Rica Documentation
Rica (Review of ICA Components Application) is an interactive web-based visualization tool for reviewing and classifying ICA components generated by tedana.
What is Rica?
Rica provides an intuitive interface to visualize multi-echo fMRI denoising results from tedana, enabling researchers to:
- Review ICA component metrics and visualizations
- Classify components as accepted, rejected, or ignored
- Export manual classifications for use in tedana pipelines
- Understand the decision tree logic used for automatic classification
Key Features
| Feature | Description |
|---|---|
| Interactive Brain Viewer | Explore component spatial maps with Niivue |
| Component Metrics | Kappa, Rho, variance explained, and more |
| Time Series & FFT | Temporal dynamics and frequency content |
| Decision Tree | Visualize tedana's classification logic |
| Quality Control | T2*, S0, and RMSE diagnostic maps |
| Dark/Light Themes | Comfortable viewing in any environment |
The ICA tab showing component visualization with scatter plots, brain viewer, and time series
Quick Start
The fastest way to use Rica:
- Visit rica-fmri.netlify.app
- Click "Select Folder" and choose your tedana output directory
- Start reviewing components!
For detailed instructions, see the Getting Started guide.
Video Tutorial
Watch a walkthrough of Rica's features:
Requirements
Rica works with tedana output files. At minimum, you need:
*_metrics.tsv- Component metrics table*_mixing.tsv- ICA mixing matrix*stat-z_components.nii.gz- Component statistical maps
See Getting Started for the complete list of supported files.
Citation
If you use Rica in your research, please cite:
@software{rica,
author = {Urunuela, Eneko},
title = {Rica: Review of ICA Components Application},
url = {https://github.com/ME-ICA/rica},
version = {2.1.1}
}
Contributing
Rica is open source! Contributions are welcome on GitHub.