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

The importance of the gut-brain axis in maintaining homeostasis has long been appreciated. However, the past 15 yr have seen the emergence of the microbiota (the trillions of microorganisms within ...

The Microbiota-Gut-Brain Axis

The steep rise of type 2 diabetes mellitus (T2DM) and associated complications go along with mounting evidence of clinically important sex and gender differences. T2DM is more frequently diagnosed at lower age and body mass index in men; however, the most prominent risk factor, which is obesity, is more common in women. Generally, large sex-ratio differences across countries are observed. Diversities in biology, culture, lifestyle, environment, and socioeconomic status impact differences between males and females in predisposition, development, and clinical presentation. Genetic effects and epigenetic mechanisms, nutritional factors and sedentary lifestyle affect risk and complications differently in both sexes. Furthermore, sex hormones have a great impact on energy metabolism, body composition, vascular function, and inflammatory responses. Thus, endocrine imbalances relate to unfavorable cardiometabolic traits, observable in women with androgen excess or men with hypogonadism. Both biological and psychosocial factors are responsible for sex and gender differences in diabetes risk and outcome. Overall, psychosocial stress appears to have greater impact on women rather than on men. In addition, women have greater increases of cardiovascular risk, myocardial infarction, and stroke mortality than men, compared with nondiabetic subjects. However, when dialysis therapy is initiated, mortality is comparable in both males and females. Diabetes appears to attenuate the protective effect of the female sex in the development of cardiac diseases and nephropathy. Endocrine and behavioral factors are involved in gender inequalities and affect the outcome. More research regarding sex-dimorphic pathophysiological mechanisms of T2DM and its complications could contribute to more personalized diabetes care in the future and would thus promote more awareness in terms of sex- and gender-specific risk factors.

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Sex and Gender Differences in Risk, Pathophysiology and Complications of Type 2 Diabetes Mellitus.

OBJECTIVES We validated actigraphy for detecting sleep and wakefulness versus polysomnography (PSG). DESIGN Actigraphy and polysomnography were simultaneously collected during sleep laboratory admissions. All studies involved 8.5 h time in bed, except for sleep restriction studies. Epochs (30-sec; n = 232,849) were characterized for sensitivity (actigraphy = sleep when PSG = sleep), specificity (actigraphy = wake when PSG = wake), and accuracy (total proportion correct); the amount of wakefulness after sleep onset (WASO) was also assessed. A generalized estimating equation (GEE) model included age, gender, insomnia diagnosis, and daytime/nighttime sleep timing factors. SETTING Controlled sleep laboratory conditions. PARTICIPANTS Young and older adults, healthy or chronic primary insomniac (PI) patients, and daytime sleep of 23 night-workers (n = 77, age 35.0 ± 12.5, 30F, mean nights = 3.2). INTERVENTIONS N/A. MEASUREMENTS AND RESULTS Overall, sensitivity (0.965) and accuracy (0.863) were high, whereas specificity (0.329) was low; each was only slightly modified by gender, insomnia, day/night sleep timing (magnitude of change 30 min/night. CONCLUSIONS This validation quantifies strengths and weaknesses of actigraphy as a tool measuring sleep in clinical and population studies. Overall, the participant-specific accuracy is relatively high, and for most participants, above 80%. We validate this finding across multiple nights and a variety of adults across much of the young to midlife years, in both men and women, in those with and without insomnia, and in 77 participants. We conclude that actigraphy is overall a useful and valid means for estimating total sleep time and wakefulness after sleep onset in field and workplace studies, with some limitations in specificity.

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Measuring sleep: accuracy, sensitivity, and specificity of wrist actigraphy compared to polysomnography.

Circadian clocks coordinate physiology and behavior with the 24h solar day to provide temporal homeostasis with the external environment. The molecular clocks that drive these intrinsic rhythmic changes are based on interlocked transcription/translation feedback loops that integrate with diverse environmental and metabolic stimuli to generate internal 24h timing. In this review we highlight recent advances in our understanding of the core molecular clock and how it utilizes diverse transcriptional and post-transcriptional mechanisms to impart temporal control onto mammalian physiology. Understanding the way in which biological rhythms are generated throughout the body may provide avenues for temporally directed therapeutics to improve health and prevent disease.

