Rica

Rica (Reports for ICA) is an interactive visualization tool for reviewing and classifying ICA components from tedana multi-echo fMRI analysis.

View Documentation | Launch Rica Online

Pronunciation: [ˈrika]. Hear it here.

Features

ICA Component Analysis

• Interactive scatter plots - Kappa vs Rho, Kappa/Rho Rank plots with elbow threshold lines, zoom/pan
• Pie chart - Component variance distribution, click to select
• 3D brain viewer - Interactive stat-z maps using Niivue with mosaic view (7 slices per orientation)
• Time series & FFT - Component time courses and power spectra
• Component table - Full metrics with sorting and selection sync
• External regressor heatmap - Interactive correlation visualization (requires tedana 24.1+)

Quality Control (QC) Tab

• Brain maps - T2*, S0, and RMSE maps with Niivue mosaic viewer
• Histograms - Distribution plots for QC metrics
• Carpet plots - Time series visualization in dedicated Carpets tab

User Experience

• Classification toggle - Accept/reject components with A/R keyboard shortcuts
• Arrow navigation - Previous/next component with wrap-around
• Light/dark theme - Toggle with the sun/moon button
• Export - Save modified classifications as TSV

How to Use

For comprehensive guides, see the Documentation.

For a video tutorial, see this walkthrough.

Keyboard Shortcuts

Key	Action
A	Accept component
R	Reject component
←	Previous component
→	Next component

Using Rica

Option 1: Online (Easiest)

Visit https://rica-fmri.netlify.app and select your tedana output folder.

Option 2: Local Server (Recommended for Local Use)

Run Rica directly from your tedana output folder with automatic data loading:

1. Download the latest release files:

   • index.html (self-contained single-file app with embedded logo)
   • rica_server.py

2. Copy these files to your tedana output folder:

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

3. Run the server:

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

4. Your browser opens automatically and data loads instantly!

Note: The "New" button is hidden in local server mode since data is loaded automatically.

Option 3: Development Server

For development or if you want to load different folders:

# Clone and install
git clone https://github.com/ME-ICA/rica.git
cd rica
npm install

# Start development server
npm start

Then open http://localhost:3000 and select your tedana output folder.

Option 4: Build from Source

Build a single-file HTML distribution:

# Install dependencies
npm install

# Build with inlined assets
npm run build
npx gulp

# Output files in build/
# - index.html (self-contained single-file app)
# - rica_server.py (local server)

Required Files

Rica expects these files from tedana output:

File Pattern	Description
*_metrics.tsv	Component metrics table (required)
*_mixing.tsv	ICA mixing matrix (time series)
*stat-z_components.nii.gz	4D component stat maps
*_desc-ICACrossComponent_metrics.json	Elbow thresholds for reference lines
figures/comp_*.png	Component figures
*.svg	Carpet plots and diagnostic figures
report.txt	Tedana report
T2starmap.nii*, S0map.nii*, rmse_statmap.nii*	QC brain maps

Versioning

Rica version is displayed in the About popup and managed centrally:

• Version is defined in package.json
• UI automatically displays the current version
• GitHub releases should be tagged as v<version> (e.g., v2.0.0)

To bump the version:

npm version patch  # 2.0.0 -> 2.0.1
npm version minor  # 2.0.0 -> 2.1.0
npm version major  # 2.0.0 -> 3.0.0

Contributing

Questions, suggestions, or contributions? Open an issue on GitHub!