Abstract:
Recent studies suggest that, human brain has a small-world behavior which is reflected by locally and globally efficient processing. To investigate this behavior a short term/working memory experiment was designed which had manipulation and retention conditions. Our goal was to be able to explore the differences between the organizations of the brain during the execution of these tasks within a graph theoretical context. The retention condition required the subject only to remember a visually applied stimulus whereas the manipulation condition to visually manipulate the stimulus before keeping it in mind. Brain activity information was recorded through the electroencephalography (EEG) device. After preprocessing, the collected EEG data was decomposed into classical frequency bands and phase locking values (PLV) between each pair of electrodes were computed with the help of the Hilbert Transform. After applying thresold to PLV matrices to build binary unweighted networks, the graph theoretical analysis was applied to determine and compare the main dynamics of functional coupling during manipulation and retention. This analysis was carried out in a time dependent manner to better monitor the variations of these dynamics. It was found that the brain exhibited a highly efficient behavior in the local and global sense both during manipulation and retention; and thus the brain had a small-world characteristic during the execution of these tasks. The statistical analysis revealed significant differences between the efficiency values of retention and manipulation. The analysis of node and edge centrality values of different frequency bands showed prominent effects in the upper alpha gamma bands. The finding of this thesis study supports the feasibility of the graph theoretical analysis for analyzing complex brain networks.|Keywords : Synchronization, Betweenness Centrality, EEG, Working Memory, Global Efficiency, Local Efficiency, Small-World, Graph Theory