Molecular Architecture of the Mammalian Circadian Clock

Study Objectives: Examine sleep restriction’s effects on weight gain, daily caloric intake, and meal timing. Design: Repeated-measures experiments assessing body weight at admittance and discharge in all subjects (N = 225) and caloric intake and meal timing across days following 2 baseline nights, 5 sleep restriction nights and 2 recovery nights or across days following control condition nights in a subset of subjects (n = 37). Setting: Controlled laboratory environment. Participants: Two hundred twenty-five healthy adults aged 22-50 y (n = 198 sleep-restricted subjects; n = 31 with caloric intake data; n = 27 control subjects; n = 6 with caloric intake data). Interventions: Approximately 8-to-1 randomization to an experimental condition (including five consecutive nights of 4 h time in bed [TIB]/night, 04:00-08:00) or to a control condition (all nights 10 h TIB/night, 22:00-08:00). Measurements and Results: Sleep-restricted subjects gained more weight (0.97 ± 1.4 kg) than control subjects (0.11 ± 1.9 kg; d = 0.51, P = 0.007). Among sleep-restricted subjects, African Americans gained more weight than Caucasians (d = 0.37, P = 0.003) and males gained more weight than females (d = 0.38, P = 0.004). Sleep-restricted subjects consumed extra calories (130.0 ± 43.0% of daily caloric requirement) during days with a delayed bedtime (04:00) compared with control subjects who did not consume extra calories (100.6 ± 11.4%; d = 0.94, P = 0.003) during corresponding days. In sleep-restricted subjects, increased daily caloric intake was due to more meals and the consumption of 552.9 ± 265.8 additional calories between 22:00-03:59. The percentage of calories derived from fat was greater during late-night hours (22:00-03:59, 33.0 ± 0.08%) compared to daytime (08:00-14:59, 28.2 ± 0.05%) and evening hours (15:00-21:59, 29.4 ± 0.06%; Ps < 0.05). Conclusions: In the largest, most diverse healthy sample studied to date under controlled laboratory conditions, sleep restriction promoted weight gain. Chronically sleep-restricted adults with late bedtimes may be more susceptible to weight gain due to greater daily caloric intake and the con

/pdf/effects-of-experimental-sleep-restriction-on-weight-gain-4gqbr67mk6.pdf

Effects of Experimental Sleep Restriction on Weight Gain, Caloric Intake, and Meal Timing in Healthy Adults

Much of the current science on, and mathematical modeling of, dynamic changes in human performance within and between days is dominated by the two-process model of sleep-wake regulation, which posits a neurobiological drive for sleep that varies homeostatically (increasing as a saturating exponential during wakefulness and decreasing in a like manner during sleep), and a circadian process that neurobiologically modulates both the homeostatic drive for sleep and waking alertness and performance. Endogenous circadian rhythms in neurobehavioral functions, including physiological alertness and cognitive performance, have been demonstrated using special laboratory protocols that reveal the interaction of the biological clock with the sleep homeostatic drive. Individual differences in circadian rhythms and genetic and other components underlying such differences also influence waking neurobehavioral functions. Both acute total sleep deprivation and chronic sleep restriction increase homeostatic sleep drive and degrade waking neurobehavioral functions as reflected in sleepiness, attention, cognitive speed, and memory. Recent evidence indicating a high degree of stability in neurobehavioral responses to sleep loss suggests that these trait-like individual differences are phenotypic and likely involve genetic components, including circadian genes. Recent experiments have revealed both sleep homeostatic and circadian effects on brain metabolism and neural activation. Investigation of the neural and genetic mechanisms underlying the dynamically complex interaction between sleep homeostasis and circadian systems is beginning. A key goal of this work is to identify biomarkers that accurately predict human performance in situations in which the circadian and sleep homeostatic systems are perturbed.

