Are age and sex effects on sleep slow waves only a matter of electroencephalogram amplitude?

Partial normalization of hippocampal oscillatory activity during sleep in TgF344-AD rats coincides with increased cholinergic synapses at early-plaque stage of Alzheimer's disease

Sleep alterations are known to occur in Alzheimer's disease (AD), before cognitive symptoms become apparent, and are thought to play an important role in the pathophysiology of AD. However, knowledge on the extent of macro- and microstructural changes of sleep during early, presymptomatic stages of AD is limited. We hypothesize that Aβ-induced perturbations of neuronal activity disrupt this oscillatory activity during sleep at pre-plaque stages of AD. In this study, we aimed to assess hippocampal oscillatory activity during sleep at pre- and early-plaque stages of AD, by performing 24-hour hippocampal electrophysiological measurements in TgF344-AD rats and wildtype littermates at pre- and early-plaque stages of AD. To provide a mechanistic understanding, histological analysis was performed to quantify GABA-ergic, glutamatergic and cholinergic synapses. We observed a differential impact of AD on hippocampal activity during rapid eye movement (REM) and non-REM (NREM) sleep, in the absence of robust changes in circadian rhythm. TgF344-AD rats demonstrated increased duration of sharp wave-ripples during NREM sleep, irrespective of age. Interestingly, a significantly decreased theta-gamma coupling was observed in TgF344-AD rats, prior to amyloid plaque deposition, which was partially restored at the early-plaque stage. The partial recovery of hippocampal activity during REM sleep coincided with an increased number of cholinergic synapses in the hippocampus during the early-plaque stage in TgF344-AD rats, suggestive of basal forebrain cholinergic compensation mechanisms. The results from this study reveal early changes in hippocampal activity prior to Aβ plaque deposition in AD. In addition, the current findings imply an important role of the cholinergic system to compensate for AD-related network alterations, thereby partially restoring sleep architecture and hippocampal activity.

Unraveling the neurophysiological correlates of phase-specific enhancement of motor memory consolidation via slow-wave closed-loop targeted memory reactivation

Memory consolidation can be enhanced during sleep using targeted memory reactivation (TMR) and closed-loop (CL) acoustic stimulation on the up-phase of slow oscillations (SOs). Here, we test whether applying TMR at specific phases of the SOs (up vs. down vs. no reactivation) can influence the behavioral and neural correlates of motor memory consolidation in healthy young adults. Results show that up- (as compared to down-) state cueing results in greater performance improvement. Sleep electrophysiological data indicate that up- (as compared to down-) stimulated SOs exhibits higher amplitude and greater peak-nested sigma power. Task-related functional magnetic resonance images reveal that up-state cueing strengthens activity in - and segregation of - striato-motor and hippocampal networks; and that these modulations are related to the beneficial effect of TMR on sleep features and performance. Overall, these findings highlight the potential of CL-TMR to induce phase-specific modulations of motor performance, sleep oscillations and brain responses during motor memory consolidation.

Widespread decoupling of spindles and slow waves in temporal lobe epilepsy

OBJECTIVE

Memory impairment is common in people with temporal lobe epilepsy (TLE). Recent studies in healthy subjects showed a positive correlation between sleep spindles coupled to slow waves (SWs) and memory performance. We aimed to determine differences in spindle-SW coupling in TLE patients compared to healthy controls using combined high-density electroencephalography and polysomnography.

METHODS

The study population consisted of 20 patients (12 female, 36.5 ± 9.9 years old) with unilateral drug-resistant TLE (10 left temporal) and 20 age- and sex-matched controls (12 female, 31.2 ± 6.3 years old). Spindles (10-16 Hz, .5-3 s) and SWs (.5-4 Hz) were automatically detected during all N2 and N3 epochs using validated detectors. Coupling of spindles with SWs was defined as overlap between both detected events.

