal information representations in not only machine learning networks but also a real, cultured neural network. Our generalized measure paves the way for unveiling the information processing capabilities of a wide variety of physical dynamics which have been left behind in nature.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A dynamical system is an information processing apparatus that encodes input streams from the external environment to its state and processes them through state transitions. The information processing capacity (IPC) is an excellent tool that comprehensively evaluates these processed inputs, providing details of unknown information processing in black box systems; however, this measure can be applied only to time-invariant systems. This paper extends the applicable range to time-variant systems and further reveals that the IPC is equivalent to coefficients of polynomial chaos (PC) expansion in more general dynamical systems. To achieve this objective, we tackle three issues. First, we establish a connection between the IPC for time-invariant systems and PC expansion, which is a type of polynomial expansion using orthogonal functions of input history as bases. We prove that the IPC corresponds to the squared norm of the coefficient vector of the basis in the PC expansion. Second, we show that an input following an arbitrary distribution can be used for the IPC, removing previous restrictions to specific input distributions. Third, we extend the conventional orthogonal bases to functions of both time and input history and propose the IPC for time-variant systems. To show the significance of our approach, we demonstrate that our measure can reveal information representations in not only machine learning networks but also a real, cultured neural network. Our generalized measure paves the way for unveiling the information processing capabilities of a wide variety of physical dynamics which have been left behind in nature.
@article{Ricci2020,
title = {MAPSYNE: Miniaturized micropipette system combined with high-density microelectrode arrays for automated manipulation of neuronal networks in-vitro},
author = {Chiara Ricci and Urs Frey and Marie Engelene J. Obien},
url = {https://ieeexplore.ieee.org/document/9175797/},
doi = {10.1109/EMBC44109.2020.9175797},
year = {2020},
date = {2020-10-08},
journal = {IEEE},
abstract = {We present MAPSYNE, a miniaturized and automated system combining a high-density microelectrode array (HD-MEA) and a movable micropipette for studying, monitoring, and perturbing neurons in vitro. The system involves an all-electrical approach to automatically move a glass micropipette towards a target location on the HD-MEA surface, without the need for a microscope. Two methods of performing blind navigation are employed, (i) stop-measure-go approach wherein the pipette moves for a predefined distance before measuring its location then the process is repeated until the pipette reaches its destination, and (ii) predictive approach wherein the pipette is continuously tracked and moved. This automated system can be applied for unsupervised single-cell manipulation of neurons in a network, such as electroporation and local delivery of compounds.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We present MAPSYNE, a miniaturized and automated system combining a high-density microelectrode array (HD-MEA) and a movable micropipette for studying, monitoring, and perturbing neurons in vitro. The system involves an all-electrical approach to automatically move a glass micropipette towards a target location on the HD-MEA surface, without the need for a microscope. Two methods of performing blind navigation are employed, (i) stop-measure-go approach wherein the pipette moves for a predefined distance before measuring its location then the process is repeated until the pipette reaches its destination, and (ii) predictive approach wherein the pipette is continuously tracked and moved. This automated system can be applied for unsupervised single-cell manipulation of neurons in a network, such as electroporation and local delivery of compounds.
@conference{Shimba2019,
title = {Evaluation of Conduction Properties of Sensory Axons with High-Density Microelectrode Array},
author = {Kenta Shimba and Takahiro Asahina and Koji Sakai and Yasuhiko JImbo and Kiyoshi Kotani},
url = {https://ieeexplore.ieee.org/abstract/document/8990233},
doi = {10.1109/BMEiCON47515.2019.8990233},
year = {2019},
date = {2019-11-20},
abstract = {In vitro modeling of neurodegenerative disorder is a promising method for developing new treatment. However, little is known about myelination and subsequent increase of conduction velocity in vitro. Here, we aim to develop a new method for evaluating salutatory conduction from myelinated sensory axons. First, sensory neurons and Schwann cells were cultured on high-density microelectrode array chips. Myelin sheath formation was confirmed with immunocytochemistry. Axonal signal was detected, and instantaneous conduction velocity was evaluated. As a result, we observed that relatively fast conduction sites between slow conduction sites. Our method is suitable for evaluating conduction properties of sensory axons.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
In vitro modeling of neurodegenerative disorder is a promising method for developing new treatment. However, little is known about myelination and subsequent increase of conduction velocity in vitro. Here, we aim to develop a new method for evaluating salutatory conduction from myelinated sensory axons. First, sensory neurons and Schwann cells were cultured on high-density microelectrode array chips. Myelin sheath formation was confirmed with immunocytochemistry. Axonal signal was detected, and instantaneous conduction velocity was evaluated. As a result, we observed that relatively fast conduction sites between slow conduction sites. Our method is suitable for evaluating conduction properties of sensory axons.
