Satori: Advanced fNIRS Analysis Made Simple

Satori is a powerful yet intuitive software solution for fNIRS (functional Near-Infrared Spectroscopy) analysis. Designed with both simplicity and capability in mind, it puts advanced analysis tools at your fingertips - no programming experience required.

Satori guides you through the complete fNIRS workflow — from raw-data import and preprocessing to visualization, statistical modeling, and group-level analysis. Its interface offers clear, interactive views (raw vs. processed signals, channel-wise plots, and 2D/3D montages) together with reproducible workflows for quickly sharing, iterating, and refining analyses.

Supported inputs include SNIRF, NIRS, HDR, and common vendor export formats. Satori provides both automated and manual quality-control tools, robust artifact correction, and a GLM-based analysis pipeline. Built with high-performance C++, it also offers seamless Python integration for custom analysis extensions and allows processed data export for further analysis in other tools.

Explore the comprehensive documentation and step-by-step tutorials — including guided workflows, example datasets, API snippets, video walkthroughs, and troubleshooting tips — tailored for researchers, and data scientists working with fNIRS. These resources focus on practical workflows, reproducible examples, and extending analyses with Python so you can get productive immediately.

Satori streamlines the entire fNIRS workflow into an intuitive, repeatable process: you begin by importing and organizing recordings (SNIRF, NIRS, HDR, or vendor exports), then visually inspect signals and run automated quality checks to flag bad channels or segments. Next, preprocessing tools - filtering, motion correction, and physiological-noise regression - clean the data while preserving transparency through interactive QC reports. From there you build and fit statistical models (GLM or block/event analyses), explore results with 2D/3D montages and channel plots, and iteratively refine regressors and contrasts. Finally, processed data and visual reports can be exported for publication or pooled across subjects for group-level statistics; every step can be saved as a reproducible pipeline or extended via Python for custom analyses.

Inspect indiviuadual time courses and event-related averages (ERAs) with Satori's dynamic visualization tools. Easily toggle between raw and processed signals, zoom into specific epochs, and compare conditions across channels. The interactive plots allow for detailed examination of hemodynamic responses, facilitating deeper insights into your fNIRS data.