New Events! (May 19, 2025)

RAVE invited tutorial will be given at ASA Statistics in Imaging Section (2025)

Date: May 19, 2025
Time: 8:00 - 9:15 AM
Location: Rice University, Houston, TX

Past events
  • Oct 06, 2024: RAVE has been selected to exhibit at Building Tools & Tech for an Innovative Future: A BRAIN Initiative Alliance Social during the Society for Neuroscience
  • Oct 18, 2022: Workshop on intracranial EEG analysis 4th Floor Atrium of the Lister Hill Library (Center for Teaching and Learning, formerly Edge of Chaos

Background photo -
RAVE highlighted at Dr. Iahn Cajigas’s talk @ CNS 2024

Power Explorer

Interactive RAVE module for exploratory time-frequency analysis and visualization

YAEL: Your Advanced Electrode Localization

RAVE module for automatic localizing and visualizing electrodes. See a demo result

RAVE
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RAVE: Reproducible Analysis & Visualization of iEEG

RAVE is free and open-source software for the analysis of intracranial electroencephalogram (iEEG) data, including data collected using strips and grids (electrocorticography, ECoG) and depth electrodes (stereotactic EEG). A sister package to RAVE is the YAEL electrode localization toolkit.

RAVE is easy to use and creates publication-ready figures with absolutely no programming. RAVE can import standard data formats, including Matlab and EDF, and is compatible with BIDS-iEEG. It runs on laptops, lab servers, or in the cloud. Since all user interactions take place through a web browser, the user experience is identical on Mac, Windows and Linux. Data from RAVE can be exported for analysis using other software (click here for a list of iEEG analysis tools). Conversely, outside results can be imported and visualized using RAVE’s visualization engine. RAVE provides templates to make it easy to create GUI-based analyses using the streamlined application programming interface.

Join our growing RAVE-iEEG community on Github . E-mail help@rave.wiki for walk-through, or post questions/discussions at our new community forum

RAVE has been developed since 2017 with funding provided by NIH R01MH133717 , U01NS113339, and 1R24MH117529. If you use RAVE for a publication, please cite:

Magnotti JF, Wang Z, Beauchamp MS. RAVE: comprehensive open-source software for reproducible analysis and visualization of intracranial EEG data. NeuroImage (2020) 223:117341. [Click here for the journal full text] [Click here for the PDF] [Click here for the preprint].

If you use YAEL for electrode localization, please cite:

Wang Z, Magnotti JF, Zhang X, Beauchamp MS. YAEL: Your Advanced Electrode Localizer. Eneuro. 2023 Oct 1;10(10). [Click here for the journal full text] [Click here for the PDF] [Click here for the preprint].

Installation

Please check our full installation guide here.

Publications

Send us your (p)reprint and we will add it to the list!

RAVE: Comprehensive open-source software for reproducible analysis and visualization of intracranial EEG data
John F. Magnotti, Zhengjia Wang, and Michael S. Beauchamp
NeuroImage , Dec 2020
DOI: 10.1016/j.neuroimage.2020.117341
YAEL: Your Advanced Electrode Localizer
Zhengjia Wang, John F. Magnotti, Xiang Zhang, and Michael S. Beauchamp
eNeuro , Oct 2023
DOI: 10.1523/ENEURO.0328-23.2023
Beta activity in human anterior cingulate cortex mediates reward biases
Jiayang Xiao, Joshua A. Adkinson, John Myers, Anusha B. Allawala, Raissa K. Mathura, Victoria Pirtle, Ricardo Najera, Nicole R. Provenza, Eleonora Bartoli, Andrew J. Watrous, Denise Oswalt, Ron Gadot, Adrish Anand, Ben Shofty, Sanjay J. Mathew, Wayne K. Goodman, Nader Pouratian, Xaq Pitkow, Kelly R. Bijanki, Benjamin Hayden, and Sameer A. Sheth
Nature Communications , July 2024
DOI: 10.1038/s41467-024-49600-7
Bayesian Image-on-Scalar Regression with a Spatial Global-Local Spike-and-Slab Prior
Zijian Zeng, Meng Li, and Marina Vannucci
Bayesian Analysis , Mar 2024
DOI: 10.1016/j.brs.2022.03.002
Intracranial stimulation and EEG feature analysis reveal affective salience network specialization
Brian A. Metzger, Prathik Kalva, Madaline M. Mocchi, Brian Cui, and Joshua A. Adkinson, Zhengjia Wang, Raissa Mathura, Kourtney Kanja, Jay Gavvala, Vaishnav Krishnan, Lu Lin, Atul Maheshwari, Ben Shofty, John F. Magnotti, Jon T. Willie, Sameer A. Sheth, Kelly R. Bijanki
Brain: A Journal of Neurology , Oct 2023
DOI: 10.1093/brain/awad200
Functional group bridge for simultaneous regression and support estimation
Zhengjia Wang, John Magnotti, Michael S. Beauchamp, and Meng Li
Biometrics , Jun 2023
DOI: 10.1111/biom.13684
Imaging versus electrographic connectivity in human mood-related fronto-temporal networks
Joshua A. Adkinson, Evangelia Tsolaki, Sameer A. Sheth, Brian A. Metzger, and Meghan E. Robinson, Denise Oswalt, Cameron C. McIntyre, Raissa K. Mathura, Allison C. Waters, Anusha B. Allawala, Angela M. Noecker, Mahsa Malekmohammadi, Kevin Chiu, Richard Mustakos, Wayne Goodman, David Borton, Nader Pouratian, Kelly R. Bijanki
Brain Stimulation , May 2022
DOI: 10.1016/j.brs.2022.03.002
Responses to Visual Speech in Human Posterior Superior Temporal Gyrus Examined with iEEG Deconvolution
Brian A. Metzger, John F. Magnotti, Zhengjia Wang, Elizabeth Nesbitt, and Patrick J. Karas, Daniel Yoshor, Michael S. Beauchamp
The Journal of Neuroscience: The Official Journal of the Society for Neuroscience , Sep 2020
DOI: 10.1523/JNEUROSCI.0279-20.2020
The visual speech head start improves perception and reduces superior temporal cortex responses to auditory speech
Patrick J Karas, John F Magnotti, Brian A Metzger, Lin L Zhu, and Kristen B Smith, Daniel Yoshor, Michael S Beauchamp
eLife , Aug 2019
DOI: 10.7554/eLife.48116

Credit Zhengjia Wang for creating the website.

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