Over more than a century of research has established the fact that sleep benefits the retention of memory. In this review we aim to comprehensively cover the field of "sleep and memory" research by providing a historical perspective on concepts and a discussion of more recent key findings. Whereas initial theories posed a passive role for sleep enhancing memories by protecting them from interfering stimuli, current theories highlight an active role for sleep in which memories undergo a process of system consolidation during sleep. Whereas older research concentrated on the role of rapid-eye-movement (REM) sleep, recent work has revealed the importance of slow-wave sleep (SWS) for memory consolidation and also enlightened some of the underlying electrophysiological, neurochemical, and genetic mechanisms, as well as developmental aspects in these processes. Specifically, newer findings characterize sleep as a brain state optimizing memory consolidation, in opposition to the waking brain being optimized for encoding of memories. Consolidation originates from reactivation of recently encoded neuronal memory representations, which occur during SWS and transform respective representations for integration into long-term memory. Ensuing REM sleep may stabilize transformed memories. While elaborated with respect to hippocampus-dependent memories, the concept of an active redistribution of memory representations from networks serving as temporary store into long-term stores might hold also for non-hippocampus-dependent memory, and even for nonneuronal, i.e., immunological memories, giving rise to the idea that the offline consolidation of memory during sleep represents a principle of long-term memory formation established in quite different physiological systems.

https://www.zora.uzh.ch/id/eprint/77770/1/physiol_rev_93.pdf

About sleep's role in memory

Deficits in daytime performance due to sleep loss are experienced universally and associated with a significant social, financial, and human cost. Microsleeps, sleep attacks, and lapses in cognition increase with sleep loss as a function of state instability. Sleep deprivation studies repeatedly show a variable (negative) impact on mood, cognitive performance, and motor function due to an increasing sleep propensity and destabilization of the wake state. Specific neurocognitive domains including executive attention, working memory, and divergent higher cognitive functions are particularly vulnerable to sleep loss. In humans, functional metabolic and neurophysiological studies demonstrate that neural systems involved in executive function (i.e., prefrontal cortex) are more susceptible to sleep deprivation in some individuals than others. Recent chronic partial sleep deprivation experiments, which more closely replicate sleep loss in society, demonstrate that profound neurocognitive deficits accumulate over time in the face of subjective adaptation to the sensation of sleepiness. Sleep deprivation associated with disease-related sleep fragmentation (i.e., sleep apnea and restless legs syndrome) also results in neurocognitive performance decrements similar to those seen in sleep restriction studies. Performance deficits associated with sleep disorders are often viewed as a simple function of disease severity; however, recent experiments suggest that individual vulnerability to sleep loss may play a more critical role than previously thought.

/pdf/neurocognitive-consequences-of-sleep-deprivation-hg8oxdvlng.pdf

Neurocognitive Consequences of Sleep Deprivation

Daytime performance changes were examined during chronic sleep restriction or augmentation and following subsequent recovery sleep. Sixty-six normal volunteers spent either 3 (n = 18), 5 (n= 16), 7 (n = 16), or 9 h (n = 16) daily time in bed (TIB) for 7 days (restriction/augmentation) followed by 3 days with 8 h daily TIB (recovery). In the 3-h group, speed (mean and fastest 10% of responses) on the psychomotor vigilance task (PVT) declined, and PVT lapses (reaction times greater than 500 ms) increased steadily across the 7 days of sleep restriction. In the 7- and 5-h groups speed initially declined, then appeared to stabilize at a reduced level; lapses were increased only in the 5-h group. In the 9-h group, speed and lapses remained at baseline levels. During recovery, PVT speed in the 7- and 5-h groups (and lapses in the 5-h group) remained at the stable, but reduced levels seen during the last days of the experimental phase, with no evidence of recovery. Speed and lapses in the 3-h group recovered rapidly following the first night of recovery sleep; however, recovery was incomplete with speed and lapses stabilizing at a level comparable with the 7- and 5-h groups. Performance in the 9-h group remained at baseline levels during the recovery phase. These results suggest that the brain adapts to chronic sleep restriction. In mild to moderate sleep restriction this adaptation is sufficient to stabilize performance, although at a reduced level. These adaptive changes are hypothesized to restrict brain operational capacity and to persist for several days after normal sleep duration is restored, delaying recovery.

https://onlinelibrary.wiley.com/doi/pdf/10.1046/j.1365-2869.2003.00337.x

Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: a sleep dose-response study

