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SS 2007
Spotlight
Computational models of brain connectivity, coupled with machine learning algorithms, make it possible to infer neuronal disease mechanisms from
non-invasive functional magnetic resonance imaging (fMRI) data in humans.
This illustration shows how dynamic systems models can be used for reducing
complex (high-dimensional) brain activity data to a simple (low-dimensional)
and mechanistically interpretable representation (Brodersen et al., PLoS
Comput. Biol. 2011). Please also see the summary on ETH Life.
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251-0502-00L 252-0206-00L |
Lecture | Visual Computing | Details |
| 251-0526-00L | Lecture | Advanced Topics in Machine Learning | Details |
| 251-0832-00L | Lecture | Informatik I (D-MAVT) | Details |
| 251-0838-00L | Lecture | Informatik II (D-MAVT) | Details |
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251-0540-00L 252-5251-00L |
Seminar | Computational Science | Details |
| 251-0566-00L | Seminar |
Machine Learning in Visual Computing |
Details |
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