meaRtools: An R package for the analysis of neuronal networks recorded on microelectrode arrays

Sahar Gelfman, Quanli Wang, Yi-Fan Lu, Diana Hall, Christopher D Bostick, Ryan Dhindsa, Matt Halvorsen, K Melodi McSweeney, Ellese Cotterill, Tom Edinburgh, Michael A Beaumont, Wayne N Frankel, Slavé Petrovski, Andrew S Allen, Michael J Boland, David B Goldstein and Stephen J Eglen

PLOS Computational Biology, 2018, vol. 14, issue 10, 1-20

Abstract: Here we present an open-source R package ‘meaRtools’ that provides a platform for analyzing neuronal networks recorded on Microelectrode Arrays (MEAs). Cultured neuronal networks monitored with MEAs are now being widely used to characterize in vitro models of neurological disorders and to evaluate pharmaceutical compounds. meaRtools provides core algorithms for MEA spike train analysis, feature extraction, statistical analysis and plotting of multiple MEA recordings with multiple genotypes and treatments. meaRtools functionality covers novel solutions for spike train analysis, including algorithms to assess electrode cross-correlation using the spike train tiling coefficient (STTC), mutual information, synchronized bursts and entropy within cultured wells. Also integrated is a solution to account for bursts variability originating from mixed-cell neuronal cultures. The package provides a statistical platform built specifically for MEA data that can combine multiple MEA recordings and compare extracted features between different genetic models or treatments. We demonstrate the utilization of meaRtools to successfully identify epilepsy-like phenotypes in neuronal networks from Celf4 knockout mice. The package is freely available under the GPL license (GPL> = 3) and is updated frequently on the CRAN web-server repository. The package, along with full documentation can be downloaded from: https://cran.r-project.org/web/packages/meaRtools/.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1006506

DOI: 10.1371/journal.pcbi.1006506

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