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Getting Started

This guide will help you get Rica up and running with your tedana output data.

Installation Options

Rica offers four ways to use the application, from simplest to most flexible:

The easiest way to use Rica - no installation required.

  1. Visit rica-fmri.netlify.app
  2. Click Select Folder
  3. Navigate to your tedana output directory
  4. Click Upload to load your data

Best for most users

The online version is always up-to-date and requires no setup.

Option 2: Local Server

Run Rica locally with automatic data loading - ideal for working with large datasets or slow connections.

  1. Download from the latest release:

    • index.html
    • rica_server.py

  2. Copy both files to your tedana output directory: 

    cp index.html rica_server.py /path/to/tedana/output/

  3. Start the server: 

    cd /path/to/tedana/output/
python rica_server.py

  4. Rica opens automatically in your browser at http://localhost:8000

Server Options

  • --port 9000 - Use a different port
  • --no-open - Don't open browser automatically

Option 3: Development Mode

For contributors or those who want the latest features.

git clone https://github.com/ME-ICA/rica.git
cd rica
npm install
npm start

Opens at http://localhost:3000. You'll need to manually select a folder.

Option 4: Build from Source

Create a standalone HTML file for offline use.

git clone https://github.com/ME-ICA/rica.git
cd rica
npm install
npm run build
npx gulp

The built files are in the build/ directory.

Required Files

Rica reads tedana output files directly from your filesystem. Here's what Rica looks for:

Essential Files

File Description Required
*_metrics.tsv Component metrics (kappa, rho, variance, etc.) Yes
*_mixing.tsv ICA mixing matrix (component time series) Yes
*stat-z_components.nii.gz 4D component statistical maps Yes
report.txt Tedana processing report Recommended

Optional Enhancement Files

These files unlock additional features:

File Feature Enabled
*_desc-ICACrossComponent_metrics.json Elbow threshold lines on scatter plots
figures/comp_*.png Static component figures (fallback for brain viewer)
*.svg Carpet plots in Carpets tab
decision_tree.json + status_table.tsv Decision Tree tab
*confound_correlations*.svg External regressor heatmap (tedana 24.1+)

Quality Control Files

File Description
T2starmap.nii* T2* brain map
S0map.nii* S0 brain map
rmse_statmap.nii* RMSE statistical map

Manual Classification

File Description
manual_classification.tsv Previously saved classifications (auto-loaded)

Manual Classification Warning

If Rica detects a manual_classification.tsv file, it will show a warning popup. This ensures you're aware that manual classifications have been applied to the data.

First Steps

Once Rica loads your data:

  1. Info Tab: Review the tedana processing report
  2. ICA Tab: Start reviewing components
  3. Use keyboard shortcuts: A (accept), R (reject), ←/→ (navigate)
  4. Save your work: Click the save button to export classifications

Continue to the Interface Overview to learn about each tab in detail.