Resting-state functional Magnetic Resonance Imaging (rs-fMRI) is a non-invasive brain imaging technique that measures brain activity non-invasively. Functional connectivity (FC) quantifies how Blood-Oxygen-Level-Dependent (BOLD) signal of remote brain regions correlates with each other temporally. Using variety of methodologies such as Independent Component Analysis (ICA) or sparse dictionary learning, Resting-State Networks (RSNs) are consistently found in human brain connectome. Functional hubs denote the brain regions that exhibit connections denser than others, whereas connector hubs especially participate in inter-network communication. My Master thesis is based on a previously published methodology called Sparsity-based analysis of reliable k-hubness (SPARK), which estimates the functional hubs by counting the number of RSNs connected to each brain voxels. By acquiring simultaneous electroencephalogram (EEG)-fMRI, functional connectivity (FC) during sleep can also be investigated. In addition, functional connectivity has been commonly applied to find potential biomarkers for neurological disease, such as epilepsy. Therefore, in the first study of this thesis, we investigated functional segregation during a recovery nap after total sleep deprivation and its association with cognitive performance. We applied an algorithm called Hierarchical Segregation Index (HSI) based on the hubness estimated by SPARK. As a result, we found significant correlation between functional segregation during sleep and working memory performance after sleep. In the second study of this thesis, we investigated the different patterns of functional hub reorganization in temporal lobe epilepsy (TLE) and frontal lobe epilepsy (FLE). By applying similar methods used in the first study, we found significant and exclusive functional hub alteration both in TLE and FLE. To conclude, in sleep, functional segregation during a whole night sleep and its association between cognitive performance can be further investigated. In TLE and FLE, further research of the hub alterations in subcortical structures will be of interest, and might serve as potential biomarkers for post-surgical outcomes
