@article{Kasuba2024,
title = {Mechanical stimulation and electrophysiological monitoring at subcellular resolution reveals differential mechanosensation of neurons within networks},
author = {Krishna Chaitanya Kasuba and Alessio Paolo Buccino and Julian Bartram and Benjamin M. Gaub and Felix J. Fauser and Silvia Ronchi and Sreedhar Saseendran Kumar and Sydney Geissler and Michele M. Nava and Andreas Hierlemann and Daniel J. Müller },
url = {https://www.nature.com/articles/s41565-024-01609-1},
doi = {10.1038/s41565-024-01609-1},
year = {2024},
date = {2024-02-20},
journal = {Nature Nanotechnology},
abstract = {A growing consensus that the brain is a mechanosensitive organ is driving the need for tools that mechanically stimulate and simultaneously record the electrophysiological response of neurons within neuronal networks. Here we introduce a synchronized combination of atomic force microscopy, high-density microelectrode array and fluorescence microscopy to monitor neuronal networks and to mechanically characterize and stimulate individual neurons at piconewton force sensitivity and nanometre precision while monitoring their electrophysiological activity at subcellular spatial and millisecond temporal resolution. No correlation is found between mechanical stiffness and electrophysiological activity of neuronal compartments. Furthermore, spontaneously active neurons show exceptional functional resilience to static mechanical compression of their soma. However, application of fast transient (∼500 ms) mechanical stimuli to the neuronal soma can evoke action potentials, which depend on the anchoring of neuronal membrane and actin cytoskeleton. Neurons show higher responsivity, including bursts of action potentials, to slower transient mechanical stimuli (∼60 s). Moreover, transient and repetitive application of the same compression modulates the neuronal firing rate. Seemingly, neuronal networks can differentiate and respond to specific characteristics of mechanical stimulation. Ultimately, the developed multiparametric tool opens the door to explore manifold nanomechanobiological responses of neuronal systems and new ways of mechanical control.},
keywords = {Action Potential, Brain Slice, HD-MEA, MaxOne, Primary Neuronal Cell Culture, Spike Sorting},
pubstate = {published},
tppubtype = {article}
}
A growing consensus that the brain is a mechanosensitive organ is driving the need for tools that mechanically stimulate and simultaneously record the electrophysiological response of neurons within neuronal networks. Here we introduce a synchronized combination of atomic force microscopy, high-density microelectrode array and fluorescence microscopy to monitor neuronal networks and to mechanically characterize and stimulate individual neurons at piconewton force sensitivity and nanometre precision while monitoring their electrophysiological activity at subcellular spatial and millisecond temporal resolution. No correlation is found between mechanical stiffness and electrophysiological activity of neuronal compartments. Furthermore, spontaneously active neurons show exceptional functional resilience to static mechanical compression of their soma. However, application of fast transient (∼500 ms) mechanical stimuli to the neuronal soma can evoke action potentials, which depend on the anchoring of neuronal membrane and actin cytoskeleton. Neurons show higher responsivity, including bursts of action potentials, to slower transient mechanical stimuli (∼60 s). Moreover, transient and repetitive application of the same compression modulates the neuronal firing rate. Seemingly, neuronal networks can differentiate and respond to specific characteristics of mechanical stimulation. Ultimately, the developed multiparametric tool opens the door to explore manifold nanomechanobiological responses of neuronal systems and new ways of mechanical control.
@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.