Circadian Rhythms, Sleep Deprivation, and Human Performance

Night eating syndrome (NES) is characterized by evening hyperphagia andfrequentawakeningsaccompaniedbyfoodintake.PatientswithNESdisplay a delayed circadian pattern of food intake but retain a normal sleep-wake cycle. Thesecharacteristicsinitiatedthecurrentstudy,inwhichthephaseandamplitude of behavioral and neuroendocrine circadian rhythms in patients with NES were evaluated. Fifteen women with NES (mean age ±SD, 40.8 ±8.7 y) and 14 control subjects(38.6 ±9.5y)werestudiedinthelaboratoryfor3nights,withfoodintake measured daily. Blood also was collected for 25 h (every 2 h from 0800 to 2000 h, and then hourly from 2100 to 0900 h) and assayed for glucose and 7 hormones (insulin, ghrelin, leptin, melatonin, cortisol, thyroid-stimulating hormone (TSH) and prolactin). Statistical analyses utilized linear mixed-effects cosinor analysis. Control subjects displayed normal phases and amplitudes for all circadian rhythms. In contrast, patients with NES showed a phase delay in the timing of meals, and delayed circadian rhythms for total caloric, fat, and carbohydrate intake. In addition, phase delays of 1.0 to 2.8 h were found in 2 food-regulatory rhythms—leptinandinsulin—andinthecircadianmelatoninrhythm(withatrend foradelayinthecircadiancortisolrhythm).Incontrast,circulatinglevelsofghre- lin,theprimaryhormonethatstimulatesfoodintake,werephaseadvancedby5.2 h. The glucose rhythm showed an inverted circadian pattern. Patients with NES

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Circadian Rhythm Profiles in Women with Night Eating Syndrome

Background: The variable number tandem repeat (VNTR) polymorphism 5-repeat allele of the circadian gene PERIOD3 (PER3 5/5 ) has been associated with cognitive decline at a specific circadian phase in response to a night of total sleep deprivation (TSD), relative to the 4-repeat allele (PER3 4/4 ). PER3 5/5 has also been related to higher sleep homeostasis, which is thought to underlie this cognitive vulnerability. To date, no study has used a candidate gene approach to investigate the response to chronic partial sleep deprivation (PSD), a condition distinct from TSD and one commonly experienced by millions of people on a daily and persistent basis. We evaluated whether the PER3 VNTR polymorphism contributed to cumulative neurobehavioral deficits and sleep homeostatic responses during PSD. Methodology/Principal Findings: PER3 5/5 (n=14), PER3 4/5 (n=63) and PER3 4/4 (n=52) healthy adults (aged 22–45 y) demonstrated large, but equivalent cumulative decreases in cognitive performance and physiological alertness, and cumulative increases in sleepiness across 5 nights of sleep restricted to 4 h per night. Such effects were accompanied by increasing daily inter-subject variability in all groups. The PER3 genotypes did not differ significantly at baseline in habitual sleep, physiological sleep structure, circadian phase, physiological sleepiness, cognitive performance, or subjective sleepiness, although during PSD, PER3 5/5 subjects had slightly but reliably elevated sleep homeostatic pressure as measured physiologically by EEG slow-wave energy in non-rapid eye movement sleep compared with PER3 4/4 subjects. PER3 genotypic and allelic frequencies did not differ significantly between Caucasians and African Americans. Conclusions/Significance: The PER3 VNTR polymorphism was not associated with individual differences in neurobehavioral responses to PSD, although it was related to one marker of sleep homoeostatic response during PSD. The comparability of PER3 genotypes at baseline and their equivalent inter-individual vulnerability to sleep restriction indicate that PER3 does not contribute to the neurobehavioral effects of chronic sleep loss.

Namni Goel

Papers

Effects of Experimental Sleep Restriction on Weight Gain, Caloric Intake, and Meal Timing in Healthy Adults

Circadian Rhythms, Sleep Deprivation, and Human Performance

Circadian Rhythm Profiles in Women with Night Eating Syndrome

PER3 polymorphism predicts cumulative sleep homeostatic but not neurobehavioral changes to chronic partial sleep deprivation.

Sleep deprivation and neurobehavioral dynamics