Graph Theoretical Analysis of Resting State Functional Connectivity as a Biomarker for Working Memory Performance

Ne Zaman:: 
Wednesday, 3 April, 2019 - 16:30

Yeditepe University, Cognitive Science Master's Program is happy to announce its next lecture:

Graph Theoretical Analysis of Resting State Functional Connectivity as a Biomarker for Working Memory Performance

Hüden Neşe 
Wednesday April 3rd, 16:30
A-442 Engineering Building

Graph theory is a powerful tool to investigate the brain as a complex system. Several studies have worked on the relation between individual difference in cognitive ability and the network organization of the brain. However this relation is still poorly understood.

In this study, we investigated the relation between resting state functional connectivity and performance in a working memory task. Spontaneous EEG of 15 subjects were recorded for 2 minutes with closed eyes using 32-channel system. Then participants performed a verbal n-back task. The correlation coefficient between channel pairs during the rest period was used as a measure of functional connectivity. Connectivity matrix was thresholded according the predefined connection density. Global efficiency, local efficiency and modularity were computed from the processed connectivity matrix, normalized and statistically analyzed.

We showed that there is a relation between functional integration and cognitive performance. Global efficiency is significantly correlated with performance especially in beta (r=0.52, p=0.045) and gamma (r=0.58, p=0.023) bands. Besides, there is also significant correlation between modularity and performance in beta band (r=0.55, p=0.33) . Our results are mainly compatible with previously published studies where they reported that global efficiency and modularity are the predictors of cognitive performance regardless of the cognitive task domain. However, there are conflicting results on the local efficiency depending on the cognitive task.

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