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dc.contributor.advisorJohn D. E. Gabrieli.en_US
dc.contributor.authorOsher, David Eugeneen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Brain and Cognitive Sciences.en_US
dc.date.accessioned2013-10-24T18:10:17Z
dc.date.available2013-10-24T18:10:17Z
dc.date.copyright2013en_US
dc.date.issued2013en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/81731
dc.descriptionThesis (Ph. D. in Neuroscience)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2013.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractConnectivity restricts and defines the information that a network can process. It is the substance of information processing that underlies the patterns of functional activity in the brain. By combining diffusion-weighted imaging or DWI, with fMRI, we are able to non-invasively measure connectivity and neural responses in the same individuals and directly relate these two measures to one another. In Chapter 2, I first establish the proof-of-principle that anatomical connectivity alone can predict neural responses in cortex, specifically of face-selectivity in the fusiform gyrus. I then extend this novel approach to the rest of the brain and test whether connectivity can accurately predict neural responses to various visual categories in Chapter 3. Finally, in Chapter 4, I compare and contrast the resulting models, which are essentially networks of connectivity that are functionally-relevant to each visual category, and demonstrate the type of knowledge that can be uncovered by directly integrating structure and function.en_US
dc.description.statementofresponsibilityby David Eugene Osher.en_US
dc.format.extent129 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectBrain and Cognitive Sciences.en_US
dc.titleFunction follows form : how connectivity patterns govern neural responsesen_US
dc.typeThesisen_US
dc.description.degreePh.D.in Neuroscienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciences
dc.identifier.oclc858804034en_US


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