http://www.kvccdocs.com/KVCC/2013-Summer/PSY101-OL/content/L-04/sleep-loss.pdf

Sleep loss, learning capacity and academic performance

Sleep deprivation is commonplace in modern society, but its far-reaching effects on cognitive performance are only beginning to be understood from a scientific perspective. While there is broad consensus that insufficient sleep leads to a general slowing of response speed and increased variability in performance, particularly for simple measures of alertness, attention and vigilance, there is much less agreement about the effects of sleep deprivation on many higher level cognitive capacities, including perception, memory and executive functions. Central to this debate has been the question of whether sleep deprivation affects nearly all cognitive capacities in a global manner through degraded alertness and attention, or whether sleep loss specifically impairs some aspects of cognition more than others. Neuroimaging evidence has implicated the prefrontal cortex as a brain region that may be particularly susceptible to the effects of sleep loss, but perplexingly, executive function tasks that putatively measure prefrontal functioning have yielded inconsistent findings within the context of sleep deprivation. Whereas many convergent and rule-based reasoning, decision making and planning tasks are relatively unaffected by sleep loss, more creative, divergent and innovative aspects of cognition do appear to be degraded by lack of sleep. Emerging evidence suggests that some aspects of higher level cognitive capacities remain degraded by sleep deprivation despite restoration of alertness and vigilance with stimulant countermeasures, suggesting that sleep loss may affect specific cognitive systems above and beyond the effects produced by global cognitive declines or impaired attentional processes. Finally, the role of emotion as a critical facet of cognition has received increasing attention in recent years and mounting evidence suggests that sleep deprivation may particularly affect cognitive systems that rely on emotional data. Thus, the extent to which sleep deprivation affects a particular cognitive process may depend on several factors, including the magnitude of global decline in general alertness and attention, the degree to which the specific cognitive function depends on emotion-processing networks, and the extent to which that cognitive process can draw upon associated cortical regions for compensatory support.

Effects of sleep deprivation on cognition

The effects of sleep deprivation on the neural substrates of cognition are poorly understood. Here we used functional magnetic resonance imaging to measure the effects of 35 hours of sleep deprivation on cerebral activation during verbal learning in normal young volunteers. On the basis of a previous hypothesis1, we predicted that the prefrontal cortex (PFC) would be less responsive to cognitive demands following sleep deprivation. Contrary to our expectations, however, the PFC was more responsive after one night of sleep deprivation than after normal sleep. Increased subjective sleepiness in sleep-deprived subjects correlated significantly with activation of the PFC. The temporal lobe was activated after normal sleep but not after sleep deprivation; in contrast, the parietal lobes were not activated after normal sleep but were activated after sleep deprivation. Although sleep deprivation significantly impaired free recall compared with the rested state, better free recall in sleep-deprived subjects was associated with greater parietal lobe activation. These findings show that there are dynamic, compensatory changes in cerebral activation during verbal learning after sleep deprivation and implicate the PFC and parietal lobes in this compensation.

Altered brain response to verbal learning following sleep deprivation

Thirteen normal volunteers were studied with fMRI during arithmetic performance after a normal night of sleep and following sleep deprivation (SD) Aims included determining whether the prefrontal cortex (PFC) and the parietal lobe arithmetic areas are vulnerable to the effects of SD After a normal night of sleep, activation localized to the bilateral PFC, parietal lobes and premotor areas Following SD, activity in these regions decreased markedly, especially in the PFC Performance also dropped Data from the serial subtraction task are consistent with Horne's PFC vulnerability hypothesis but, based on this and other studies, we suggest the localized, functional effects of SD in the brain may vary, in part, with the specific cognitive task

/pdf/sleep-deprivation-induced-reduction-in-cortical-functional-1u7qry2442.pdf

Sleep deprivation-induced reduction in cortical functional response to serial subtraction.

Semantic and cross-case identity priming were investigated in nondemented patients with Parkinson's disease (PD) and controls using the Lexical Decision Task. Three conditions were administered that consisted of the presentation of prime and target word pairs. In the semantic priming condition the word pairs were semantically related (e.g., table-CHAIR), in the cross-case identity priming condition the word pairs consisted of the same word (e.g., noise-NOISE), and in the unrelated condition the word pairs were not related semantically (e.g., guns-DEEP). A fourth condition was also administered that consisted of the presentation of a prime word and a pronounceable nonword target (e.g., starved-FORVE). Participants were asked to indicate whether the target was a real word or a nonword. The prime and target were separated by either a short or long (250 ms or 1000 ms) stimulus onset asynchrony (SOA). Results indicated that PD patients displayed normal semantic priming (i.e., faster responding to the target in...

Semantic and cross-case identity priming in patients with Parkinson's disease.

OBJECTIVE
Growing evidence supports the importance of learning as a central deficit in preclinical/prodromal Alzheimer's disease. The aims of this study were to conduct a series of neural network simulations to develop a functional understanding of a distributed, nonmodular memory system that can learn efficiently without interference. This understanding is applied to the development of a novel digital memory test.


METHOD
Simulations using traditional feed forward neural network architectures to learn simple logic problems are presented. The simulations demonstrate three limitations: (a) inefficiency, (b) an inability to learn problems consistently, and (c) catastrophic interference when given multiple problems. A new mirrored cascaded architecture is introduced to address these limitations, with support provided by a series of simulations.


RESULTS
The mirrored cascaded architecture demonstrates efficient and consistent learning relative to feed forward networks but also suffers from catastrophic interference. Addition of context values to add the capability of distinguishing features as part of learning eliminates the problem of interference in the mirrored cascaded, but not the feed forward, architectures.


CONCLUSIONS
A mirrored cascaded architecture addresses the limitations of traditional feed forward neural networks, provides support for a distributed memory system, and emphasizes the importance of context to avoid interference. These process models contributed to the design of a digital computer-adaptive word list learning test that places maximum stress on the capability to distinguish specific episodes of learning. Process simulations provide a useful method of testing models of brain function and contribute to new approaches to neuropsychological assessment. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Neural network process simulations support a distributed memory system and aid design of a novel computer adaptive digital memory test for preclinical and prodromal Alzheimer's disease.

learning following sleep deprivation

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