It is hypothesized that deep sleep is essential for restoring the brain’s capacity to learn efficiently, especially in regions heavily activated during the day. However, causal evidence in humans has been lacking due to the inability to sleep deprive one target area while keeping the natural sleep pattern intact. Here we introduce a novel approach to focally perturb deep sleep in motor cortex, and investigate the consequences on behavioural and neurophysiological markers of neuroplasticity arising from dedicated motor practice. We show that the capacity to undergo neuroplastic changes is reduced by wakefulness but restored during unperturbed sleep. This restorative process is markedly attenuated when slow waves are selectively perturbed in motor cortex, demonstrating that deep sleep is a requirement for maintaining sustainable learning efficiency.

SUMMARYObjective: In CSWS (continuous spike waves during sleep) activation of spike waves during slow wave sleep has been causally linked to neuropsychological deficits, but the pathophysiologic mechanisms are still unknown. In healthy subjects, the overnight decrease of the slope of slow waves in NREM (non-rapid eye movement) sleep has been linked to brain recovery to regain optimal cognitive performance. Here, we investigated whether the electrophysiologic hallmark of CSWS, the spike waves during sleep, is related to an alteration in the overnight decrease of the slope, and if this alteration is linked to location and density of spike waves. Methods: In a retrospective study, the slope of slow waves (0.5-2 Hz) in the first hour and last hour of sleep (19 electroencephalography [EEG] electrodes) of 14 patients with CSWS (3.1-13.5 years) was calculated. The spike wave "focus" was determined as the location of highest spike amplitude and the density of spike waves as spike wave index (SWI). Results: There was no overnight change of the slope of slow waves in the "focus." Instead, in "nonfocal" regions, the slope decreased significantly. This difference in the overnight course resulted in a steeper slope in the "focus" compared to "nonfocal" electrodes during the last hour of sleep. Spike wave density was correlated with the impairment of the overnight slope decrease: The higher the SWI, the more hampered the slope decrease. Significance: Location and density of spike waves are related to an alteration of the physiologic overnight decrease of the slow wave slope. This overnight decrease of the slope was shown to be closely related to the recovery function of sleep. Such recovery is necessary for optimal cognitive performance during wakefulness. Therefore we propose the impairment of this process by spike waves as a potential mechanism leading to neuropsychological deficits in CSWS.

The use of information-based measures to assess changes in conscious state is an increasingly popular topic. Though recent results have seemed to justify the merits of such methods, little has been done to investigate the applicability of such measures to children. For our work, we used the approximate entropy (ApEn), a measure previously shown to correlate with changes in conscious state when applied to the electroencephalogram (EEG), and sought to confirm whether previously reported trends in adult ApEn values across wake and sleep were present in children. Besides validating the prior findings that ApEn decreases from wake to sleep (including wake, rapid eye movement (REM) sleep, and non-REM sleep) in adults, we found that previously reported ApEn decreases across vigilance states in adults were also present in children (ApEn trends for both age groups: wake > REM sleep > non-REM sleep). When comparing ApEn values between age groups, adults had significantly larger ApEn values than children during wakefulness. After the application of an 8 Hz high-pass filter to the EEG signal, ApEn values were recalculated. The number of electrodes with significant vigilance state effects dropped from all 109 electrodes with the original 1 Hz filter to 1 electrode with the 8 Hz filter. The number of electrodes with significant age effects dropped from 10 to 4. Our results support the notion that ApEn can reliably distinguish between vigilance states, with low-frequency sleep-related oscillations implicated as the driver of changes between vigilance states. We suggest that the observed differences between adult and child ApEn values during wake may reflect differences in connectivity between age groups, a factor which may be important in the use of EEG to measure consciousness.

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