RESULTS

Coupled spindle-SW rates (per minute) were globally reduced in patients with TLE compared to healthy controls (median = .18 [interquartile range (IQR) = .08-.36] vs. .35 [IQR = .24-.46], p = .014, d = -.46). This reduction was also found for coupled fast spindle (12-16 Hz)-SW (.06 [IQR = .02-.13] vs. .18 [IQR = .07-.25], p = .013, d = -.46) and slow spindle (10-12 Hz)-SW rates (.11 [IQR = .04-.23] vs. .19 [IQR = .13-.27], p = .034, d = -.40). Within TLE patients, there was no local difference between the coupling rates in the lobe with the epileptic focus compared to the contralateral side (.09 [IQR = .02-.13] vs. .07 [IQR = .02-.13], p = .18). The effect size of the reduction was stronger in early than late sleep for both N2 and N3 sleep (early N2 d = -.50 vs. late N2 d = -.39; early N3 d = -.53 vs. late N3 d = -.47).

SIGNIFICANCE

Despite a focal epileptic generator, patients with unilateral TLE showed a widespread decoupling between sleep spindles and SWs that was most prominent in early sleep. As coupling was shown to be associated with neuropsychological performance in healthy people, this global decoupling may constitute one potential mechanism of poor memory performance in people with TLE.

Sex differences in electrical activity of the brain during sleep: a systematic review of electroencephalographic findings across the human lifespan

BACKGROUND

With the explosion of techniques for recording electrical brain activity, our recognition of neurodiversity has expanded significantly. Yet, uncertainty exists regarding sex differences in electrical activity during sleep and whether these differences, if any, are associated with social parameters. We synthesised existing evidence applying the PROGRESS-Plus framework, which captures social parameters that may influence brain activity and function.

METHODS

We searched five databases from inception to December 2024, and included English language peer-reviewed research examining sex differences in electrical activity during sleep in healthy participants. We performed risk of bias assessment following recommended criteria for observational studies. We reported results on sex differences by wave frequency (delta, theta, alpha, sigma, beta, and gamma) and waveforms (spindle and sawtooth), positioning results across age-related developmental stages. We created visualizations of results linking study quality and consideration of PROGRESS-Plus parameters, which facilitated certainty assessment.

RESULTS

Of the 2,783 unique citations identified, 28 studies with a total of 3,374 participants (47% male, age range 4-5 months to 101 years) were included in data synthesis. Evidence of high certainty reported no sex differences in alpha and delta relative power among participants in middle-to-late adulthood. Findings of moderate certainty suggest no sex differences in alpha power; and theta, sigma and beta relative power; and delta density. There is evidence of moderate certainty suggesting that female participants had a steeper delta wave slope and male participants had greater normalized delta power. Evidence that female participants have higher spindle power density is of low certainty. All other findings were regarded as very low in certainty. The PROGRESS-Plus parameters were rarely integrated into the methodology of studies included in this review.

CONCLUSION

Evidence on the topic of sex differences in sleep wave parameters is variable. It is possible that the reported results reflect unmeasured social parameters, instead of biological sex. Future research on sex differences in sleep should be discussed in relevance to functional or clinical outcomes. Development of uniform testing procedures across research settings is timely.

PROSPERO

CRD42022327644.

FUNDING

Canada Research Chairs (Neurological Disorders and Brain Health, CRC-2021-00074); UK Pilot Award for Global Brain Health Leaders (GBHI ALZ UK-23-971123).

