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Study Objectives Fast frequency sleep spindles are reduced in aging and Alzheimer’s disease (AD), but the mechanisms and functional relevance of these deficits remain unclear. The study objective was to identify AD biomarkers associated with fast sleep spindle deficits in cognitively unimpaired older adults at risk for AD. Methods Fifty-eight cognitively unimpaired, β-amyloid-negative, older adults (mean ± SD; 61.4 ± 6.3 years, 38 female) enriched with parental history of AD (77.6%) and apolipoprotein E (APOE) ε4 positivity (25.9%) completed the study. Cerebrospinal fluid (CSF) biomarkers of central nervous system inflammation, β-amyloid and tau proteins, and neurodegeneration were combined with polysomnography (PSG) using high-density electroencephalography and assessment of overnight memory retention. Parallelized serial mediation models were used to assess indirect effects of age on fast frequency (13 to Results Glial activation was associated with prefrontal fast frequency sleep spindle expression deficits. While adjusting for sex, APOE ε4 genotype, apnea–hypopnea index, and time between CSF sampling and sleep study, serial mediation models detected indirect effects of age on fast sleep spindle expression through microglial activation markers and then tau phosphorylation and synaptic degeneration markers. Sleep spindle expression at these electrodes was also associated with overnight memory retention in multiple regression models adjusting for covariates. Conclusions These findings point toward microglia dysfunction as associated with tau phosphorylation, synaptic loss, sleep spindle deficits, and memory impairment even prior to β-amyloid positivity, thus offering a promising candidate therapeutic target to arrest cognitive decline associated with aging and AD.

Study Objectives To determine whether subjective measures of exercise and sleep are associated with cognitive complaints and whether exercise effects are mediated by sleep. Methods This study analyzed questionnaire data from adults (18–89) enrolled in a recruitment registry. The Cognitive Function Instrument (CFI) assessed cognitive complaints. Medical Outcomes Study Sleep Scale (MOS-SS) subscales and factor scores assessed sleep quality, daytime sleepiness, nighttime disturbance, and insomnia and obstructive sleep apnea (OSA)-like symptoms. Exercise frequency was defined as the weekly number of exercise sessions. Exercise frequency, MOS-SS subscales, and factor scores were examined as predictors of CFI score, adjusting for age, body mass index, education, sex, cancer diagnosis, antidepressant usage, psychiatric conditions, and medical comorbidities. Analyses of covariance examined the relationship between sleep duration groups (short, mid-range, and long) and CFI score, adjusting for covariates. Mediation by sleep in the exercise-CFI score relationship was tested. Results Data from 2106 adults were analyzed. Exercise and MOS-SS subscales and factor scores were associated with CFI score. Higher Sleep Adequacy scores were associated with fewer cognitive complaints, whereas higher Sleep Somnolence, Sleep Disturbance, Sleep Problems Index I, Sleep Problems Index II, and factor scores were associated with more cognitive complaints. MOS-SS subscales and factor scores, except Sleep Disturbance and the insomnia factor score, mediated the association between exercise and cognitive complaints. Conclusions The relationship between exercise frequency and subjective cognitive performance is mediated by sleep. In particular, the mediation effect appears to be driven by symptoms possibly suggestive of OSA which are negatively associated with exercise engagement, sleep quality, daytime sleepiness, and subjective cognitive performance.

Hippocampal-dependent memory consolidation during sleep is hypothesized to depend on the synchronization of distributed neuronal ensembles, organized by the hippocampal sharp-wave ripples (SWRs, 80 to 150 Hz), subcortical/cortical slow-wave activity (SWA, 0.5 to 4 Hz), and sleep spindles (SP, 7 to 15 Hz). However, the precise role of these interactions in synchronizing subcortical/cortical neuronal activity is unclear. Here, we leverage intracranial electrophysiological recordings from the human hippocampus, amygdala, and temporal and frontal cortices to examine activity modulation and cross-regional coordination during SWRs. Hippocampal SWRs are associated with widespread modulation of high-frequency activity (HFA, 70 to 200 Hz), a measure of local neuronal activation. This peri-SWR HFA modulation is predicted by the coupling between hippocampal SWRs and local subcortical/cortical SWA or SP. Finally, local cortical SWA phase offsets and SWR amplitudes predicted functional connectivity between the frontal and temporal cortex during individual SWRs. These findings suggest a selection mechanism wherein hippocampal SWR and cortical slow-wave synchronization governs the transient engagement of distributed neuronal populations supporting hippocampal-dependent memory consolidation.

