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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 `RawArray` with oscillatory signal plus low-frequency drift.
- Applies a basic `1-30 Hz` band-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-Python` example before working on real electrophysiology recordings.
## Example
```bash
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`