Scalp and hippocampal sleep correlates of memory function in drug-resistant temporal lobe epilepsy

Seminal animal studies demonstrated the role of sleep oscillations such as cortical slow waves, thalamocortical spindles, and hippocampal ripples in memory consolidation. In humans, whether ripples are involved in sleep-related memory processes is less clear. Here, we explored the interactions between sleep oscillations (measured as traits) and general episodic memory abilities in 26 adults with drug-resistant temporal lobe epilepsy who performed scalp-intracranial electroencephalographic recordings and neuropsychological testing, including two analogous hippocampal-dependent verbal and nonverbal memory tasks. We explored the relationships between hemispheric scalp (spindles, slow waves) and hippocampal physiological and pathological oscillations (spindles, slow waves, ripples, and epileptic spikes) and material-specific memory function. To differentiate physiological from pathological ripples, we used multiple unbiased data-driven clustering approaches. At the individual level, we found material-specific cerebral lateralization effects (left-verbal memory, right-nonverbal memory) for all scalp spindles (rs > 0.51, ps < 0.01) and fast spindles (rs > 0.61, ps < 0.002). Hippocampal epileptic spikes and short pathological ripples, but not physiological oscillations, were negatively (rs > -0.59, ps < 0.01) associated with verbal learning and retention scores, with left lateralizing and antero-posterior effects. However, data-driven clustering failed to separate the ripple events into defined clusters. Correlation analyses with the resulting clusters revealed no meaningful or significant associations with the memory scores. Our results corroborate the role of scalp spindles in memory processes in patients with drug-resistant temporal lobe epilepsy. Yet, physiological and pathological ripples were not separable when using data-driven clustering, and thus our findings do not provide support for a role of sleep ripples as trait-like characteristics of general memory abilities in epilepsy.

The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study

Closed-loop auditory stimulation (CLAS) is a brain modulation technique in which sounds are timed to enhance or disrupt endogenous neurophysiological events. CLAS of slow oscillation up-states in sleep is becoming a popular tool to study and enhance sleep's functions, as it increases slow oscillations, evokes sleep spindles and enhances memory consolidation of certain tasks. However, few studies have examined the specific neurophysiological mechanisms involved in CLAS, in part because of practical limitations to available tools. To evaluate evidence for possible models of how sound stimulation during brain up-states alters brain activity, we simultaneously recorded electro- and magnetoencephalography in human participants who received auditory stimulation across sleep stages. We conducted a series of analyses that test different models of pathways through which CLAS of slow oscillations may affect widespread neural activity that have been suggested in literature, using spatial information, timing and phase relationships in the source-localized magnetoencephalography data. The results suggest that auditory information reaches ventral frontal lobe areas via non-lemniscal pathways. From there, a slow oscillation is created and propagated. We demonstrate that while the state of excitability of tissue in auditory cortex and frontal ventral regions shows some synchrony with the electroencephalography (EEG)-recorded up-states that are commonly used for CLAS, it is the state of ventral frontal regions that is most critical for slow oscillation generation. Our findings advance models of how CLAS leads to enhancement of slow oscillations, sleep spindles and associated cognitive benefits and offer insight into how the effectiveness of brain stimulation techniques can be improved.

Targeted memory reactivation during post-learning sleep does not enhance motor memory consolidation in older adults

Targeted memory reactivation (TMR) during sleep enhances memory consolidation in young adults by modulating electrophysiological markers of neuroplasticity. Interestingly, older adults exhibit deficits in motor memory consolidation, an impairment that has been linked to age-related degradations in the same sleep features sensitive to TMR. We hypothesised that TMR would enhance consolidation in older adults via the modulation of these markers. A total of 17 older participants were trained on a motor task involving two auditory-cued sequences. During a post-learning nap, two auditory cues were played: one associated to a learned (i.e., reactivated) sequence and one control. Performance during two delayed re-tests did not differ between reactivated and non-reactivated sequences. Moreover, both associated and control sounds modulated brain responses, yet there were no consistent differences between the auditory cue types. Our results collectively demonstrate that older adults do not benefit from specific reactivation of a motor memory trace by an associated auditory cue during post-learning sleep. Based on previous research, it is possible that auditory stimulation during post-learning sleep could have boosted motor memory consolidation in a non-specific manner.

