Package for modelling electrophysiological responses to stimuli
Project description
sPyEEG
Citation
Pierre Hieu Guilleminot, Mikolaj Kegler, & Enrico Varano. (2021). sPyEEG (0.0.1). Zenodo. https://doi.org/10.5281/zenodo.7006933
Version: 0.2.2
Package for modelling s/M/EEG responses to stimuli. In other words, for mapping sensory or cognitive features, through python (sPyeech) to EEG (sPyEEG)... and the other way around!
Not mind-reading for espionage purposes ;). (Definitely not that)
Setup
Requirements
Package builds on top on MNE and relies on a similar set of dependencies and 3rd party packages listed in requirements.txt. Normally, installing via pip will take care of dependencies but in case, you can check that there won't be problems.
Installation
For a standard installation (but this will require to be installed if you need to install another version of the library):
pip install spyeeg
Tested on:
- macOS Big Sur v11.1
- Ubuntu 18.04.5 LTS
- Windows 10 22H2
Modules (sketch)
- models - for all your modelling needs
- TRF: Temporal Response Function a.k.a Ridge regression a.k.a. fancy linear regression, optimized for speed
- iRRR: integrative reduced rank regression a.k.a fancier linear regression
- _methods: useful methods used by several model classes
- tbc
Contributors:
- Pierre Guilleminot (pierre.hieu.guilleminot@gmail.com)
- Mikolaj Kegler (mak616@ic.ac.uk)
- Michael Thornton (m.thornton20@imperial.ac.uk)
Last updated: 15th March 2025
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