The proposed mechanisms of sleep-dependent memory consolidation involve the overnight regulation of neural activity at both synaptic and whole-network levels. Now, there is a lack of in vivo data in humans elucidating if, and how, sleep and its varied stages balance neural activity, and if such recalibration benefits memory. We combined electrophysiology with in vivo two-photon calcium imaging in rodents as well as intracranial and scalp electroencephalography (EEG) in humans to reveal a key role for non-oscillatory brain activity during rapid eye movement (REM) sleep to mediate sleep-dependent recalibration of neural population dynamics. The extent of this REM sleep recalibration predicted the success of overnight memory consolidation, expressly the modulation of hippocampal—neocortical activity, favoring remembering rather than forgetting. The findings describe a non-oscillatory mechanism how human REM sleep modulates neural population activity to enhance long-term memory.

Summary: Many studies investigating sleep and memory consolidation have evaluated full‐night sleep rather than alternative sleep periods such as daytime naps. This multi‐centre study followed up on, and was compared with, an earlier full‐night study (Schabus et al., 2004) investigating the relevance of daytime naps for the consolidation of declarative and procedural memory. Seventy‐six participants were randomly assigned to a nap or wake group, and performed a declarative word‐pair association or procedural mirror‐tracing task. Performance changes from before to after a 90‐min retention interval filled with sleep or quiet wakefulness were evaluated between groups. Associations between performance changes, sleep architecture, spindles, and slow oscillations were investigated. For the declarative task we observed a trend towards stronger forgetting across a wake period compared with a nap period, and a trend towards memory increase over the full‐night. For the procedural task, accuracy was significantly decreased following daytime wakefulness, showed a trend to increase with a daytime nap, and significantly increased across full‐night sleep. For the nap protocol, neither sleep stages, spindles, nor slow oscillations predicted performance changes. A direct comparison of day and nighttime sleep revealed that daytime naps are characterized by significantly lower spindle density, but higher spindle activity and amplitude compared with full‐night sleep. In summary, data indicate that daytime naps protect procedural memories from deterioration, whereas full‐night sleep improves performance. Given behavioural and physiological differences between day and nighttime sleep, future studies should try to characterize potential differential effects of full‐night and daytime sleep with regard to sleep‐dependent memory consolidation.

Disturbed sleep can negatively affect overnight memory retention as well as new learning the subsequent day. In healthy participants, positive associations between memory performance and sleep characteristics (e.g., time spent in slow-wave sleep [SWS]) have been detected. In a previous study, we found that SWS was much reduced in patients with focal seizures, but when correlations between memory complaints and various sleep characteristics were considered, the only significant relationship was with the time to onset of rapid eye movement (REM) sleep (i.e., REM latency). In this study, we investigated the relationships between sleep, epilepsy, and objective memory performance variables. Twenty-five patients with focal seizures had their memory tested while undergoing a two-day ambulatory electroencephalography (EEG). The sleep variables of interest were the percentage of time spent in SWS (%SWS) and REM latency. Epilepsy variables included the presence of (1) seizures, (2) interictal epileptiform discharges, and/or (3) hippocampal lesions as well as site of seizure origin (temporal vs extratemporal). Overnight retention (of autobiographical events, a story, and a complex geometric figure) and the ability to learn a word list on day 2 were the measures of memory. A significant positive correlation was found between word-list learning and %SWS during the previous night. A significant negative correlation was observed between REM latency and overnight retention of autobiographical events. Overnight retention scores for the story and geometric figure were not related to sleep characteristics but were negatively affected by the presence of epileptiform activity. Story retention was also worse for temporal lobe epilepsy (TLE) than for patients with extratemporal epilepsy (ETE). Those with hippocampal lesions were more impaired than those without lesions on word-list learning, autobiographical events' retention, and story retention. When multiple contributing factors were entered into regression analyses, %SWS was found to be the best predictor of subsequent word-list learning, whereas the presence of a hippocampal lesion was the best predictor of overnight retention of autobiographical events and a story. These findings provide further evidence of the ways in which particular sleep characteristics are associated with memory and suggest that treatment of sleep disturbances in patients with epilepsy might be helpful for improving their performance.

Sharp-wave ripples (SWR) are central for cognition and hallmark sleep in the rodent hippocampus. Recently, ripple-like activity was also observed in the human hippocampus and neocortex during wakefulness and sleep. However, ripple detection across brain states and cortical regions remains challenging. We demonstrate that putative ripples largely index noise originating from region-, state-, and demand-dependent modulation of cortical background activity. We establish the noise sensitivity for five common detection algorithms across three intracranial EEG studies during sleep and cognitive engagement. On average, 77% of awake ripples in the medial temporal lobe, including the hippocampus, reflect false positives within the 1/ f ^χ noise floor. We also report task-related 1/ f ^χ modulations that lead to spurious ripple activity, and demonstrate scenarios where ripple detections are less impacted by noise. Our results offer a simulation-based approach to estimate the false positive rate and demonstrate the importance of 1/ f ^χ activity for state- and context-dependent cortical processing.