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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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