@inbook{Kubota2019b,
title = {Echo State Property of Neuronal Cell Cultures},
author = {Tomoyuki Kubota and Kohei Nakajima and Hirokazu Takahashi },
url = {https://link.springer.com/chapter/10.1007%2F978-3-030-30493-5_13},
doi = {10.1007/978-3-030-30493-5_13},
isbn = {978-3-030-30493-5},
year = {2019},
date = {2019-09-09},
volume = {11731},
publisher = {Springer},
abstract = {Physical reservoir computing (PRC) utilizes the nonlinear dynamics of physical systems, which is called a reservoir, as a computational resource. The prerequisite for physical dynamics to be a successful reservoir is to have the echo state property (ESP), asymptotic properties of transient trajectory to driving signals, with some memory held in the system. In this study, the prerequisites in dissociate cultures of cortical neuronal cells are estimated. With a state-of-the-art measuring system of high-dense CMOS array, our experiments demonstrated that each neuron exhibited reproducible spike trains in response to identical driving stimulus. Additionally, the memory function was estimated, which found that input information in the dynamics of neuronal activities in the culture up to at least 20 ms was retrieved. These results supported the notion that the cultures had ESP and could thereby serve as PRC.},
keywords = {Action Potential, MaxOne, Neuronal cell culture},
pubstate = {published},
tppubtype = {inbook}
}
Physical reservoir computing (PRC) utilizes the nonlinear dynamics of physical systems, which is called a reservoir, as a computational resource. The prerequisite for physical dynamics to be a successful reservoir is to have the echo state property (ESP), asymptotic properties of transient trajectory to driving signals, with some memory held in the system. In this study, the prerequisites in dissociate cultures of cortical neuronal cells are estimated. With a state-of-the-art measuring system of high-dense CMOS array, our experiments demonstrated that each neuron exhibited reproducible spike trains in response to identical driving stimulus. Additionally, the memory function was estimated, which found that input information in the dynamics of neuronal activities in the culture up to at least 20 ms was retrieved. These results supported the notion that the cultures had ESP and could thereby serve as PRC.
@article{Mita2019,
title = {Classification of Inhibitory and Excitatory Neurons of Dissociated Cultures Based on Action Potential Waveforms on High-density CMOS Microelectrode Arrays},
author = {Takeshi Mita and Douglas J. Bakkum and Urs Frey and Andreas Hierlemann and Ryohei Kanzaki and Hirokazu Takahashi },
url = {https://www.jstage.jst.go.jp/article/ieejeiss/139/5/139_615/_article/-char/en},
doi = {10.1541/ieejeiss.139.615},
issn = {1348-8155},
year = {2019},
date = {2019-05-01},
journal = {IEEJ Transactions on Electronics, Information and Systems},
volume = {139},
number = {5},
pages = {615-624},
abstract = {Electrophysiological data from in vivo and slice preparations show that inhibitory neurons had shorter duration action potentials (AP) than excitatory neurons. However, this criterion has not yet been established in dissociated cultured neurons. In the present study, we used a high-density CMOS microelectrode array to extracellularly investigate neural signals in primary dissociated cultures of rat neocortex, and we characterized AP waveforms to discriminate excitatory and inhibitory neurons. The CMOS array offers the possibility to acquire comprehensive spatio-temporal neural activity patterns with 11,011 electrodes in about 2×1.75 mm2 area at 20-kHz sampling rate. The waveforms of APs were investigated around cell bodies of neurons, which were classified into either excitatory neurons or inhibitory neurons on the basis of MAP2 and GABA immunostaining images. Consistent with previous in vivo and slice studies, we demonstrated that AP waveforms of inhibitory neurons had shorter durations and recovery time than those of excitatory neurons. The discrimination accuracy was around 0.9 in the receiver-operating characteristics (ROC) analyses. Additionally, taking advantage of non-invasive CMOS recording, we investigated AP waveforms throughout development of cultures. We confirmed that APs were classified into two classes, i.e., putative excitatory and inhibitory neurons, regardless of developmental stages, and found that the duration and recovery time of AP shortened in matured cultures. Thus, AP waveforms have rich information about cell types and developmental stages, which are of worth to elucidate underlying mechanisms of neuronal dynamics in spatio-temporal patterns.},
keywords = {Action Potential, HD-MEA},
pubstate = {published},
tppubtype = {article}
}
Electrophysiological data from in vivo and slice preparations show that inhibitory neurons had shorter duration action potentials (AP) than excitatory neurons. However, this criterion has not yet been established in dissociated cultured neurons. In the present study, we used a high-density CMOS microelectrode array to extracellularly investigate neural signals in primary dissociated cultures of rat neocortex, and we characterized AP waveforms to discriminate excitatory and inhibitory neurons. The CMOS array offers the possibility to acquire comprehensive spatio-temporal neural activity patterns with 11,011 electrodes in about 2×1.75 mm2 area at 20-kHz sampling rate. The waveforms of APs were investigated around cell bodies of neurons, which were classified into either excitatory neurons or inhibitory neurons on the basis of MAP2 and GABA immunostaining images. Consistent with previous in vivo and slice studies, we demonstrated that AP waveforms of inhibitory neurons had shorter durations and recovery time than those of excitatory neurons. The discrimination accuracy was around 0.9 in the receiver-operating characteristics (ROC) analyses. Additionally, taking advantage of non-invasive CMOS recording, we investigated AP waveforms throughout development of cultures. We confirmed that APs were classified into two classes, i.e., putative excitatory and inhibitory neurons, regardless of developmental stages, and found that the duration and recovery time of AP shortened in matured cultures. Thus, AP waveforms have rich information about cell types and developmental stages, which are of worth to elucidate underlying mechanisms of neuronal dynamics in spatio-temporal patterns.
