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RAVE: comprehensive open-source software for reproducible analysis and visualization of intracranial EEG data

John F. Magnotti, Zhengjia Wang, View ORCID ProfileMichael S. Beauchamp
doi: https://doi.org/10.1101/2020.06.02.129676
John F. Magnotti
1Department of Neurosurgery, Baylor College of Medicine
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Zhengjia Wang
2Graduate Program in Statistics, Rice University
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Michael S. Beauchamp
1Department of Neurosurgery, Baylor College of Medicine
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  • ORCID record for Michael S. Beauchamp
  • For correspondence: michael.beauchamp@bcm.edu
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Abstract

Direct recording of neural activity from the human brain using implanted electrodes (iEEG, intracranial electroencephalography) is a fast-growing technique in human neuroscience. While the ability to record from the human brain with high spatial and temporal resolution has advanced our understanding, it generates staggering amounts of data: a single patient can be implanted with hundreds of electrodes, each sampled thousands of times a second for hours or days. The difficulty of exploring these vast datasets is the rate-limiting step in discovery. To overcome this obstacle, we created RAVE (“R Analysis and Visualization of iEEG”). All components of RAVE, including the underlying “R” language, are free and open source. User interactions occur through a web browser, making it transparent to the user whether the back-end data storage and computation is occurring on a local machine, a lab server, or in the cloud. Without writing a single line of computer code, users can create custom analyses, apply them to data from hundreds of iEEG electrodes, and instantly visualize the results on cortical surface models. Multiple types of plots are used to display analysis results, each of which can be downloaded as publication-ready graphics with a single click. RAVE consists of nearly 50,000 lines of code designed to prioritize an interactive user experience, reliability and reproducibility.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://openwetware.org/wiki/RAVE

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted June 03, 2020.
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RAVE: comprehensive open-source software for reproducible analysis and visualization of intracranial EEG data
John F. Magnotti, Zhengjia Wang, Michael S. Beauchamp
bioRxiv 2020.06.02.129676; doi: https://doi.org/10.1101/2020.06.02.129676
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RAVE: comprehensive open-source software for reproducible analysis and visualization of intracranial EEG data
John F. Magnotti, Zhengjia Wang, Michael S. Beauchamp
bioRxiv 2020.06.02.129676; doi: https://doi.org/10.1101/2020.06.02.129676

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