Abstract
The cognitive states have broadly been divided into waking, rapid eye movement sleep (REMS), and non-REMS (NREMS). The exact mechanism of cognitive state maintenance/transition is unknown to date. We have proposed that functional activation/deactivation of specific brain regions leads to such transition irrespective of the underlying cortical structure complexity. An analysis of electroencephalogram (EEG) allows us to explore properties and associations among brain regions. To address our query, we have recorded the frontal and occipital cortical EEG from surgically prepared chronic freely moving, normally behaving rats and classified vigilance states (VS) and vigilance state transitions (VST). Brain functional and structural complexity analysis has been carried out to characterize VS and VST. The multifractal spectrum width categorized VST as highly non-linear and more complex than vigilance states. The NREMS possesses a more complex cortical structure but it exhibits lower functional complexity than REMS and Wake. Further, the EEG signals decomposed into brain oscillations and dynamic network attributes of these oscillations show a strong/weak correlation of topology between the frontal and occipital regions reflecting synchrony/de-synchrony, respectively, during a cognitive state or transition. The functional topology trends of the underlying hierarchical network organization have been characterized by the percentage of the hub and non-hub nodes, which further determines the global and local connectivity trends. The switching behaviour in the ratio of hub/non-hub nodes between frontal and occipital regions during NREMS-Wake and Wake-NREMS transitions provides support as proof-of-principle of functional regional inactivation or activation of hub-nodes as the gradual switching mechanism towards transitioning of cognitive states in a graded (or non-flipping) manner, wake to sleep or vice versa; the detailed neuro-physio-chemical mechanism needs further study. Understanding sleep-wake transitions is vital for addressing sleep disorders, such as insomnia and sleep apnea. Analyzing EEG signals in rats reveals neural mechanisms behind these transitions, laying groundwork for precision interventions to restore healthy sleep patterns and mitigate sleep disorder impacts on cognition and well-being.
Published Version
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