eeg-stats
CommunityRun rigorous claim-driven EEG stats
Education & Research#multiple comparisons#mne-python#eeg statistics#cluster permutation#ANALYSIS_PLAN#roi channels#cohens d
Authordengzhe-hou
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill turns pre-defined EEG claims into rigorous, reproducible group-level statistics so you can test hypotheses without ad-hoc choices.
Core Features & Use Cases
- Claim-driven cluster permutation testing: Runs spatio-temporal cluster permutation tests (directional or two-sided) for ERP/TFR/connectivity contrasts specified in ANALYSIS_PLAN.
- ROI + channel-mapping guardrails: Enforces planned time windows and ROI channels, using channel_mapping.json to resolve 10-20 names to numbered channels and stopping when mappings are missing.
- COBIDAS-ready statistical outputs: Writes per-claim JSON verdicts plus reproducibility artifacts (arrays and backend resolution) and appends a structured FINDINGS.md entry.
- Multiple-comparisons controls: Applies the multiple-comparisons strategy defined in ANALYSIS_PLAN (e.g., Bonferroni or hierarchical).
Quick Start
Use the eeg-stats Skill to compute cluster permutation group statistics for your frozen ANALYSIS_PLAN by running it on a prepared project directory (with stats prerequisites generated by earlier ERP/TFR stages).
Dependency Matrix
Required Modules
mnescipynumpypython
Components
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: eeg-stats Download link: https://github.com/dengzhe-hou/auto-eeg-analysis/archive/main.zip#eeg-stats Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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