2 research outputs found
A Comparison of Neuroelectrophysiology Databases
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. These
archives provide researchers with tools to store, share, and reanalyze
neurophysiology data though the means of accomplishing these objectives differ.
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. While many tools are available to reanalyze
data on and off the archives' platforms, this article features Reproducible
Analysis and Visualization of Intracranial EEG (RAVE) toolkit, developed
specifically for the analysis of intracranial signal data and integrated with
the discussed standards and archives. Neuroelectrophysiology data archives
improve how researchers can aggregate, analyze, distribute, and parse these
data, which can lead to more significant findings in neuroscience research.Comment: 25 pages, 8 figures, 1 tabl
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A comparison of neuroelectrophysiology databases
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