eeg-connectivity

What problem does it solve?

It turns cleaned EEG epochs into defensible functional connectivity and optional network metrics, reducing the risk of misleading sensor-space synchronization claims.

Core Features & Use Cases

• Connectivity computation with validated metrics: Computes wPLI, PLV, coherence, imaginary coherence, Granger causality, or PAC, with explicit warnings about sensor-space volume conduction and metric validity checks.
• Flexible sensor vs source-space support: Runs on sensor-space epochs by default, and supports source-space connectivity if source-stage exists (with leakage/orthogonalization guardrails).
• Graph-theoretic summaries and reporting outputs: Optionally thresholds connectivity matrices and outputs graph metrics plus group aggregation artifacts suitable for downstream stats and figure generation.

Quick Start

Run the connectivity stage for your study by asking for a specific metric and space, for example: "/eeg-connectivity projects/my-study — metric: wpli — space: sensor".