Difference between revisions of "/tmp/bci/machine-learning"
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| − | Experiment with basic brain reverse engineering: out of the raw signal of the brain (EEG, fNIRS, ...), try to identify stable correlation with mental activity (reading text, listening to music, programming, sleeping) so as to find more deterministic ways to use the kits to control devices or generate artistic | + | Experiment with basic brain reverse engineering: out of the raw signal of the brain (EEG, fNIRS, ...), try to identify stable correlation with mental activity (reading text, listening to music, programming, sleeping) so as to find more deterministic ways to use the kits to control devices or generate artistic outputs (music, video, ...). |
= Tools = | = Tools = | ||
Revision as of 19:17, 13 January 2011
Goal
Experiment with basic brain reverse engineering: out of the raw signal of the brain (EEG, fNIRS, ...), try to identify stable correlation with mental activity (reading text, listening to music, programming, sleeping) so as to find more deterministic ways to use the kits to control devices or generate artistic outputs (music, video, ...).
Tools
scikit-learn
scikit-learn provides a rich tool box of machine learning algorithms implemented with python / numpy / cython. Approx 50% of the core developers are involved in applications of statistical learning for Neuro-Imaging research.
Some resources to get started:
- Official github source code repo
- Official website with documentation
- Tutorial on application of machine learning to neuroimaging by scikit-learn developers
People interested in this subproject
- Olivier Grisel (@ogrisel) - scikit-learn developer
- Add your name here