@article{Bullmann2019,
title = {Large-Scale Mapping of Axonal Arbors Using High-Density Microelectrode Arrays},
author = {Bullmann, Torsten; Radivojevic, Milos; Huber, Stefan T: Deligkaris, Kosmas; Hierlemann, Andreas; Frey, Urs},
url = {https://www.frontiersin.org/articles/10.3389/fncel.2019.00404/full},
doi = {10.3389/fncel.2019.00404},
issn = {1662-5102},
year = {2019},
date = {2019-09-06},
journal = {Frontiers in Cellular Neuroscience },
volume = {13},
abstract = {Understanding the role of axons in neuronal information processing is a fundamental task in neuroscience. Over the last years, sophisticated patch-clamp investigations have provided unexpected and exciting data on axonal phenomena and functioning, but there is still a need for methods to investigate full axonal arbors at sufficient throughput. Here, we present a new method for the simultaneous mapping of the axonal arbors of a large number of individual neurons, which relies on their extracellular signals that have been recorded with high-density microelectrode arrays (HD-MEAs). The segmentation of axons was performed based on the local correlation of extracellular signals. Comparison of the results with both, ground truth and receiver operator characteristics, shows that the new segmentation method outperforms previously used methods. Using a standard HD-MEA, we mapped the axonal arbors of 68 neurons in <6 h. The fully automated method can be extended to new generations of HD-MEAs with larger data output and is estimated to provide data of axonal arbors of thousands of neurons within recording sessions of a few hours.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Understanding the role of axons in neuronal information processing is a fundamental task in neuroscience. Over the last years, sophisticated patch-clamp investigations have provided unexpected and exciting data on axonal phenomena and functioning, but there is still a need for methods to investigate full axonal arbors at sufficient throughput. Here, we present a new method for the simultaneous mapping of the axonal arbors of a large number of individual neurons, which relies on their extracellular signals that have been recorded with high-density microelectrode arrays (HD-MEAs). The segmentation of axons was performed based on the local correlation of extracellular signals. Comparison of the results with both, ground truth and receiver operator characteristics, shows that the new segmentation method outperforms previously used methods. Using a standard HD-MEA, we mapped the axonal arbors of 68 neurons in <6 h. The fully automated method can be extended to new generations of HD-MEAs with larger data output and is estimated to provide data of axonal arbors of thousands of neurons within recording sessions of a few hours.
@article{Mita2019,
title = {Classification of Inhibitory and Excitatory Neurons of Dissociated Cultures Based on Action Potential Waveforms on High-density CMOS Microelectrode Arrays},
author = {Takeshi Mita and Douglas J. Bakkum and Urs Frey and Andreas Hierlemann and Ryohei Kanzaki and Hirokazu Takahashi },
url = {https://www.jstage.jst.go.jp/article/ieejeiss/139/5/139_615/_article/-char/en},
doi = {10.1541/ieejeiss.139.615},
issn = {1348-8155},
year = {2019},
date = {2019-05-01},
journal = {IEEJ Transactions on Electronics, Information and Systems},
volume = {139},
number = {5},
pages = {615-624},
abstract = {Electrophysiological data from in vivo and slice preparations show that inhibitory neurons had shorter duration action potentials (AP) than excitatory neurons. However, this criterion has not yet been established in dissociated cultured neurons. In the present study, we used a high-density CMOS microelectrode array to extracellularly investigate neural signals in primary dissociated cultures of rat neocortex, and we characterized AP waveforms to discriminate excitatory and inhibitory neurons. The CMOS array offers the possibility to acquire comprehensive spatio-temporal neural activity patterns with 11,011 electrodes in about 2×1.75 mm2 area at 20-kHz sampling rate. The waveforms of APs were investigated around cell bodies of neurons, which were classified into either excitatory neurons or inhibitory neurons on the basis of MAP2 and GABA immunostaining images. Consistent with previous in vivo and slice studies, we demonstrated that AP waveforms of inhibitory neurons had shorter durations and recovery time than those of excitatory neurons. The discrimination accuracy was around 0.9 in the receiver-operating characteristics (ROC) analyses. Additionally, taking advantage of non-invasive CMOS recording, we investigated AP waveforms throughout development of cultures. We confirmed that APs were classified into two classes, i.e., putative excitatory and inhibitory neurons, regardless of developmental stages, and found that the duration and recovery time of AP shortened in matured cultures. Thus, AP waveforms have rich information about cell types and developmental stages, which are of worth to elucidate underlying mechanisms of neuronal dynamics in spatio-temporal patterns.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Electrophysiological data from in vivo and slice preparations show that inhibitory neurons had shorter duration action potentials (AP) than excitatory neurons. However, this criterion has not yet been established in dissociated cultured neurons. In the present study, we used a high-density CMOS microelectrode array to extracellularly investigate neural signals in primary dissociated cultures of rat neocortex, and we characterized AP waveforms to discriminate excitatory and inhibitory neurons. The CMOS array offers the possibility to acquire comprehensive spatio-temporal neural activity patterns with 11,011 electrodes in about 2×1.75 mm2 area at 20-kHz sampling rate. The waveforms of APs were investigated around cell bodies of neurons, which were classified into either excitatory neurons or inhibitory neurons on the basis of MAP2 and GABA immunostaining images. Consistent with previous in vivo and slice studies, we demonstrated that AP waveforms of inhibitory neurons had shorter durations and recovery time than those of excitatory neurons. The discrimination accuracy was around 0.9 in the receiver-operating characteristics (ROC) analyses. Additionally, taking advantage of non-invasive CMOS recording, we investigated AP waveforms throughout development of cultures. We confirmed that APs were classified into two classes, i.e., putative excitatory and inhibitory neurons, regardless of developmental stages, and found that the duration and recovery time of AP shortened in matured cultures. Thus, AP waveforms have rich information about cell types and developmental stages, which are of worth to elucidate underlying mechanisms of neuronal dynamics in spatio-temporal patterns.
