Human electrophysiology


MNE is a software package for processing electrophysiological signals primarily from magnetoencephalographic (MEG) and electroencephalographic (EEG) recordings, and more recently sEEG, ECoG and fNIRS. It provides a comprehensive solution for data preprocessing, forward modeling (with boundary element models), distributed source imaging, time–frequency analysis, non-parametric multivariate statistics, multivariate pattern analysis, and connectivity estimation.


SpikeInterface is a unified Python framework for spike sorting. With its high-level API, it is designed to be accessible and easy to use, allowing users to build full analysis pipelines for spike sorting (reading-writing (IO) / preprocessing / spike sorting / postprocessing / validation / curation / comparison / visualization) with a few lines of code.

Heuristic Spike Sorting Tuner (HSST), a framework to determine optimal parameter selection for a generic spike sorting algorithm

Extracellular microelectrodes frequently record neural activity from more than one neuron in the vicinity of the electrode. The process of labeling each recorded spike waveform with the identity of its source neuron is called spike sorting and is often approached from an abstracted statistical perspective.