Summary Experimental sleep-wake disruption in rodents and humans causally modulates β-amyloid (Aβ) dynamics (e.g., [ 1 , 2 , 3 ]). This leads to the hypothesis that, beyond cross-sectional associations, impaired sleep structure and physiology could represent prospective biomarkers of the speed with which Aβ accumulates over time. Here, we test the hypothesis that initial baseline measures of non-rapid eye movement (NREM) sleep slow-wave activity (SWA) and sleep quality (efficiency) provide future forecasting sensitivity to the rate of Aβ accumulation over subsequent years. A cohort of clinically normal older adults was assessed using objective sleep polysomnography in combination with longitudinal tracking of Aβ accumulation with [11C]PiB positron emission tomography (PET) imaging. Both the proportion of NREM SWA below 1 Hz and the measure of sleep efficiency predicted the speed (slope) of subsequent Aβ deposition over time, and these associations remained robust when taking into account additional cofactors of interest (e.g., age, sex, sleep apnea). Moreover, these measures were specific, such that no other macro- and microphysiological architecture metrics of sleep demonstrated such sensitivity. Our data support the proposal that objective sleep markers could be part of a set of biomarkers that statistically forecast the longitudinal trajectory of cortical Aβ deposition in the human brain. Sleep may therefore represent a potentially affordable, scalable, repeatable, and non-invasive tool for quantifying of Aβ pathological progression, prior to cognitive symptoms of Alzheimer’s disease (AD).

See Mander et al. (doi:10.1093/awx174) for a scientific commentary on this article.

How are memories transferred from short-term to long-term storage? Systems-level memory consolidation is thought to be dependent on the coordinated interplay of cortical slow waves, thalamo-cortical sleep spindles and hippocampal ripple oscillations. However, it is currently unclear how the selective interaction of these cardinal sleep oscillations is organized to support information reactivation and transfer. Here, using human intracranial recordings, we demonstrate that the prefrontal cortex plays a key role in organizing the ripple-mediated information transfer during non-rapid eye movement (NREM) sleep. We reveal a temporally precise form of coupling between prefrontal slow-wave and spindle oscillations, which actively dictates the hippocampal-neocortical dialogue and information transfer. Our results suggest a model of the human sleeping brain in which rapid bidirectional interactions, triggered by the prefrontal cortex, mediate hippocampal activation to optimally time subsequent information transfer to the neocortex during NREM sleep., How are memories transferred from short-term to long-term storage? Here, the authors show that during deep (NREM) sleep, the prefrontal cortex initiates rapid, bidirectional interactions to trigger information transfer from the hippocampus to the neocortex.

Deep non-rapid eye movement sleep (NREM) and general anesthesia with propofol are prominent states of reduced arousal linked to the occurrence of synchronized oscillations in the electroencephalogram (EEG). Although rapid eye movement (REM) sleep is also associated with diminished arousal levels, it is characterized by a desynchronized, ‘wake-like’ EEG. This observation implies that reduced arousal states are not necessarily only defined by synchronous oscillatory activity. Using intracranial and surface EEG recordings in four independent data sets, we demonstrate that the 1/f spectral slope of the electrophysiological power spectrum, which reflects the non-oscillatory, scale-free component of neural activity, delineates wakefulness from propofol anesthesia, NREM and REM sleep. Critically, the spectral slope discriminates wakefulness from REM sleep solely based on the neurophysiological brain state. Taken together, our findings describe a common electrophysiological marker that tracks states of reduced arousal, including different sleep stages as well as anesthesia in humans., eLife digest Electroencephalogram (EEG for short) is a widespread technique that helps to monitor the electrical activity of the brain. In particular, it can be used to examine, recognize and compare different states of brain consciousness such as sleep, wakefulness or general anesthesia. Yet, during rapid eye movement sleep (the sleep phase in which dreaming occurs), the electrical activity of the brain is similar to the one recorded during wakefulness, making it difficult to distinguish these states based on EEG alone. EEG records brain activity in the shape of rhythmic waves whose frequency, shape and amplitude vary depending on the state of consciousness. In the EEG signal from the human brain, the higher frequency waves are weaker than the low-frequency waves: a measure known as spectral slope reflects the degree of this difference in the signal strength. Previous research suggests that spectral slope can be used to distinguish wakefulness from anesthesia and non-REM sleep. Here, Lendner et al. explored whether certain elements of the spectral slope could also discern wakefulness from all states of reduced arousal. EEG readings were taken from patients and volunteers who were awake, asleep or under anesthesia, using electrodes placed either on the scalp or into the brain. Lendner et al. found that the spectral slope could distinguish wakefulness from anesthesia, deep non-REM and REM sleep. The changes in the spectral slope during sleep could accurately track the degree of arousal with great temporal precision and across a wide range of time scales. This method means that states of consciousness can be spotted just from a scalp EEG. In the future, this approach could be embedded into the techniques used for monitoring sleep or anesthesia during operations; it could also be harnessed to monitor other low-response states, such as comas.

