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dc.contributor.advisorÇukur, Tolga
dc.contributor.authorYılmaz, Özgür
dc.date.accessioned2019-09-24T10:37:34Z
dc.date.available2019-09-24T10:37:34Z
dc.date.copyright2019-09
dc.date.issued2019-09
dc.date.submitted2019-09-23
dc.identifier.urihttp://hdl.handle.net/11693/52492
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (Ph.D.): Bilkent University, Department of Electrical and Electronics Engineering, İhsan Doğramacı Bilkent University, 2019.en_US
dc.descriptionIncludes bibliographical references (leaves 91-106).en_US
dc.description.abstractHumans can effortlessly identify target auditory objects during natural listening and shift their focus between different targets. Unique allocation of brain resources would be inefficient for semantic search task. Here, we hypothesize that auditory attention shifts tuning of cortical voxels toward target category and that attention expands the representation of target words while compressing the representation of behaviorally irrelevant words across cortex. To test, we designed an fMRI experiment with a semantic search task. Subjects listened to natural stories twice while searching for words that are semantically related to either `humans' or `places'. Fit voxelwise models for two attention tasks were compared to identify semantic tuning shifts in single voxels. Results indicate that attention shifts semantic tuning of single voxels broadly across cortex and attention warps language representation in favor of target words across cortex. We also introduced a novel feature regularization in voxelwise modeling for a naturalistic movie experiment. Feature regularization simply enforces similar model weights over semantically related stimulus features. We tested the proposed method on an fMRI experiment with naturalistic movies. Results suggest that the proposed method offer improved sensitivity in modeling of single voxels. Moreover, we proposed a novel method to improve the sensitivity of phase-sensitive fatwater separation in balanced steady-state free precession (bSSFP) acquisitions. In bSSFP applications using phased-array coils, reconstructed images suffer a lot from spatial sensitivity variations within individual coils. To improve, we first performed region-growing phase correction in individual coil images, then used a linear combination of phase-corrected images. Tests on SSFP angiograms of the thigh, lower leg, and foot suggest that the proposed method enhances fat{water separation in phased-array acquisitions with improved phase estimates.en_US
dc.description.statementofresponsibilityby Özgür Yılmazen_US
dc.format.extentxxxviii, 137 leaves : illustrations (some color), charts (some color) ; 30 cm.en_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectComputational neuroscienceen_US
dc.subjectfMRIen_US
dc.subjectVoxelwise modelingen_US
dc.subjectTuning shiften_US
dc.subjectSSFPen_US
dc.subjectFat-water separationen_US
dc.titleEffects of auditory attention on language representation across the human brainen_US
dc.title.alternativeİşitsel dikkatin dilin beyin üzerindeki gösterimine etkilerien_US
dc.typeThesisen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreePh.D.en_US
dc.identifier.itemidB152825
dc.embargo.release2020-03-20


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