@article{Emmenegger2019,
title = {Technologies to Study Action Potential Propagation With a Focus on HD-MEAs},
author = {Vishalini Emmenegger and Marie Engelene J. Obien and Felix Franke and Andreas Hierlemann},
url = {https://www.frontiersin.org/articles/10.3389/fncel.2019.00159/full},
doi = {10.3389/fncel.2019.00159 },
issn = {1662-5102 },
year = {2019},
date = {2019-04-26},
journal = {Frontiers in Cellular Neuroscience},
volume = {13},
pages = {1-11},
abstract = {Axons convey information in neuronal circuits via reliable conduction of action potentials from the axon initial segment to the presynaptic terminals. Recent experimental findings increasingly evidence that the axonal function is not limited to the simple transmission of action potentials. Advances in subcellular-resolution recording techniques have shown that axons display activity-dependent modulation in spike shape and conduction velocity, which influence synaptic strength and latency. We briefly review, here, how recent methodological developments facilitate the understanding of the axon physiology. We included the three most common methods, i.e. genetically encoded voltage imaging, subcellular patch-clamp and high-density microelectrode arrays (HD-MEAs). We then describe the potential of using HD-MEAs in studying axonal physiology in more detail. Due to their robustness, amenability to high-throughput and high spatiotemporal resolution, HD-MEAs can provide a direct functional electrical readout of single cells and cellular ensembles at subcellular resolution. HD-MEAs can, therefore, be employed in investigating axonal pathologies, the effects of large-scale genomic interventions (e.g., with RNAi or CRISPR) or in compound screenings. A combination of extracellular microelectrode arrays, intracellular microelectrodes and optical imaging may potentially reveal yet unexplored repertoires of axonal functions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Axons convey information in neuronal circuits via reliable conduction of action potentials from the axon initial segment to the presynaptic terminals. Recent experimental findings increasingly evidence that the axonal function is not limited to the simple transmission of action potentials. Advances in subcellular-resolution recording techniques have shown that axons display activity-dependent modulation in spike shape and conduction velocity, which influence synaptic strength and latency. We briefly review, here, how recent methodological developments facilitate the understanding of the axon physiology. We included the three most common methods, i.e. genetically encoded voltage imaging, subcellular patch-clamp and high-density microelectrode arrays (HD-MEAs). We then describe the potential of using HD-MEAs in studying axonal physiology in more detail. Due to their robustness, amenability to high-throughput and high spatiotemporal resolution, HD-MEAs can provide a direct functional electrical readout of single cells and cellular ensembles at subcellular resolution. HD-MEAs can, therefore, be employed in investigating axonal pathologies, the effects of large-scale genomic interventions (e.g., with RNAi or CRISPR) or in compound screenings. A combination of extracellular microelectrode arrays, intracellular microelectrodes and optical imaging may potentially reveal yet unexplored repertoires of axonal functions.