How do we remember emotional events? While emotion often leads to vivid recollection, the precision of emotional memories can be degraded, especially when discriminating among overlapping experiences in memory (i.e., pattern separation). Communication between the amygdala and the hippocampus has been proposed to support emotional memory, but the exact neural mechanisms remain unclear. Here, we used intracranial recordings in pre-surgical epilepsy patients to show that successful pattern separation of emotional stimuli is associated with theta band (3-7Hz)-coordinated bidirectional interactions between the amygdala and the hippocampus. In contrast, discrimination errors (i.e., failure to discriminate similar stimuli) were associated with alpha band (7-13Hz)-coordinated unidirectional influence from the amygdala to the hippocampus. These findings imply that alpha band synchrony may impair discrimination of similar emotional events via the amygdala-hippocampal directional coupling, which suggests a target for treatments of psychiatric conditions such as post-traumatic stress disorder, in which aversive experiences are often overgeneralized.

Older adults with mild cognitive impairment (MCI) are at-risk of developing dementia, particularly Alzheimer's disease. While some research suggests that alterations in sleep architecture may mediate cognitive decline, the nature and magnitude of changes to sleep macro- (sleep stages) and micro-architecture (electroencephalography (EEG) oscillations) in MCI is not yet clear. This study aimed to systematically review and meta-analyse case-control studies objectively measuring sleep in MCI. A systematic search was conducted using PubMed, Scopus, Web of Science, Embase and Psycinfo databases and after review, a total of 10 studies met inclusion criteria. Of these, all reported sleep macro-architecture and four reported micro-architecture outcomes. A combined total of 430 participants (209 with and 221 without MCI) underwent objective sleep assessments in the included full text articles. Findings show that compared to healthy controls, those with MCI have pronounced changes in sleep macro-architecture with greater wake after sleep onset, reduced total sleep time, lower sleep efficiency, longer sleep onset latency, longer rapid eye movement sleep (REM) latency, reduced REM sleep, greater N1 sleep, and worse severity of hypoxemia. Pooling of sleep micro-architecture EEG measures was not possible due to limited studies, however reduced spindles in non-REM sleep and greater EEG slowing in REM sleep were reported.

BACKGROUND: Several lines of research support associations between sleep and cognition in older adults. However, there is a paucity of data regarding sleep and cognition in nonagenarians and centenarians. AIMS: The current study examined self-reported sleep quantity and sleep quality in relation to hippocampal volume and cognition in adults aged 90 and older. METHODS: A total of 144 participants of The 90+ Study completed The Medical Outcomes Study sleep questionnaire. Participants reported subjective sleep duration in hours and three sleep quality factors: sleep problems, adequacy, and somnolence. Neuropsychological assessments of memory, global cognition, language, and executive function were completed, on average, 61 days from the questionnaire. Hippocampal volume on 3T MRI, adjusted for intracranial volume, was obtained in 82 participants. We performed multiple linear regressions, controlling for age, sex, education, sleep medication, and depression, to examine sleep characteristics in relation to hippocampal volume and cognitive performance in all subjects and then stratified by cognition. RESULTS: Sleep duration >8 hours was associated with lower scores in tests of global cognition, memory, and executive function compared to sleep duration of 7–8 hours when collapsing across cognitive status, but only with memory in cognitively impaired subjects, and not in cognitively normal subjects. DISCUSSION AND CONCLUSIONS: Long sleep duration is associated with poorer global cognition, memory, and executive function in the oldest-old, and is only associated with memory in cognitively impaired oldest-old. Additional research is necessary to determine if sleep duration is a risk factor or a result of poor cognition in advanced age.

