Inter-regional connectivity in the human brain during visual search
| buir.advisor | Çukur, Tolga | |
| dc.contributor.author | Dar, Salman UI Hassan | |
| dc.date.accessioned | 2016-08-31T05:58:36Z | |
| dc.date.available | 2016-08-31T05:58:36Z | |
| dc.date.copyright | 2016-08 | |
| dc.date.issued | 2016-08 | |
| dc.date.submitted | 2016-08-12 | |
| dc.description | Cataloged from PDF version of article. | en_US |
| dc.description | Thesis (M.S.): Bilkent University, Department of Electrical and Electronics Engineering, İhsan Doğramacı Bilkent University, 2016. | en_US |
| dc.description | Includes bibliographical references (leaves 45-49). | en_US |
| dc.description.abstract | Separate groups of regions in the human brain are thought to be functionally specialized for representing specific categories of visual objects, and for controlling and deployments of visual attention. It is commonly assumed that the information ow between these regions is altered during visual search. However, little is known about the magnitude and extent of these changes during natural visual search. Here, we assess the changes in functional connectivity between the attention-control network and the category-selective regions during category-based visual search in natural movies. Brain activity was recorded using functional magnetic resonance imaging (fMRI) while subjects viewed natural movies. To investigate the changes in connectivity strength between pairs of brain regions, we employed coherence analysis. Coherence is a non-directional measure of association, which identifies correlation in frequency domain. To infer the in uence of attention-control areas on category-selective areas, Granger causality analysis was carried out. Granger causality uses the idea of temporal precedence that cause precedes the effect. Furthermore, to examine whether attention changes inter-regional connectivity after accounting for stimulus-driven brain activity, two separate encoding models were used to capture brain responses elicited by low-level structural and high-level category features in natural movies via L2-regularized linear regression. Response predictions of the structural and category models were removed from the recorded blood-oxygen-level dependent (BOLD) responses to obtain the residual responses. The connectivity analyses were repeated on the residuals to determine if the attentional changes in connectivity persist even after projecting out the stimulus-driven brain activity. The results indicate that performing visual search for a specific object category enhances the in uence of high-level attention-control network on category-selective areas in ventral temporal cortex. Furthermore, these connectivity patterns persist even after projecting out the stimulus-driven brain activity from the recorded BOLD responses. | en_US |
| dc.description.provenance | Submitted by Betül Özen (ozen@bilkent.edu.tr) on 2016-08-31T05:58:36Z No. of bitstreams: 1 10121705.pdf: 54742816 bytes, checksum: cd85f2c808d043fd10983e2e6598b101 (MD5) | en |
| dc.description.provenance | Made available in DSpace on 2016-08-31T05:58:36Z (GMT). No. of bitstreams: 1 10121705.pdf: 54742816 bytes, checksum: cd85f2c808d043fd10983e2e6598b101 (MD5) Previous issue date: 2016-08 | en |
| dc.description.statementofresponsibility | by Salman Ul Hassan Dar. | en_US |
| dc.embargo.release | 2018-08-11 | |
| dc.format.extent | xiv, 60 leaves : illustrations, charts (some color) | en_US |
| dc.identifier.itemid | B119853 | |
| dc.identifier.uri | http://hdl.handle.net/11693/32186 | |
| dc.language.iso | English | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Coherence | en_US |
| dc.subject | Granger Causality | en_US |
| dc.subject | Brain Connectivity | en_US |
| dc.subject | Model Fitting | en_US |
| dc.title | Inter-regional connectivity in the human brain during visual search | en_US |
| dc.title.alternative | Görsel dikkat sırasında insan beynindeki bölgeler-arası bağlantılılık | en_US |
| dc.type | Thesis | en_US |
| thesis.degree.discipline | Electrical and Electronic Engineering | |
| thesis.degree.grantor | Bilkent University | |
| thesis.degree.level | Master's | |
| thesis.degree.name | MS (Master of Science) |