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The cognitive states have broadly been divided into waking, rapid eyemovement sleep and non-REMS. Although the mechanism of state transition isunknown, it has been proposed that functional activation/deactivation amongdifferent brain regions leads to such transition. As analysis ofelectroencephalogram allows us exploring properties and association among brainregions, we exploited it to address our query. We have recorded the frontal andoccipital cortical EEG from surgically prepared chronic freely moving, normallybehaving rats and classified their vigilance states and vigilancestate-transitions. The complexity analysis carried out by computingmultifractal spectrum width categorized VST as highly non-linear and complexthan their participating vigilance states. The EEG signals were decomposed intofrequency ranges as that of classical human Delta, Theta, Alpha, Beta and Gammaoscillations. The dynamic network attributes of these oscillations has showncompelling topological correlation between the frontal and occipital regions ofthe brain during conscious states. The topological trends of the underlyinghierarchical network organization have been characterized by the percentage ofthe hub and non-hub nodes, that further determines the global and localconnectivity trends. This has revealed interesting insights of functionaldisconnection during NREMS due to decrease in their number of hub-nodes ascompared to waking state. There is also switching behaviour in the ratio ofhub/non-hub nodes between frontal and occipital region during NREMS-Wake andWake-NREMS transitions. Our findings provide support as proof-of-principle offunctional regional inactivation or activation of hub-nodes as the gradualswitching mechanism towards transitioning of cognitive states in a gradedmanner, wake to sleep or vice versa; the detailed neuro-physio-chemicalmechanism needs further study.

Functional switching among dynamic neuronal hub-nodes in the brain induces transition of cognitive states