Mne eeg preprocessing starter
Skill ma-compbio-lab/SkillFoundry/skills/neuroscience-and-neuroimaging/mne-eeg-preprocessing-starter
A framework for discovering, compiling, and validating reusable skills for scientific agents.
npx -y skills add ma-compbio-lab/SkillFoundry --skill mne-eeg-preprocessing-starterAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
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MNE EEG Preprocessing Starter
Use this skill to create a tiny synthetic EEG recording with MNE-Python, apply a simple band-pass filter, and summarize the preprocessing effect.
What it does
- Builds a deterministic two-channel
RawArraywith oscillatory signal plus low-frequency drift. - Applies a basic
1-30 Hzband-pass filter. - Returns compact JSON with sampling rate, channel names, and before/after dispersion summaries.
When to use it
- You need a runnable starter for
EEG / MEG preprocessing. - You want a verified local
MNE-Pythonexample before working on real electrophysiology recordings.
Example
slurm/envs/neuro/bin/python skills/neuroscience-and-neuroimaging/mne-eeg-preprocessing-starter/scripts/run_mne_eeg_preprocessing.py \
--out scratch/neuro/mne_preprocessing_summary.json
Verification
- Skill-local tests:
python3 -m unittest discover -s skills/neuroscience-and-neuroimaging/mne-eeg-preprocessing-starter/tests -p 'test_*.py' - Repository smoke:
python3 -m unittest tests.smoke.test_phase31_frontier_leaf_conversion_skills -v