A generative model for activations in functional MRI
Generative model for activations in functional magnetic resonance imaging
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
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Detection of brain activity and selectivity using functional magnetic resonance imaging (fMRI) provides unique insight into the underlying functional properties of the brain. We propose a generative model that jointly explains neural activation and temporal activity in an fMRI experiment. We derive an algorithm for inferring activation patterns and estimating the temporal response from fMRI data, and present results on synthetic and actual fMRI data, showing that the model performs well in both settings, and provides insight into patterns of selectivity.
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 87-91).
DepartmentMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.