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From fMRI to Behavior and Back: The Decoding of large fMRI Datasets
Speaker: Francois Meyer, University of Colorado [November 17, 4:10 p.m. CUE 518]
Functional Magnetic Resonance Imaging can be used to infer subjective experience and brain states of subjects immersed in "natural environments". These environments are rich with uncontrolled stimuli and resemble real life experiences.
We describe a new method that yields a low dimensional embedding of the fMRI data. The embedding provides a representation of the cognitive activity. We learn a set of time series that are implicit functions of the cognitive activity, and we predict the values of these times series in the future from the knowledge of the fMRI data only.
In addition, our exploratory approach is able to detect independently visual areas (V1/V2, V5/MT), auditory areas, and language areas. Our method can be used to analyze fMRI collected during "natural stimuli".
We present experiments conducted with the datasets of the 2007 Pittsburgh Brain Activity Interpretation Competition.
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