How does a lack of sleep affect our brains? In contrast to the benefits of sleep, frameworks exploring the impact of sleep loss are relatively lacking. Importantly, the effects of sleep deprivation (SD) do not simply reflect the absence of sleep and the benefits attributed to it; rather, they reflect the consequences of several additional factors, including extended wakefulness. With a focus on neuroimaging studies, we review the consequences of SD on attention and working memory, positive and negative emotion, and hippocampal learning. We explore how this evidence informs our mechanistic understanding of the known changes in cognition and emotion associated with SD, and the insights it provides regarding clinical conditions associated with sleep disruption.

Older adults do not sleep as well as younger adults. Why? What alterations in sleep quantity and quality occur as we age, and are there functional consequences? What are the underlying neural mechanisms that explain age-related sleep disruption? This review tackles these questions. First, we describe canonical changes in human sleep quantity and quality in cognitively normal older adults. Second, we explore the underlying neurobiological mechanisms that may account for these human sleep alterations. Third, we consider the functional consequences of age-related sleep disruption, focusing on memory impairment as an exemplar. We conclude with a discussion of a still-debated question: do older adults simply need less sleep, or rather, are they unable to generate the sleep that they still need?

© The Author 2013. Published by Oxford University Press. All rights reserved. A hallmark feature of cognitive aging is a decline in the ability to form new memories. Parallel to these cognitive impairments are marked disruptions in sleep physiology. Despite recent evidence in young adults establishing a role for sleep spindles in restoring hippocampaldependent memory formation, the possibility that disrupted sleep physiology contributes to age-related decline in hippocampaldependent learning remains unknown. Here, we demonstrate that reduced prefrontal sleep spindles by over 40% in older adults statistically mediates the effects of old age on next day episodic learning, such that the degree of impaired episodic learning is explained by the extent of impoverished prefrontal sleep spindles. In addition, prefrontal spindles significantly predicted the magnitude of impaired next day hippocampal activation, thereby determining the influence of spindles on post-sleep learning capacity. These data support the hypothesis that disrupted sleep physiology contributes to age-related cognitive decline in later life, the consequence of which has significant treatment intervention potential.

Aging has independently been associated with regional brain atrophy, reduced slow wave activity (SWA) during non-rapid eye movement (NREM) sleep and impaired long-term retention of episodic memories. However, whether the interaction of these factors represents a neuropatholgical pathway associated with cognitive decline in later life remains unknown. We found that age- related medial prefrontal cortex (mPFC) gray-matter atrophy was associated with reduced NREM SWA in older adults, the extent to which statistically mediated the impairment of overnight sleep-dependent memory retention. Moreover, this memory impairment was further associated with persistent hippocampal activation and reduced task-related hippocampal-prefrontal cortex functional connectivity, potentially representing impoverished hippocampal-neocortical memory transformation. Together, these data support a model in which age-related mPFC atrophy diminishes SWA, the functional consequence of which is impaired long-term memory. Such findings suggest that sleep disruption in the elderly, mediated by structural brain changes, represents a contributing factor to age-related cognitive decline in later life.

Sleep disruption appears to be a core component of Alzheimer's disease (AD) and its pathophysiology. Signature abnormalities of sleep emerge before clinical onset of AD. Moreover, insufficient sleep facilitates accumulation of amyloid-β (Aβ), potentially triggering earlier cognitive decline and conversion to AD. Building on such findings, this review has four goals: evaluating (i) associations and plausible mechanisms linking non-rapid-eye-movement (NREM) sleep disruption, Aβ, and AD; (ii) a role for NREM sleep disruption as a novel factor linking cortical Aβ to impaired hippocampus-dependent memory consolidation; (iii) the potential diagnostic utility of NREM sleep disruption as a new biomarker of AD; and (iv) the possibility of sleep as a new treatment target in aging, affording preventative and therapeutic benefits.