@article{Viswam2018,
title = {Impedance Spectroscopy and Electrophysiological Imaging of Cells With a High-Density CMOS Microelectrode Array System},
author = {Vijay Viswam and Raziyeh Bounik and Amir Shadmani and Jelena Dragas and Cedar Urwyler and Julia Alicia Boos and Marie Engelene J. Obien and Jan Muller and Yihui Chen and Andreas Hierlemann},
url = {https://ieeexplore.ieee.org/document/8532304},
doi = {10.1109/TBCAS.2018.2881044},
issn = {1932-4545},
year = {2018},
date = {2018-11-12},
journal = {IEEE Transactions on Biomedical Circuits and Systems},
volume = {12},
number = {6},
pages = {1356-1368},
abstract = {A monolithic multi-functional CMOS microelectrode array system was developed that enables label-free electrochemical impedance spectroscopy of cells in vitro at high spatiotemporal resolution. The electrode array includes 59,760 platinum microelectrodes, densely packed within a 4.5 mm × 2.5 mm sensing region at a pitch of 13.5 μm. A total of 32 on-chip lock-in amplifiers can be used to measure the impedance of any arbitrarily chosen subset of electrodes in the array. A sinusoidal voltage, generated by an on-chip waveform generator with a frequency range from 1 Hz to 1 MHz, was applied to the reference electrode. The sensing currents through the selected recording electrodes were amplified, demodulated, filtered, and digitized to obtain the magnitude and phase information of the respective impedances. The circuitry consumes only 412 μW at 3.3 V supply voltage and occupies only 0.1 mm 2 , for each channel. The system also included 2048 extracellular action-potential recording channels on the same chip. Proof of concept measurements of electrical impedance imaging and electrophysiology recording of cardiac cells and brain slices are demonstrated in this paper. Optical and impedance images showed a strong correlation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A monolithic multi-functional CMOS microelectrode array system was developed that enables label-free electrochemical impedance spectroscopy of cells in vitro at high spatiotemporal resolution. The electrode array includes 59,760 platinum microelectrodes, densely packed within a 4.5 mm × 2.5 mm sensing region at a pitch of 13.5 μm. A total of 32 on-chip lock-in amplifiers can be used to measure the impedance of any arbitrarily chosen subset of electrodes in the array. A sinusoidal voltage, generated by an on-chip waveform generator with a frequency range from 1 Hz to 1 MHz, was applied to the reference electrode. The sensing currents through the selected recording electrodes were amplified, demodulated, filtered, and digitized to obtain the magnitude and phase information of the respective impedances. The circuitry consumes only 412 μW at 3.3 V supply voltage and occupies only 0.1 mm 2 , for each channel. The system also included 2048 extracellular action-potential recording channels on the same chip. Proof of concept measurements of electrical impedance imaging and electrophysiology recording of cardiac cells and brain slices are demonstrated in this paper. Optical and impedance images showed a strong correlation.
@conference{Fiscella2018,
title = {Electrophysiological phenotype characterization of human iPSC-derived dopaminergic neuronal lines by means of high-resolution microelectrode array},
author = {Michele Fiscella and Noelle Leary and Silvia Ronchi and Andreas Hierlemann },
url = {https://www.abstractsonline.com/pp8/#!/4649/presentation/24924},
year = {2018},
date = {2018-11-07},
volume = {Contribution 700.13},
address = {San Diego, CA, USA},
organization = {Society for Neuroscience (SfN) Meeting},
abstract = {High-resolution-microelectrode-array (HD-MEA) technology enables to study neuronal dynamics at different scales, ranging from axonal physiology to network connectivity [1]. We have used this HD-MEA technology to characterize and compare the electrical phenotypes of commercially available human dopaminergic neurons (iCell DopaNeurons, MyCell DopaNeurons A53T α-synuclein, Cellular Dynamics International, Madison, WI, US). Furthermore, we have studied the effect of human astrocytes (iCell Astrocytes, Cellular Dynamics International, Madison, WI, US) on neural-culture development. Astrocyte/neuron co-cultures showed higher signal amplitudes and higher firing rates than neural cultures without astrocytes. Adding astrocytes to neural cultures changed the whole culture morphology by promoting cell clustering. Interestingly, astrocyte/neuron co-cultures showed a lower sample-to-sample variability across multiple HD-MEA recordings compared to neural cultures without astrocytes. We compared action potential propagation velocities along axons between dopaminergic A53T α-synuclein neurons and the wild-type isogenic control cell line. We found that in both, wild-type and disease-model neurons, axonal action potential propagation velocities were lower than in rat primary cortical neurons [2]. Furthermore, we found different axonal-action-potential-velocity-development profiles of A53T α-synuclein dopaminergic neurons and the wild-type counterpart. Finally, we were able to precisely evoke action potentials in individual single human neurons by subcellular-resolution electrical stimulation. HD-MEA systems enable to access novel electrophysiological parameters of iPSC-derived neurons, which can be potentially used as biomarkers for phenotype screening and drug testing.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
High-resolution-microelectrode-array (HD-MEA) technology enables to study neuronal dynamics at different scales, ranging from axonal physiology to network connectivity [1]. We have used this HD-MEA technology to characterize and compare the electrical phenotypes of commercially available human dopaminergic neurons (iCell DopaNeurons, MyCell DopaNeurons A53T α-synuclein, Cellular Dynamics International, Madison, WI, US). Furthermore, we have studied the effect of human astrocytes (iCell Astrocytes, Cellular Dynamics International, Madison, WI, US) on neural-culture development. Astrocyte/neuron co-cultures showed higher signal amplitudes and higher firing rates than neural cultures without astrocytes. Adding astrocytes to neural cultures changed the whole culture morphology by promoting cell clustering. Interestingly, astrocyte/neuron co-cultures showed a lower sample-to-sample variability across multiple HD-MEA recordings compared to neural cultures without astrocytes. We compared action potential propagation velocities along axons between dopaminergic A53T α-synuclein neurons and the wild-type isogenic control cell line. We found that in both, wild-type and disease-model neurons, axonal action potential propagation velocities were lower than in rat primary cortical neurons [2]. Furthermore, we found different axonal-action-potential-velocity-development profiles of A53T α-synuclein dopaminergic neurons and the wild-type counterpart. Finally, we were able to precisely evoke action potentials in individual single human neurons by subcellular-resolution electrical stimulation. HD-MEA systems enable to access novel electrophysiological parameters of iPSC-derived neurons, which can be potentially used as biomarkers for phenotype screening and drug testing.
