Compute ERP evoked responses and component measures from EEG epochs.
npx skills add https://github.com/dengzhe-hou/auto-eeg-analysis --skill eeg-erp
Please help me install this Agent Skill. Skill: eeg-erp Source: https://github.com/dengzhe-hou/auto-eeg-analysis/tree/main/skills/eeg-erp Command: npx skills add https://github.com/dengzhe-hou/auto-eeg-analysis --skill eeg-erp
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.
.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.
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.
High-intent search queries and answers about installing and using this skill.
To compute ERP evoked responses and grand averages, this skill processes pre-cleaned EEG epochs to generate per-subject .fif evoked files, grand averages, and GFP aligned to a frozen ANALYSIS_PLAN.
Measuring ERP component amplitude and latency is done by applying ROI channels and time windows from an ANALYSIS_PLAN, supporting mean amplitude, peak, adaptive mean, or fractional area latency measures for downstream statistics.
Generating per-contrast difference waves involves averaging planned conditions from pre-cleaned epochs and exporting subject-level evoked difference waves, enabling direct downstream statistical comparisons across conditions.
Yes, calculating event-related potentials requires reading a frozen ANALYSIS_PLAN.md to resolve ROI channels and time windows, ensuring component measurements align with the pre-registered analysis plan.
Extracting ERP components requires pre-cleaned epoch-stage outputs, an ENVIRONMENT.json for backend validation, and a channel_mapping.json for ROI resolution to produce measurement tables and evoked .fif files.
Use grand averaging and GFP in ERP analysis when you need paper-ready summaries of condition-level evoked responses across subjects, producing documentation artifacts for downstream figure and stats stages.
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