Austin Health

Title
meaRtools: An R package for the analysis of neuronal networks recorded on microelectrode arrays.
Publication Date
2018-10
Author(s)
Gelfman, Sahar
Wang, Quanli
Lu, Yi-Fan
Hall, Diana
Bostick, Christopher D
Dhindsa, Ryan
Halvorsen, Matt
McSweeney, K Melodi
Cotterill, Ellese
Edinburgh, Tom
Beaumont, Michael A
Frankel, Wayne N
Petrovski, Slavé
Allen, Andrew S
Boland, Michael J
Goldstein, David B
Eglen, Stephen J
Type of document
Journal Article
OrcId
0000-0002-4727-7862
0000-0001-5462-4407
0000-0002-8965-0813
0000-0002-6707-2418
0000-0003-4760-9748
0000-0002-1527-961X
0000-0001-8607-8025
DOI
10.1371/journal.pcbi.1006506
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/.
Link
Citation
PLoS computational biology 2018; 14(10): e1006506
Jornal Title
PLoS computational biology

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