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This paper presents the functional interdependences among electroencephalograph (EEG) signals collected from human subjects undergoing a controlled experiment over a period of 36 h of sleep deprivation. The EEG signals were recorded from 19 electrodes spread all over the scalp. The interdependence among the signals was measured using synchronization likelihood (SL), which measures the dynamical (both linear and nonlinear) interdependence between two or more nonstationary time series. A network structure was evolved based on these SL values. The EEG signal being nonstationary, instead of the frequency bands, the connectivity was evaluated at various intrinsic modes known as intrinsic mode functions (IMFs). These IMFs were generated using empirical mode decomposition. It was observed that the connectivity of the networks exhibits definite patterns at specific IMFs with increase in sleep deprivation at successive stages of the experiment. The results were validated using subjective assessment and audiovisual response tests.