Bartram, Julian; Schroter, Manuel; Ronchi, Silvia; Emmenegger, Vishalini; Muller, Jan; Hierlemann, Andreas: Mechanisms of homeostatic synaptic plasticity. Contribution 037.11 , Society for Neuroscience (SfN) Meeting San Diego, CA, USA, 2018.(Type: Conference | Abstract | Links | BibTeX)
@conference{Bartram2018,
title = {Mechanisms of homeostatic synaptic plasticity},
author = {Julian Bartram and Manuel Schroter and Silvia Ronchi and Vishalini Emmenegger and Jan Muller and Andreas Hierlemann},
url = {https://www.abstractsonline.com/pp8/#!/4649/presentation/3968},
year = {2018},
date = {2018-11-03},
volume = {Contribution 037.11},
address = {San Diego, CA, USA},
organization = {Society for Neuroscience (SfN) Meeting},
abstract = {Homeostatic plasticity is a crucial set of mechanisms acting at typically slow temporal scales in order to stabilize neuronal spike rates. Despite the functional significance of such processes, revealing the precise induction mechanisms has proven to be difficult, as the roles of postsynaptic spiking and synaptic activity are still debated. For a clearer picture of the induction process to emerge, information about synaptic efficacies of multiple inputs needs to be combined with accurate information about spiking activities of the respective presynaptic cells and the postsynaptic cell during the induction of homeostatic plasticity. In this study, we were able to achieve such measurements by performing combined high-density microelectrode array (HD-MEA) and whole-cell patch-clamp recordings in cultures of primary cortical neurons. Homeostatic plasticity was induced by pharmacological alteration of global network spiking and synaptic transmission with TTX or CNQX. Monosynaptic connections between neurons - here with a focus on excitatory connections between pyramidal cells - were identified by correlating presynaptic spiking activity (HD-MEA recordings) with postsynaptic subthreshold responses (patch current-clamp recordings). Presynaptic spiking was spontaneously observed or could be induced via the stimulation capabilities of the HD-MEA system. This experimental approach enabled us to link changes in synaptic efficacy with the respective pre- and postsynaptic spike patterns, recorded during the induction phase, which sheds new light on the rules and mechanisms of homeostatic synaptic plasticity at excitatory synapses.
Financial support through the ERC Advanced Grant 694829 “neuroXscales” is gratefully acknowledged.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Homeostatic plasticity is a crucial set of mechanisms acting at typically slow temporal scales in order to stabilize neuronal spike rates. Despite the functional significance of such processes, revealing the precise induction mechanisms has proven to be difficult, as the roles of postsynaptic spiking and synaptic activity are still debated. For a clearer picture of the induction process to emerge, information about synaptic efficacies of multiple inputs needs to be combined with accurate information about spiking activities of the respective presynaptic cells and the postsynaptic cell during the induction of homeostatic plasticity. In this study, we were able to achieve such measurements by performing combined high-density microelectrode array (HD-MEA) and whole-cell patch-clamp recordings in cultures of primary cortical neurons. Homeostatic plasticity was induced by pharmacological alteration of global network spiking and synaptic transmission with TTX or CNQX. Monosynaptic connections between neurons - here with a focus on excitatory connections between pyramidal cells - were identified by correlating presynaptic spiking activity (HD-MEA recordings) with postsynaptic subthreshold responses (patch current-clamp recordings). Presynaptic spiking was spontaneously observed or could be induced via the stimulation capabilities of the HD-MEA system. This experimental approach enabled us to link changes in synaptic efficacy with the respective pre- and postsynaptic spike patterns, recorded during the induction phase, which sheds new light on the rules and mechanisms of homeostatic synaptic plasticity at excitatory synapses.
Financial support through the ERC Advanced Grant 694829 “neuroXscales” is gratefully acknowledged.
