eeg-decoding
CommunityDecode information from EEG with MVPA.
Education & Research#classification#scikit-learn#mvpa#mne#eeg decoding#temporal generalization#permutation testing
Authordengzhe-hou
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill turns EEG epochs into multivariate decoding results so you can answer whether (and when) information about conditions or classes is represented in the brain.
Core Features & Use Cases
- Sliding time-point decoding: train and test at each time point to produce time-resolved decoding curves (e.g., face vs object).
- Temporal generalization (train time × test time): reveal whether neural representations are transient, sustained, or reactivated over time.
- Searchlight decoding & CSP decoding: localize informational content across channels (searchlight) or decode oscillatory patterns (CSP) for frequency-band focused questions.
- Use Case: If your analysis plan claims that two conditions differ in discriminable neural patterns between 100–200 ms, use decoding to quantify peak decoding time, chance level, and statistical significance.
Quick Start
Use the eeg-decoding skill to decode a cognitive contrast by running decoding on your epoched data and producing decoding outputs for each claim in ANALYSIS_PLAN.md.
Dependency Matrix
Required Modules
numpyscikit-learnmne
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-decoding Download link: https://github.com/dengzhe-hou/auto-eeg-analysis/archive/main.zip#eeg-decoding Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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