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dc.contributor.authorAverick, John Wesley
dc.date.accessioned2014-03-04T21:00:42Z
dc.date.available2014-03-04T21:00:42Z
dc.date.issued2013-05
dc.identifier.otheraverick_john_w_201305_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/averick_john_w_201305_ms
dc.identifier.urihttp://hdl.handle.net/10724/28651
dc.description.abstractSchizophrenia is a severe mental disorder that affects millions of people and is subject to much research. Functional magnetic resonance imaging (fMRI) is a tool that provides, by observing changes in blood oxygenation, an indirect measure of brain activation. As schizophrenia is known to be partially hereditary, a study was conducted on patients, their relatives, and a control group in order to measure differences in brain activation patterns during the performance of an antisaccade task. In this master's thesis, the processes of bootstrapping and distribution construction are used in an attempt to assess the differences in brain activation among the three groups. The results indicate differences both between the control group and the relatives and between the controls and patients, but no definite evidence that the two differences coincide. Simulated data sets are used to confirm the efficacy of the methodology used. Speculation is given as to incongruities with previous analyses of the data.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectbootstrap
dc.subjectfmri
dc.subjectresampling
dc.subjectfisher's method
dc.subjectschizophrenia
dc.titleThe use of bootstrapping to measure image differences in fMRI data
dc.typeThesis
dc.description.degreeMS
dc.description.departmentStatistics
dc.description.majorStatistics
dc.description.advisorNicole Lazar
dc.description.committeeNicole Lazar
dc.description.committeeLynne Seymour
dc.description.committeeJaxk Reeves


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