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Functional connectivity at awakening: the cerebral correlates of sleep inertia assessed with combined EEG-fMRI

On The May 29, 2017

Raphael Vallat

Abstract :

The transition from sleep to wake is characterized by reduced vigilance, sleepiness and impaired performances, a state often referred as sleep inertia. Even though the behavioral aspects of sleep inertia are now well documented, its cerebral underpinning remain still poorly understood. A previous PET study has shown that the resumption of normal waking cerebral blood flow took about 20 minutes in prefrontal and neocortical areas, an observation thought to reflect the slow re-establishment of alertness across the minutes following awakening. The present study goes a step further by characterizing the changes in functional connectivity patterns throughout the sleep inertia period. We performed a simultaneous EEG-fMRI study over thirty-nine participants during an afternoon nap after a 3 hours partial sleep deprivation. Functional connectivity was assessed using 6 minutes resting-state scans performed before the nap, upon awakening from NREM sleep, and 25 min after awakening. Each resting-state scan was coupled with a behavioral task to measure the corresponding impairment of cognitive performances. Functional connectivity during sleep inertia was similar in certain respects to the functional connectivity observed during NREM sleep, including a disruption of several nodes of the default mode network in addition with a slight decrease in the anti-correlation between the default mode and dorsal attention networks. In addition we found a negative significant correlation between the percentage of N2/N3 sleep during the nap and the average connectivity of these two networks immediately upon awakening. The sensori-motor network was also severely altered, even at 25 minutes post-awakening. Our findings indicate that the first half hour after awakening is associated with a progressive resumption of the normal waking functional connectivity across several, but not all, brain networks.