PT  - JOURNAL ARTICLE
AU  - John F. Magnotti
AU  - Zhengjia Wang
AU  - Michael S. Beauchamp
TI  - RAVE: comprehensive open-source software for reproducible analysis and visualization of intracranial EEG data
AID  - 10.1101/2020.06.02.129676
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.06.02.129676
4099  - http://biorxiv.org/content/early/2020/06/03/2020.06.02.129676.short
4100  - http://biorxiv.org/content/early/2020/06/03/2020.06.02.129676.full
AB  - 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 StatementThe authors have declared no competing interest.