Functional connectivity during rest and task : a study based on graph theoretical metrics
| 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.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.format.pages | xiv, 62 leaves ; | |
| dc.identifier.other | BM 2015 N47 | |
| dc.identifier.uri | https://digitalarchive.library.bogazici.edu.tr/handle/123456789/18867 | |
| 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 |
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