index.qmd

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title: "RAVE"
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        Cover Images
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            <a href="https://www.jneurosci.org/content/45/42.cover-expansion" target="_blank">
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            <a href="https://www.sciencedirect.com/science/article/pii/S1053811920308272" target="_blank">
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        <p class="text-start">
        Please check out our posters at sfN 2025! <br />
        &nbsp;&nbsp;  Date: Nov 17, 2025 <br />
        &nbsp;&nbsp;  Location: San Diego Convention Center
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          <details class="text-start">
            <summary>Past events</summary>
            <ul>
              <li>May 19, 2025" RAVE invited tutorial will be given at <i>[ASA Statistics in Imaging Section](https://statistics.rice.edu/events/2025-statistical-methods-imaging-conference)</i></li>
              <li>Oct 06, 2024: RAVE has been selected to exhibit at <i>[Building Tools & Tech for an Innovative Future: A BRAIN Initiative Alliance Social](https://www.braininitiative.org/events/sfn-social/){target="_blank"}</i> during the Society for Neuroscience</li>
              <li>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](https://sites.uab.edu/cnbci/education/workshops/)</li>
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            Background photo - <br/>RAVE highlighted at Dr. Iahn Cajigas's talk @ CNS 2024
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        Power Explorer
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        Interactive RAVE module for exploratory time-frequency analysis and visualization
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        YAEL: Your Advanced Electrode Localization
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        RAVE module for automatic localizing and visualizing electrodes. [See a demo result](/posts/3dviewer/viewer301.html?viewer=full){target="_blank"}
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## RAVE: Reproducible Analysis & Visualization of iEEG {{< ai open-access >}}

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](https://yael.wiki).

[<iframe width="480" height="270" src="https://www.youtube-nocookie.com/embed/s6EnlqF-Q8E"
    title="RAVE Highlights" frameborder="0" 
    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
    referrerpolicy="strict-origin-when-cross-origin" 
    allowfullscreen> </iframe>]{#rave-intro-video style="width: 480px; display: block; float: right;"} 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](https://openwetware.org/wiki/RAVE:SoftwareToolsTable)). 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 {{< fa brands github >}}. E-mail [help\@rave.wiki](mailto:help@rave.wiki) for walk-through, or post questions/discussions at our [new community forum](https://github.com/orgs/rave-ieeg/discussions)

## Attribution

RAVE has been developed since 2017 with funding provided by NIH `R01MH133717` , `U01NS113339`, and `1R24MH117529`, released under [creative-common ({{< fa brands creative-commons >}}{{< fa brands creative-commons-by >}})](https://creativecommons.org/licenses/by/4.0/) license. 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. \[[Click here for the journal full text](https://www.sciencedirect.com/science/article/pii/S1053811920308272)\] \[[Click here for the PDF](https://s3-us-west-2.amazonaws.com/oww-files-public/d/da/Magnotti_Wang_Beauchamp_Neuroimage2020_RAVE.pdf)\] \[[Click here for the preprint](https://www.biorxiv.org/content/10.1101/2020.06.02.129676v1)\].

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). \[[Click here for the journal full text](https://www.eneuro.org/content/10/10/ENEURO.0328-23.2023)\] \[[Click here for the PDF](https://s3-us-west-2.amazonaws.com/oww-files-public/7/76/Wang_Magnotti_Zhang_Beauchamp_eNeuro_2023.pdf)\] \[[Click here for the preprint](https://www.biorxiv.org/content/10.1101/2023.08.04.552023v1)\].

If you like RAVE, we appreciate that you include the following "created-via-RAVE" logo to help promote us:

![RAVE Attribution Logo](images/attribution.png){width=30%}

## Installation

Please check our [full installation guide here.](posts/installation/installation.html)

## Publications

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

```{r, echo=FALSE}
# R code block to prettify the abstracts
res <- source("abstracts.R", echo = FALSE, print.eval = FALSE, local = TRUE)
res$value
```