eeg-erp

What problem does it solve?

It automates the process of computing event-related potentials (ERPs) from cleaned EEG epochs, including grand averages, difference waves, and component-level amplitude/latency measurements aligned to a pre-registered analysis plan.

Core Features & Use Cases

• Condition- and contrast-aware evoked exports: averages per condition and generates per-contrast subject evoked difference waves for later statistics.
• Component measurement per ANALYSIS_PLAN: measures component amplitude and latency (mean amplitude by default, with support for peak, adaptive mean, or fractional area latency) using ROI channels and time windows from the frozen plan.
• Paper-oriented outputs: produces per-subject .fif evoked files, grand averages, GFP, measurement tables, and the documentation artifacts needed for downstream figure/stats/audit stages.

Use it when you need to respond to prompts like "compute ERPs", "average epochs", or "ERP components", or right after the epoch-stage finishes so the pipeline can proceed to stats and figures.

Quick Start

Run eeg-erp on your project by providing a frozen ANALYSIS_PLAN and an epoch-stage so the skill can compute evoked responses for the planned conditions and export the ERP outputs.