@conference{Fiscella2018c,
title = {Electrophysiological phenotype characterization of human iPSC-derived dopaminergic neuronal lines by means of high-resolution microelelectrode arrays},
author = {Michele Fiscella and Noelle Leary and Silvia Ronchi and Andreas Hierlemann},
url = {https://www.frontiersin.org/Community/AbstractDetails.aspx?ABS_DOI=10.3389/conf.fncel.2018.38.00014&eid=5473&sname=MEA_Meeting_2018_%7C_11th_International_Meeting_on_Substrate_Integrated_Microelectrode_Arrays},
doi = {10.3389/conf.fncel.2018.38.00014},
year = {2018},
date = {2018-07-04},
address = {Reutlingen, Germany},
organization = {11th International Meeting on Substrate Integrated Microelectrode Arrays (MEA Meeting)},
abstract = {High-resolution-microelectrode-array (MEA) technology enables to study neuronal dynamics at different scales, ranging from axonal physiology to network connectivity (Müller et. al, Lab on a Chip, 2015). We have used this MEA technology to characterize and compare the electrical phenotypes of commercially available human dopaminergic neurons (iCell DopaNeurons, MyCell DopaNeurons A53T α-synuclein, Cellular Dynamics International, Madison, WI, US). Furthermore, we have studied the effect of human astrocytes (iCell Astrocytes, Cellular Dynamics International, Madison, WI, US) on neural culture development.
Astrocyte/neuron co-cultures showed higher signal amplitudes and higher firing rates than neural cultures without astrocytes. Adding astrocytes to neural cultures changed the whole culture morphology by promoting cell clustering. Interestingly, astrocyte/neuron co-cultures showed a lower sample-to-sample variability across multiple MEA recording sessions compared to neural cultures without astrocytes.
We compared velocities of action potential propagation along axons between dopaminergic A53T α-synuclein neurons and the wild-type isogenic control cell line. We found that in both, wild-type and disease-model neurons, axonal action potential propagation velocities were lower than, for example, in rat primary cortical neurons (Bakkum et. al, Nature Communications, 2013). Furthermore, we found different axonal action-potential-velocity development profiles of A53T α-synuclein dopaminergic neurons and the wild-typecell line. Finally, we were able to precisely and reproducibly evoke action potentials in individual single human IPSC-derived neurons through subcellular-resolution electrical stimulation.
High-resolution MEA systems enable to access novel electrophysiological parameters of iPSC-derived neurons, which can be potentially used as biomarkers for phenotype screening and drug testing.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
High-resolution-microelectrode-array (MEA) technology enables to study neuronal dynamics at different scales, ranging from axonal physiology to network connectivity (Müller et. al, Lab on a Chip, 2015). We have used this MEA technology to characterize and compare the electrical phenotypes of commercially available human dopaminergic neurons (iCell DopaNeurons, MyCell DopaNeurons A53T α-synuclein, Cellular Dynamics International, Madison, WI, US). Furthermore, we have studied the effect of human astrocytes (iCell Astrocytes, Cellular Dynamics International, Madison, WI, US) on neural culture development.
Astrocyte/neuron co-cultures showed higher signal amplitudes and higher firing rates than neural cultures without astrocytes. Adding astrocytes to neural cultures changed the whole culture morphology by promoting cell clustering. Interestingly, astrocyte/neuron co-cultures showed a lower sample-to-sample variability across multiple MEA recording sessions compared to neural cultures without astrocytes.
We compared velocities of action potential propagation along axons between dopaminergic A53T α-synuclein neurons and the wild-type isogenic control cell line. We found that in both, wild-type and disease-model neurons, axonal action potential propagation velocities were lower than, for example, in rat primary cortical neurons (Bakkum et. al, Nature Communications, 2013). Furthermore, we found different axonal action-potential-velocity development profiles of A53T α-synuclein dopaminergic neurons and the wild-typecell line. Finally, we were able to precisely and reproducibly evoke action potentials in individual single human IPSC-derived neurons through subcellular-resolution electrical stimulation.
High-resolution MEA systems enable to access novel electrophysiological parameters of iPSC-derived neurons, which can be potentially used as biomarkers for phenotype screening and drug testing.
