Categories and functional units: An infinite hierarchical model for brain activations
Name
Golland_Categories and functional.pdf
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1.21 MB
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Adobe PDF
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6d188485b204bf5c1e0f6ce4fcd866d0
Author(s)
Lashkari, Danial
Sridharan, Ramesh
Golland, Polina
Date Issued
January 2010
Journal
Proceedings of the 24th Annual Conference on Neural Information Processing Systems (NIPS 2010)
Publisher
Neural Information Processing Systems Foundation (NIPS)
Citation
D. Lashkari, R. Sridharan, and P. Golland. "Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations." Proceedings of the 24th Annual Conference on Neural Information Processing Systems, 1252-1260, 2010.
Version
Author's final manuscript
Abstract
We present a model that describes the structure in the responses of different brain areas to a set of stimuli in terms of stimulus categories (clusters of stimuli) and functional units (clusters of voxels). We assume that voxels within a unit respond similarly to all stimuli from the same category, and design a nonparametric hierarchical model to capture inter-subject variability among the units. The model explicitly encodes the relationship between brain activations and fMRI time courses. A variational inference algorithm derived based on the model learns categories, units, and a set of unit-category activation probabilities from data. When applied to data from an fMRI study of object recognition, the method finds meaningful and consistent clusterings of stimuli into categories and voxels into units.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
http://nips.cc/Conferences/2010/Program/accepted-papers.php