@article{Emmenegger2019,
title = {Technologies to Study Action Potential Propagation With a Focus on HD-MEAs},
author = {Vishalini Emmenegger and Marie Engelene J. Obien and Felix Franke and Andreas Hierlemann},
url = {https://www.frontiersin.org/articles/10.3389/fncel.2019.00159/full},
doi = {10.3389/fncel.2019.00159 },
issn = {1662-5102 },
year = {2019},
date = {2019-04-26},
journal = {Frontiers in Cellular Neuroscience},
volume = {13},
pages = {1-11},
abstract = {Axons convey information in neuronal circuits via reliable conduction of action potentials from the axon initial segment to the presynaptic terminals. Recent experimental findings increasingly evidence that the axonal function is not limited to the simple transmission of action potentials. Advances in subcellular-resolution recording techniques have shown that axons display activity-dependent modulation in spike shape and conduction velocity, which influence synaptic strength and latency. We briefly review, here, how recent methodological developments facilitate the understanding of the axon physiology. We included the three most common methods, i.e. genetically encoded voltage imaging, subcellular patch-clamp and high-density microelectrode arrays (HD-MEAs). We then describe the potential of using HD-MEAs in studying axonal physiology in more detail. Due to their robustness, amenability to high-throughput and high spatiotemporal resolution, HD-MEAs can provide a direct functional electrical readout of single cells and cellular ensembles at subcellular resolution. HD-MEAs can, therefore, be employed in investigating axonal pathologies, the effects of large-scale genomic interventions (e.g., with RNAi or CRISPR) or in compound screenings. A combination of extracellular microelectrode arrays, intracellular microelectrodes and optical imaging may potentially reveal yet unexplored repertoires of axonal functions.},
keywords = {Action Potential, HD-MEA},
pubstate = {published},
tppubtype = {article}
}
Axons convey information in neuronal circuits via reliable conduction of action potentials from the axon initial segment to the presynaptic terminals. Recent experimental findings increasingly evidence that the axonal function is not limited to the simple transmission of action potentials. Advances in subcellular-resolution recording techniques have shown that axons display activity-dependent modulation in spike shape and conduction velocity, which influence synaptic strength and latency. We briefly review, here, how recent methodological developments facilitate the understanding of the axon physiology. We included the three most common methods, i.e. genetically encoded voltage imaging, subcellular patch-clamp and high-density microelectrode arrays (HD-MEAs). We then describe the potential of using HD-MEAs in studying axonal physiology in more detail. Due to their robustness, amenability to high-throughput and high spatiotemporal resolution, HD-MEAs can provide a direct functional electrical readout of single cells and cellular ensembles at subcellular resolution. HD-MEAs can, therefore, be employed in investigating axonal pathologies, the effects of large-scale genomic interventions (e.g., with RNAi or CRISPR) or in compound screenings. A combination of extracellular microelectrode arrays, intracellular microelectrodes and optical imaging may potentially reveal yet unexplored repertoires of axonal functions.
@conference{Obien2017,
title = {Mapping neuron cluster development based on axonal action potential propagation},
author = {Marie Engelene J. Obien and Giulio Zorzi and Andreas Hierlemann},
year = {2017},
date = {2017-07-20},
address = {Chiba, Japan},
organization = {The 40th Annual Meeting of the Japan Neuroscience Society},
keywords = {Action Potential, Neuronal Networks},
pubstate = {published},
tppubtype = {conference}
}
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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