ERP Data Analysis
CommunityERP analysis guidance from preprocessing to stats
Education & Research#statistics#preprocessing#erp#research-design#eeg#erp-analysis#component-identification
AuthorHaoxuanLiTHUAI
Version1.0.0
Installs0
System Documentation
What problem does it solve?
ERP data analysis is complex and benefits from a domain-validated pipeline detailing preprocessing, artifact handling, epoching, ERP component identification, and robust statistical strategies.
Core Features & Use Cases
- Preprocessing guidance: default filtering, re-referencing, and artifact rejection recommendations aligned with Luck (2014) and Keil et al. (2014).
- Component-focused analysis: guidelines for P1/N1/N170, N400, P600, ERN/Ne, and other ERP components including ROI and time-window suggestions.
- Statistical frameworks: instructions for traditional ANOVA, mass-univariate, and regression-based ERP approaches, with robust reporting standards.
- Use case example: designing an ERP study with a 64-channel setup, or reanalyzing an existing dataset to extract N400 effects.
Quick Start
Load your EEG dataset and invoke the ERP analysis workflow to obtain preprocessing, component identification, and statistical analysis guidance.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 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: ERP Data Analysis Download link: https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/archive/main.zip#erp-data-analysis Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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