@conference{Urwyler2018,
title = {Electrical impedance tomography on high-density microelectrode arrays},
author = {Cedar Urwyler and Raziyeh Bounik and Vijay Viswam and Andreas Hierlemann },
url = {https://www.frontiersin.org/10.3389/conf.fncel.2018.38.00084/event_abstract},
doi = {10.3389/conf.fncel.2018.38.00084},
year = {2018},
date = {2018-07-04},
address = {Reutlingen, Germany},
organization = {11th International Meeting on Substrate Integrated Microelectrode Arrays (MEA Meeting)},
abstract = {Electrical impedance tomography (EIT) is a non-invasive, label-free imaging technique that enables to reconstruct the conductivity distribution in a body from a series of impedance measurements. Impedance measurements can be used to determine the position, morphology, and growth of cells or tissues, as well as pathological signs, e.g., precancerous tissue conditions (Gersing 1999). The newest high-density microelectrode array (MEA) system developed in our group features 59,760 integrated electrodes (Dragas et al. 2017). The chip features a variety of electrophysiological functions: Action-potential recording (2048 channels), cyclic voltammetry (28 channels), local-field-potential recording (32 channels) and extracellular stimulation (16 channels) [Fig 1A]. The chip can also measure impedance through 32 channels, which enables EIT measurements. We were able to establish a proof of concept for EIT (Viswam et al. 2017). The current goal of this project is to develop an impedance measurement protocol and an appropriate reconstruction algorithm that allow for single-cell-resolution impedance imaging.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Electrical impedance tomography (EIT) is a non-invasive, label-free imaging technique that enables to reconstruct the conductivity distribution in a body from a series of impedance measurements. Impedance measurements can be used to determine the position, morphology, and growth of cells or tissues, as well as pathological signs, e.g., precancerous tissue conditions (Gersing 1999). The newest high-density microelectrode array (MEA) system developed in our group features 59,760 integrated electrodes (Dragas et al. 2017). The chip features a variety of electrophysiological functions: Action-potential recording (2048 channels), cyclic voltammetry (28 channels), local-field-potential recording (32 channels) and extracellular stimulation (16 channels) [Fig 1A]. The chip can also measure impedance through 32 channels, which enables EIT measurements. We were able to establish a proof of concept for EIT (Viswam et al. 2017). The current goal of this project is to develop an impedance measurement protocol and an appropriate reconstruction algorithm that allow for single-cell-resolution impedance imaging.
@conference{Bartram2018b,
title = {Probing synaptic connectivity and function using high-density microelectrode arrays and whole-cell patch-clamp recordings},
author = {Julian Bartram and Manuel Schroter and Silvia Ronchi and Vishalini Emmenegger and Jan Muller and Andreas Hierlemann},
url = {https://www.frontiersin.org/10.3389/conf.fncel.2018.38.00085/5473/MEA_Meeting_2018_%7C_11th_International_Meeting_on_Substrate_Integrated_Microelectrode_Arrays/all_events/event_abstract},
doi = {10.3389/conf.fncel.2018.38.00085},
year = {2018},
date = {2018-07-04},
address = {Reutlingen, Germany},
organization = {11th International Meeting on Substrate Integrated Microelectrode Arrays (MEA Meeting)},
abstract = {Synaptic efficacy and synapse number of monosynaptic connections between neurons are often regulated by the spiking activity of the respective pre- and postsynaptic cell. Progress towards a better understanding of the rules and mechanisms that underlie such modifications has been limited due to the difficulties associated with simultaneously studying plasticity at multiple synaptic inputs. Here, we provide a solution to this problem by combining cutting-edge high-density microelectrode array (HD-MEA) technology with the patch-clamp technique. While the latter allows for accurate measurement of postsynaptic currents or potentials, evoked by individual synaptic activation, the HD-MEA technology provides large-scale information about unit activity and allows for selective stimulation of neurons, including multiple presynaptic cells. The proposed approach has been applied to comprehensively examine forms of homeostatic plasticity – a collection of crucial processes acting at different temporal scales in order to stabilize neuronal firing rates. We report on a characterization of classic synaptic scaling operating in mature cortical networks and propose a novel model for the study of homeostatic plasticity during natural network states.
},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Synaptic efficacy and synapse number of monosynaptic connections between neurons are often regulated by the spiking activity of the respective pre- and postsynaptic cell. Progress towards a better understanding of the rules and mechanisms that underlie such modifications has been limited due to the difficulties associated with simultaneously studying plasticity at multiple synaptic inputs. Here, we provide a solution to this problem by combining cutting-edge high-density microelectrode array (HD-MEA) technology with the patch-clamp technique. While the latter allows for accurate measurement of postsynaptic currents or potentials, evoked by individual synaptic activation, the HD-MEA technology provides large-scale information about unit activity and allows for selective stimulation of neurons, including multiple presynaptic cells. The proposed approach has been applied to comprehensively examine forms of homeostatic plasticity – a collection of crucial processes acting at different temporal scales in order to stabilize neuronal firing rates. We report on a characterization of classic synaptic scaling operating in mature cortical networks and propose a novel model for the study of homeostatic plasticity during natural network states.
