EEG and MEG measure electrophysiological activity directly, at millisecond resolution — the opposite trade-off to fMRI. Six CNS projects use them, making electrophysiology the second-largest methodological cluster in the program after deep learning.
Data¶
PREVENT-AD includes MEG/EEG alongside its imaging and biomarker measures
DANDI archives open neurophysiology data
Processing¶
Brainstorm — open-source MEG/EEG analysis environment, and the platform the AD Toolbox is being built on
MNE-Python — the scripted alternative, better suited to batching over a cohort and version-controlling your choices
BIDS has EEG and MEG extensions, so the same organizational conventions apply
Unlike the MRI path, there is no fMRIPrep equivalent here — no agreed pipeline turns raw EEG into analysis-ready data, so more of the decisions are yours to make and record.
CNS Projects¶
Diellor Basha — electrophysiology of neurological disorders; building an AD Toolbox within Brainstorm
Phillip Johnston — detecting invisible brain injury from repeated head impacts using generative neurophysiological modelling
Selena Singh — EEG signatures of neural attractor states in major depression
Nooshin Bahador — chirp localization in EEG spectrograms
Tom George — EEG as one input modality to a neuro-foundation model
Emmanuelle Renauld — EEG alongside diffusion MRI and fMRI
Related topics¶
Seizure Disorders, Major Depressive Disorder, Alzheimer’s Disease