"Boosting Neuroimaging Analysis and Results Digestibility 🧠"
summary
Uses MNE Python to load varied EEG formats, run ICA denoising, and export concise visuals and stats; demos include data from a consumer Muse headband (8 electrodes) and clinical 1‑hour vs 48‑hour recordings. Heat maps and time‑region plots highlight a 1‑second seizure‑like peak and localize activity (e.g., right temporal), making artifact vs real events easier to decide. Workflow exports cleaned signals and summaries to Dropbox/iCloud for patient reports.
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chapters (6)
- 0:00EEG and brain imaging intro
- 3:10EEG sensors and 10-20 system
- 8:10EEG in Python tech
- 15:36Processing EEG with Python
- 22:19Digestible EEG results
- 25:42Open resources and future
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