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Compact 256-channel multi-well microelectrode array system for: In vitro neuropharmacology test

Cited 10 time in Web of Science Cited 9 time in Scopus
Authors

Kim, Daejeong; Kang, Hongki; Nam, Yoonkey

Issue Date
2020-09
Publisher
Royal Society of Chemistry
Citation
Lab on a Chip, Vol.20 No.18, pp.3410-3422
Abstract
Microelectrode arrays (MEAs) have been extensively used to measure extracellular spike activity from cultured neurons using multiple electrodes embedded in a planar glass substrate. This system has been implemented to investigate drug effects by detecting pharmacological perturbation reflected in spontaneous network activity. By configuring multiple wells in an MEA, a high-throughput electrophysiological assay has become available, speeding up drug tests. Despite its merits in acquiring massive amounts of electrophysiological data, the high cost and the bulky size of commercial multi-well MEA systems and most importantly its lack of customizability prevent potential users from fully implementing the system in drug experiments. In this work, we have developed a microelectrode array based drug testing platform by incorporating a custom-made compact 256-channel multi-well MEA in a standard microscope slide and commercial application-specific integrated circuit (ASIC) chip based recording system. We arranged 256 electrodes in 16 wells to maximize data collection from a single chip. The multi-well MEA in this work has a more compact design with reduced chip size compared to previously reported multi-well MEAs. Four synaptic modulators (NMDA, AMPA, bicuculline (BIC) and ATP) were applied to a multi-well MEA and neural spike activity was analyzed to study their neurophysiological effects on cultured neurons. Analyzing various neuropharmacological compounds has become much more accessible by utilizing commercially available digital amplifier chips and customizing a user-preferred analog-front-end interface design with additional benefits in reduced platform size and cost.
ISSN
1473-0197
URI
https://hdl.handle.net/10371/203107
DOI
https://doi.org/10.1039/d0lc00384k
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  • College of Medicine
  • Department of Medicine
Research Area Biosensors, Microelectronics, Neurotechnology

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