mne-python

Why we included this project

For labs that record brain activity, MNE-Python is the go-to library for MEG, EEG, sEEG, ECoG, and fNIRS data. It covers the full pipeline, from loading and cleaning raw signals to artifact rejection, source estimation, and connectivity analysis, so you don't have to stitch together several incompatible packages. Its built-in machine-learning routines, including time generalization and receptive field estimation, let you run decoding analyses directly on the neurophysiological data. Because it's pure Python and integrates with NumPy, SciPy, and matplotlib, it fits naturally into existing scientific workflows and Jupyter notebooks. If you work with human brain recordings, this is a mature, well-documented foundation worth building on.