@conference{Fiscella2018b,
title = {Electrophysiological phenotype characterization of human iPSC-derived dopaminergic neuronal lines by means of high-resolution microelelectrode arrays},
author = {Michele Fiscella and Noelle Leary and Silvia Ronchi and Andreas Hierlemann },
url = {http://www.isscr.org/docs/default-source/2018-melbourne-ann-mtng/66670-isscr-abstracts_with-links.pdf?sfvrsn=4&utm_source=ISSCR-Informz&utm_medium=email&utm_campaign=default},
year = {2018},
date = {2018-06-20},
volume = {W-2151},
address = {Melbourne, Australia},
organization = {International Society for Stem Cell Research (ISSCR) Annual Meeting},
abstract = {High-resolution-microelectrode-array (MEA) technology enables to study neuronal dynamics at different scales, ranging from axonal physiology to network connectivity (Müller et. al, Lab on a Chip, 2015). We have used this MEA technology to characterize and compare the electrical phenotypes of commercially available human dopaminergic neurons (iCell DopaNeurons, MyCell DopaNeurons A53T α-synuclein, Cellular Dynamics International, Madison, WI, US). Furthermore, we have studied the effect of human astrocytes (iCell Astrocytes, Cellular Dynamics International, Madison, WI, US) on neural culture development. Astrocyte/neuron co- cultures showed higher signal amplitudes and higher firing rates than neural cultures without astrocytes. Adding astrocytes to neural cultures changed the whole culture morphology by promoting cell clustering. Interestingly, astrocyte/neuron co-cultures showed a lower sample-to-sample variability across multiple MEA recordings compared to neural cultures without astrocytes. We compared action potential propagation velocities along axons between dopaminergic A53T α-synuclein neurons and the wild-type isogenic control cell line. We found that in both, wild-type and disease model neurons, axonal action potential propagation velocities were lower than in rat primary cortical neurons. Furthermore, we found different axonal action potential velocity development profiles of A53T α-synuclein dopaminergic neurons and the wild-type counterpart. Finally, we were able to precisely evoke action potentials in individual single human neurons by subcellular- resolution electrical stimulation. High-resolution MEA systems enable to access novel electrophysiological parameters of iPSC-derived neurons, which can be potentially used as biomarkers for phenotype screening and drug testing.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
High-resolution-microelectrode-array (MEA) technology enables to study neuronal dynamics at different scales, ranging from axonal physiology to network connectivity (Müller et. al, Lab on a Chip, 2015). We have used this MEA technology to characterize and compare the electrical phenotypes of commercially available human dopaminergic neurons (iCell DopaNeurons, MyCell DopaNeurons A53T α-synuclein, Cellular Dynamics International, Madison, WI, US). Furthermore, we have studied the effect of human astrocytes (iCell Astrocytes, Cellular Dynamics International, Madison, WI, US) on neural culture development. Astrocyte/neuron co- cultures showed higher signal amplitudes and higher firing rates than neural cultures without astrocytes. Adding astrocytes to neural cultures changed the whole culture morphology by promoting cell clustering. Interestingly, astrocyte/neuron co-cultures showed a lower sample-to-sample variability across multiple MEA recordings compared to neural cultures without astrocytes. We compared action potential propagation velocities along axons between dopaminergic A53T α-synuclein neurons and the wild-type isogenic control cell line. We found that in both, wild-type and disease model neurons, axonal action potential propagation velocities were lower than in rat primary cortical neurons. Furthermore, we found different axonal action potential velocity development profiles of A53T α-synuclein dopaminergic neurons and the wild-type counterpart. Finally, we were able to precisely evoke action potentials in individual single human neurons by subcellular- resolution electrical stimulation. High-resolution MEA systems enable to access novel electrophysiological parameters of iPSC-derived neurons, which can be potentially used as biomarkers for phenotype screening and drug testing.
@conference{Viswam2017b,
title = {High-density Mapping of Brain Slices Using a Large Multi-functional High-density CMOS Microelectrode Array System},
author = {Vijay Viswam and Raziyeh Bounik and Amir Shadmani and Jelena Dragas and Marie Engelene J. Obien and Jan Muller and Yihui Chen and Andreas Hierlemann },
url = {https://ieeexplore.ieee.org/abstract/document/7994006},
doi = {10.1109/TRANSDUCERS.2017.7994006},
issn = {2167-0021},
year = {2017},
date = {2017-06-18},
pages = {135-138},
address = {Kaohsiung, Taiwan},
organization = {19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS)},
abstract = {We present a CMOS-based high-density microelectrode array (HD-MEA) system that enables high-density mapping of brain slices in-vitro with multiple readout modalities. The 4.48×2.43 mm 2 array consists of 59,760 micro-electrodes at 13.5 μm pitch (5487 electrodes/mm 2 ). The overall system features 2048 action-potential, 32 local-field-potential and 32 current recording channels, 32 impedance-measurement and 28 neurotransmitter-detection channels and 16 voltage/current stimulation channels. The system enables real-time and label-free monitoring of position, size, morphology and electrical activity of brain slices.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
We present a CMOS-based high-density microelectrode array (HD-MEA) system that enables high-density mapping of brain slices in-vitro with multiple readout modalities. The 4.48×2.43 mm 2 array consists of 59,760 micro-electrodes at 13.5 μm pitch (5487 electrodes/mm 2 ). The overall system features 2048 action-potential, 32 local-field-potential and 32 current recording channels, 32 impedance-measurement and 28 neurotransmitter-detection channels and 16 voltage/current stimulation channels. The system enables real-time and label-free monitoring of position, size, morphology and electrical activity of brain slices.
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