The coupled interaction between slow-wave oscillations and sleep spindles during non-rapid-eye-movement (NREM) sleep has been proposed to support memory consolidation. However, little evidence in humans supports this theory. Moreover, whether such dynamic coupling is impaired as a consequence of brain aging in later life, contributing to cognitive and memory decline, is unknown. Combining electroencephalography (EEG), structural MRI, and sleep-dependent memory assessment, we addressed these questions in cognitively normal young and older adults. Directional cross-frequency coupling analyses demonstrated that the slow wave governs a precise temporal coordination of sleep spindles, the quality of which predicts overnight memory retention. Moreover, selective atrophy within the medial frontal cortex in older adults predicted a temporal dispersion of this slow wave-spindle coupling, impairing overnight memory consolidation and leading to forgetting. Prefrontal-dependent deficits in the spatiotemporal coordination of NREM sleep oscillations therefore represent one pathway explaining age-related memory decline.

One function of spatial attention is to enable goal-directed interactions with the environment through the allocation of neural resources to motivationally relevant parts of space. Studies have shown that responses are enhanced when spatial attention is predictively biased towards locations where significant events are expected to occur. Previous studies suggest that the ability to bias attention predictively is related to posterior cingulate cortex (PCC) activation [Small, D.M., et al., 2003. The posterior cingulate and medial prefrontal cortex mediate the anticipatory allocation of spatial attention. Neuroimage 18, 633–41]. Sleep deprivation (SD) impairs selective attention and reduces PCC activity [Thomas, M., et al., 2000. Neural basis of alertness and cognitive performance impairments during sleepiness. I. Effects of 24 h of sleep deprivation on waking human regional brain activity. J. Sleep Res. 9, 335–352]. Based on these findings, we hypothesized that SD would affect PCC function and alter the ability to predictively allocate spatial attention. Seven healthy, young adults underwent functional magnetic resonance imaging (fMRI) following normal rest and 34–36 h of SD while performing a task in which attention was shifted in response to peripheral targets preceded by spatially informative (valid), misleading (invalid), or uninformative (neutral) cues. When rested, but not when sleep-deprived, subjects responded more quickly to targets that followed valid cues than those after neutral or invalid cues. Brain activity during validly cued trials with a reaction time benefit was compared to activity in trials with no benefit. PCC activation was greater during trials with a reaction time benefit following normal rest. In contrast, following SD, reaction time benefits were associated with activation in the left intraparietal sulcus, a region associated with receptivity to stimuli at unexpected locations. These changes may render sleep-deprived individuals less able to anticipate the locations of upcoming events, and more susceptible to distraction by stimuli at irrelevant locations.

Independent evidence associates β-amyloid pathology with both non-rapid eye movement (NREM) sleep disruption and memory impairment in older adults. However, whether the influence of β-amyloid pathology on hippocampus-dependent memory is, in part, driven by impairments of NREM slow wave activity (SWA) and associated overnight memory consolidation is unknown. Here we show that β-amyloid burden in medial prefrontal cortex (mPFC) correlates significantly with the severity of impairment in NREM SWA generation. Moreover, reduced NREM SWA generation was further associated with impaired overnight memory consolidation and impoverished hippocampal-neocortical memory transformation. Furthermore, structural equation models revealed that the association between mPFC β-amyloid pathology and impaired hippocampus-dependent memory consolidation was not direct, but instead statistically depended on the intermediary factor of diminished NREM SWA. By linking β-amyloid pathology with impaired NREM SWA, these data implicate sleep disruption as a mechanistic pathway through which β-amyloid pathology may contribute to hippocampus-dependent cognitive decline in the elderly.

