Automated in vivo patch-clamp evaluation of extracellular multielectrode array spike recording capability
Name
905f4e7ab2aba6657a90a6cc7a147e6dee84.pdf
Description
Accepted version
Size
3.15 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Allen, Brian D
Moore-Kochlacs, Caroline
Bernstein, Jacob G
Kinney, Justin P
Scholvin, Jorg
Seoane, Luís F
Chronopoulos, Chris
Lamantia, Charlie
Kodandaramaiah, Suhasa B
Tegmark, Max
Date Issued
2018
Journal
Journal of Neurophysiology
Publisher
American Physiological Society
Version
Author's final manuscript
Abstract
© 2018 American Physiological Society. All rights reserved. Much innovation is currently aimed at improving the number, density, and geometry of electrodes on extracellular multielectrode arrays for in vivo recording of neural activity in the mammalian brain. To choose a multielectrode array configuration for a given neuroscience purpose, or to reveal design principles of future multielectrode arrays, it would be useful to have a systematic way of evaluating the spike recording capability of such arrays. We describe an automated system that performs robotic patch-clamp recording of a neuron being simultaneously recorded via an extracellular multielectrode array. By recording a patch-clamp data set from a neuron while acquiring extracellular recordings from the same neuron, we can evaluate how well the extracellular multielectrode array captures the spiking information from that neuron. To demonstrate the utility of our system, we show that it can provide data from the mammalian cortex to evaluate how the spike sorting performance of a close-packed extracellular multielectrode array is affected by bursting, which alters the shape and amplitude of spikes in a train. We also introduce an algorithmic framework to help evaluate how the number of electrodes in a multielectrode array affects spike sorting, examining how adding more electrodes yields data that can be spike sorted more easily. Our automated methodology may thus help with the evaluation of new electrode designs and configurations, providing empirical guidance on the kinds of electrodes that will be optimal for different brain regions, cell types, and species, for improving the accuracy of spike sorting. NEW & NOTEWORTHY We present an automated strategy for evaluating the spike recording performance of an extracellular multielectrode array, by enabling simultaneous recording of a neuron with both such an array and with patch clamp. We use our robot and accompanying algorithms to evaluate the performance of multielectrode arrays on supporting spike sorting.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
McGovern Institute for Brain Research at MIT
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
MIT Kavli Institute for Astrophysics and Space Research
Massachusetts Institute of Technology. Department of Physics
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1152/JN.00650.2017
