Scientific Data (Oct 2023)

A comparison of neuroelectrophysiology databases

  • Priyanka Subash,
  • Alex Gray,
  • Misque Boswell,
  • Samantha L. Cohen,
  • Rachael Garner,
  • Sana Salehi,
  • Calvary Fisher,
  • Samuel Hobel,
  • Satrajit Ghosh,
  • Yaroslav Halchenko,
  • Benjamin Dichter,
  • Russell A. Poldrack,
  • Chris Markiewicz,
  • Dora Hermes,
  • Arnaud Delorme,
  • Scott Makeig,
  • Brendan Behan,
  • Alana Sparks,
  • Stephen R Arnott,
  • Zhengjia Wang,
  • John Magnotti,
  • Michael S. Beauchamp,
  • Nader Pouratian,
  • Arthur W. Toga,
  • Dominique Duncan

DOI
https://doi.org/10.1038/s41597-023-02614-0
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 18

Abstract

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Abstract As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial neuroelectrophysiology data repositories: Data Archive for the BRAIN Initiative (DABI), Distributed Archives for Neurophysiology Data Integration (DANDI), OpenNeuro, and Brain-CODE. The aim of this review is to describe archives that provide researchers with tools to store, share, and reanalyze both human and non-human neurophysiology data based on criteria that are of interest to the neuroscientific community. The Brain Imaging Data Structure (BIDS) and Neurodata Without Borders (NWB) are utilized by these archives to make data more accessible to researchers by implementing a common standard. As the necessity for integrating large-scale analysis into data repository platforms continues to grow within the neuroscientific community, this article will highlight the various analytical and customizable tools developed within the chosen archives that may advance the field of neuroinformatics.