Whereas patients with Alzheimer's disease (AD) experience difficulties forming and retrieving memories, their memory impairments may also partially reflect an unrecognized dysfunction in sleep-dependent consolidation that normally stabilizes declarative memory storage across cortical areas. Patients with amnestic mild cognitive impairment (aMCI) exhibit circumscribed declarative memory deficits, and many eventually progress to an AD diagnosis. Whether sleep is disrupted in aMCI and whether sleep disruptions contribute to memory impairment is unknown. We measured sleep physiology and memory for two nights and found that aMCI patients had fewer stage-2 spindles than age-matched healthy adults. Furthermore, aMCI patients spent less time in slow-wave sleep and showed lower delta and theta power during sleep compared to controls. Slow-wave and theta activity during sleep appear to reflect important aspects of memory processing, as evening-to-morning change in declarative memory correlated with delta and theta power during intervening sleep in both groups. These results suggest that sleep changes in aMCI patients contribute to memory impairments by interfering with sleep-dependent memory consolidation. (JINS, 2012, 18, 490–500)

Sleep deprivation impairs many cognitive abilities, but these impairments can be reversed following a certain quantity and quality of sleep. The ability to inhibit responding is particularly susceptible to disruption following prolonged wakefulness. How recovery sleep alters brain activity, leading to improved performance on a variety of cognitive tasks remains unclear. This issue was examined in the current study using spectral analysis of electroencephalographic (EEG) data during sleep. These measures of sleep physiology were acquired after both normal sleep (NS) and recovery sleep (RS), and were related to measures of inhibitory control and concurrent brain activity. Subjects were nine young adults who underwent functional magnetic resonance imaging twice, after 9 hours of NS and after 10 hours of RS that followed 38 hours awake. A multiple regression model was used to examine differences between conditions in (1) EEG spectral power during sleep, (2) probability of successful inhibition in a go/no-go task, and (3) activation within a region of right prefrontal cortex during the task. Performance recovery, as indexed by reduced performance differences between conditions, was predicted by increased delta power and decreased sigma power in RS compared to NS. These EEG variables predicted most of the variance in inhibitory performance difference between conditions. Regressions also suggested that RS improved performance due to changes in brain function including prefrontal regions that resulted from delta rebound. We thus propose that slow waves, reflected in delta power during recovery sleep, act to restore brain function, thereby improving cognitive performance that entails response inhibition.

Background Evidence from laboratory and epidemiologic studies suggests that decreased sleep duration or quality may increase diabetes risk. We examined whether short or poor sleep is associated with glycemic control in African Americans with type 2 diabetes mellitus. Methods We conducted a cross-sectional study of volunteers with type 2 diabetes interviewed at the University of Chicago Hospitals, Chicago, Ill. The final analysis included 161 participants. Glycemic control was assessed by hemoglobin A 1c (HbA 1c ) level obtained from medical charts. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Perceived sleep debt was calculated as the difference between preferred and actual weekday sleep duration. Results The mean ± SD sleep duration was 6.0 ± 1.6 hours, and 71% of the participants were classified as having poor quality sleep (PSQI score >5). We excluded patients with sleep frequently disrupted by pain (n = 39). In patients without diabetic complications, glycemic control was associated with perceived sleep debt but not PSQI score. The predicted increase in HbA 1c level for a perceived sleep debt of 3 hours per night was 1.1% above the median. In patients with at least 1 complication, HbA 1c level was associated with PSQI score but not perceived sleep debt. The predicted increase in HbA 1c level for a 5-point increase in PSQI was 1.9% above the median. Conclusions In our sample, sleep duration and quality were significant predictors of HbA 1c , a key marker of glycemic control. Combined with existing evidence linking sleep loss to increased diabetes risk, these data suggest that optimizing sleep duration and quality should be tested as an intervention to improve glucose control in patients with type 2 diabetes.

Summary While the benefit of sleep after learning in offline consolidation is established [1], a role for sleep before learning in promoting initial memory formation remains largely uncharacterized. Existing theoretical frameworks speculate that accrued time awake, associated with ongoing experience, decreases learning capacity, while specific non-rapid-eye-movement (NREM) oscillations support restoration of learning ability [1,2]. Despite these model predictions, it remains untested whether episodic learning capacity remains stable across the day, or is progressively compromised by continued time awake. Furthermore, it is similarly unclear whether the presence, rather than the detrimental absence, of sleep restores efficient learning ability, and if so, what aspect(s) of sleep physiology support such reinstatement [3,4]. We have tested these related hypotheses, and report here a learning interaction, such that episodic encoding capacity deteriorates across a daytime waking interval, but sleep and associated NREM spindle oscillations restore efficient learning ability.