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Functional connectivity during rest and task : a study based on graph theoretical metrics

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dc.contributor Graduate Program in Biomedical Engineering.
dc.contributor.advisor Gülsoy, Murat,
dc.contributor.advisor Akın, Ata.
dc.contributor.author Neşe, Hüden.
dc.date.accessioned 2023-03-16T13:12:53Z
dc.date.available 2023-03-16T13:12:53Z
dc.date.issued 2015.
dc.identifier.other BM 2015 N47
dc.identifier.uri http://digitalarchive.boun.edu.tr/handle/123456789/18867
dc.description.abstract In this study, task-related network organization were examined, and the association between network integration at rest and cognitive performance was investigated using n-back task. Global e ciency, local e ciency and modularity were computed at rest and during n-back task. Task-related metrics were compared with resting state metrics to understand the neural mechanism underlying working memory. Correlations between resting state metrics and performance in the n-back task were computed to investigate the optimal topology. The results revealed that performing n-back task required a reorganization of resting state network. Task-related topology showed higher global e ciency and modularity , and lower local e ciency compared to rest. Moreover, it was reported that the resting state topology was an indicator of cognitive performance. Performance in n-back task was positively correlated with global e ciency, local e ciency and modularity of resting state network.|Keywords : Graph Theory, Resting State, Working Memory, Network Integration, Cognitive Performance.
dc.format.extent 30 cm.
dc.publisher Thesis (M.S.)-Bogazici University. Institute of Biomedical Engineering, 2015.
dc.subject.lcsh Graph theory.
dc.subject.lcsh Working mothers.
dc.title Functional connectivity during rest and task : a study based on graph theoretical metrics
dc.format.pages xiv, 62 leaves ;


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