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Review ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Neuroinform. | doi: 10.3389/fninf.2019.00057

Comparing open-source toolboxes for processing and analysis of spike and local field potentials data

  • 1Cognitive Neuroscience Laboratory, Deutsches Primatenzentrum, Germany
  • 2Primate Cognition, Leibniz Science Campus Primacy Cognition, University of Göttingen, Germany
  • 3Department of Economic and Social Psychology, Institute of Psychology, Georg-August-University Goettingen, Germany
  • 4Bernstein Center for Computational Neuroscience, Germany

Analysis of spike and local field potential (LFP) data is an essential part of neuroscientific research. Today there exist many open-source toolboxes for spike and LFP data analysis implementing various functionality. Here we aim to provide a practical guidance for neuroscientists in the choice of an open-source toolbox best satisfying their needs. We overview major open-source toolboxes for spike and LFP data analysis as well as toolboxes with tools for connectivity analysis, dimensionality reduction and generalized linear modeling. We focus on comparing toolboxes functionality, statistical and visualization tools, documentation and support quality. To give a better insight, we compare and illustrate functionality of the toolboxes on open-access dataset or simulated data and make corresponding MATLAB scripts publicly available.

Keywords: Spike data, LFP = local field potential, Toolbox, MATLAB, open-source, Python (programming language), dimensionality reduction, GLM

Received: 12 Apr 2019; Accepted: 11 Jul 2019.

Edited by:

Andrew P. Davison, UMR9197 Institut des Neurosciences Paris Saclay (Neuro-PSI), France

Reviewed by:

Sonja Grün, Julich Research Centre, Germany
Henrik Lindén, University of Copenhagen, Denmark  

Copyright: © 2019 Unakafova and Gail. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Valentina A. Unakafova, Deutsches Primatenzentrum, Cognitive Neuroscience Laboratory, Göttingen, Germany, unakafovavalentina@gmail.com