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.
