The reorganisation of memory during sleep

Landmann, Nina; Kühn, Marion; Piosczyk, Hannah; Feige, Bernd; Baglioni, Chiara; Spiegelhalder, Kai; Frase, Lukas; Riemann, Dieter; Sterr, Annette; Nissen, Christoph

doi:10.1016/j.smrv.2014.03.005

Cited by 135 publications

(114 citation statements)

References 136 publications

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“…Creativity and associative thinking have been thought to require the formation of "associative elements into new combinations, which either meet specified requirements or are in some way useful" (32). This leap away from existing associations has been hypothesized to require changes to memory that involve the disintegration of existing schemas to ignite new and useful combinations (54). REM sleep may facilitate schema disintegration due to its highly associative nature.…”

Section: Discussionmentioning

confidence: 99%

Autonomic activity during sleep predicts memory consolidation in humans

Whitehurst

Cellini

McDevitt

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Throughout history, psychologists and philosophers have proposed that good sleep benefits memory, yet current studies focusing on the relationship between traditionally reported sleep features (e.g., minutes in sleep stages) and changes in memory performance show contradictory findings. This discrepancy suggests that there are events occurring during sleep that have not yet been considered. The autonomic nervous system (ANS) shows strong variation across sleep stages. Also, increases in ANS activity during waking, as measured by heart rate variability (HRV), have been correlated with memory improvement. However, the role of ANS in sleepdependent memory consolidation has never been examined. Here, we examined whether changes in cardiac ANS activity (HRV) during a daytime nap were related to performance on two memory conditions (Primed and Repeated) and a nonmemory control condition on the Remote Associates Test. In line with prior studies, we found sleep-dependent improvement in the Primed condition compared with the Quiet Wake control condition. Using regression analyses, we compared the proportion of variance in performance associated with traditionally reported sleep features (model 1) vs. sleep features and HRV during sleep (model 2). For both the Primed and Repeated conditions, model 2 (sleep + HRV) predicted performance significantly better (73% and 58% of variance explained, respectively) compared with model 1 (sleep only, 46% and 26% of variance explained, respectively). These findings present the first evidence, to our knowledge, that ANS activity may be one potential mechanism driving sleep-dependent plasticity.sleep | heart rate variability | memory | consolidation | vagal activity S leep has been shown to facilitate the transformation of recent experiences into stable, long-term memories (i.e., consolidation), and specific electrophysiological sleep features have been implicated in this process (1). For example, minutes spent in slow wave sleep (SWS) and the number of sleep spindles [transient neural events in nonrapid eye movement (NREM) sleep, 12-15 Hz] in a posttraining sleep period correlate with the magnitude of explicit memory improvement [e.g., conscious, episodic memories (2, 3)]. Minutes in rapid eye movement (REM) sleep, on the other hand, are associated with improvements in implicit memory [e.g., unconscious, priming, procedural skills (4, 5)]. However, recent reviews and meta-analyses of the literature report inconsistencies in these findings (6, 7), suggesting that there may be unexplored factors critical to sleep-dependent memory consolidation.One possible influence that has received little attention in the sleep and memory literature is the autonomic nervous system (ANS). This lack of attention is somewhat surprising, considering that the literature describing ANS modulation of memory during wake is well established (8). Studies have found that memory storage of new information can be enhanced or impaired by directly modifying the activity of peripheral hormones following acquisition (9...

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Section: Discussionmentioning

confidence: 99%

Autonomic activity during sleep predicts memory consolidation in humans

Whitehurst

Cellini

McDevitt

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…REM sleep, on the other hand, benefits creativity that requires the disintegration of existing patterns 70 . Of note, both sleep stages are commonly reported as reduced/fragmented in OSA, and it is likely that some of the cognitive complaints and memory deficits described are partly acquired via this dysregulation.…”

Section: -69mentioning

confidence: 99%

Sleep apnoea and the brain: a complex relationship

Rosenzweig¹,

Glasser²,

Polšek³

et al. 2015

The Lancet Respiratory Medicine

211

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Summary (151/150 words)The complex relationship between obstructive sleep apnoea (OSA) and the brain is explored in this review. During the untreated apnoea/hypopnoea, intermittent hypoxia, reoxygenation and hyper/hypocapnia occur, in both adults and children, along with changes in cerebral blood flow and sleep fragmentation. They may in time result in cognitive deficits with functional consequences for work and school efficiency.The ability to assess how OSA affects cognition depends on the specificity and sensitivity of the tests, which are rarely developed specifically for OSA. In this review we discuss both the neural adaptive and maladaptive processes to hypoxemia. Their net result on cognitive and emotional performance depends on the stage of this dynamic process, effects on other body systems, cognitive reserve and the idiosyncratic susceptibility. The contribution of fragmented sleep and the disruption of sleep structure is also explored, with a focus on its effects at different times in the genesis of the disease. Lancet Respiratory Medicine

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“…However, there have been some attempts to elucidate the role of sleeping in human beings. It has been related to plasticity [2], and also to the reorganization of memory [3,4].…”

Section: Introductionmentioning

confidence: 99%

Automatic Sleep Stages Classification Using EEG Entropy Features and Unsupervised Pattern Analysis Techniques

Rodríguez-Sotelo

Osorio-Forero

Jiménez-Rodríguez

et al. 2014

Entropy

106

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Sleep is a growing area of research interest in medicine and neuroscience. Actually, one major concern is to find a correlation between several physiologic variables and sleep stages. There is a scientific agreement on the characteristics of the five stages of human sleep, based on EEG analysis. Nevertheless, manual stage classification is still the most widely used approach. This work proposes a new automatic sleep classification method based on unsupervised feature classification algorithms recently developed, and on EEG entropy measures. This scheme extracts entropy metrics from EEG records to obtain a feature vector. Then, these features are optimized in terms of relevance using the Q-α algorithm. Finally, the resulting set of features is entered into a clustering procedure to obtain a final segmentation of the sleep stages. The proposed method reached up to an average of 80% correctly classified stages for each patient separately while keeping the computational cost low.

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The reorganisation of memory during sleep

Cited by 135 publications

References 136 publications

Autonomic activity during sleep predicts memory consolidation in humans

Autonomic activity during sleep predicts memory consolidation in humans

Sleep apnoea and the brain: a complex relationship

Automatic Sleep Stages Classification Using EEG Entropy Features and Unsupervised Pattern Analysis Techniques

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