Medial temporal lobe functional network architecture supports sleep-related emotional memory processing in older adults

Memory consolidation occurs via reactivation of a hippocampal index during non-rapid eye movement slow-wave sleep (NREM SWS) which binds attributes of an experience existing within cortical modules. For memories containing emotional content, hippocampal-amygdala dynamics facilitate consolidation over a sleep bout. This study tested if modularity and centrality-graph theoretical measures that index the level of segregation/integration in a system and the relative import of its nodes-map onto central tenets of memory consolidation theory and sleep-related processing. Findings indicate that greater network integration is tied to overnight emotional memory retention via NREM SWS expression. Greater hippocampal and amygdala influence over network organization supports emotional memory retention, and hippocampal or amygdala control over information flow are differentially associated with distinct stages of memory processing. These centrality measures are also tied to the local expression and coupling of key sleep oscillations tied to sleep-dependent memory consolidation. These findings suggest that measures of intrinsic network connectivity may predict the capacity of brain functional networks to acquire, consolidate, and retrieve emotional memories.

The Interactive Role of Sleep and Circadian Rhythms in Episodic Memory in Older Adults

Adequate sleep is essential for healthy physical, emotional, and cognitive functioning, including memory. However, sleep ability worsens with increasing age. Older adults on average have shorter sleep durations and more disrupted sleep compared with younger adults. Age-related sleep changes are thought to contribute to age-related deficits in episodic memory. Nonetheless, the nature of the relationship between sleep and episodic memory deficits in older adults is still unclear. Further complicating this relationship are age-related changes in circadian rhythms such as the shift in chronotype toward morningness and decreased circadian stability, which may influence memory abilities as well. Most sleep and cognitive aging studies do not account for circadian factors, making it unclear whether age-related and sleep-related episodic memory deficits are partly driven by interactions with circadian rhythms. This review will focus on age-related changes in sleep and circadian rhythms and evidence that these factors interact to affect episodic memory, specifically encoding and retrieval. Open questions, methodological considerations, and clinical implications for diagnosis and monitoring of age-related memory impairments are discussed.

Sleep slow waves' negative-to-positive-phase transition: a marker of cognitive and apneic status in aging

The sleep slow-wave (SW) transition between negative and positive phases is thought to mirror synaptic strength and likely depends on brain health. This transition shows significant age-related changes but has not been investigated in pathological aging. The present study aimed at comparing the transition speed and other characteristics of SW between older adults with amnestic mild cognitive impairment (aMCI) and cognitively normal (CN) controls with and without obstructive sleep apnea (OSA). We also examined the association of SW characteristics with the longitudinal changes of episodic memory and executive functions and the degree of subjective cognitive complaints. aMCI (no/mild OSA = 17; OSA = 15) and CN (no/mild OSA = 20; OSA = 17) participants underwent a night of polysomnography and a neuropsychological evaluation at baseline and 18 months later. Participants with aMCI had a significantly slower SW negative-to-positive-phase transition speed and a higher proportion of SW that are "slow-switchers" than CN participants. These SW measures in the frontal region were significantly correlated with memory decline and cognitive complaints in aMCI and cognitive improvements in CN participants. The transition speed of the SW that are "fast-switchers" was significantly slower in OSA compared to no or mild obstructive sleep apnea participants. The SW transition-related metrics showed opposite correlations with the longitudinal episodic memory changes depending on the participants' cognitive status. These relationships were particularly strong in participants with aMCI. As the changes of the SW transition-related metrics in pathological aging might reflect synaptic alterations, future studies should investigate whether these new metrics covary with biomarker levels of synaptic integrity in this population.

Frontal grey matter microstructure is associated with sleep slow waves characteristics in late midlife

STUDY OBJECTIVES

The ability to generate slow waves (SW) during non-rapid eye movement (NREM) sleep decreases as early as the 5th decade of life, predominantly over frontal regions. This decrease may concern prominently SW characterized by a fast switch from hyperpolarized to depolarized, or down-to-up, state. Yet, the relationship between these fast and slow switcher SW and cerebral microstructure in ageing is not established.

METHODS

We recorded habitual sleep under EEG in 99 healthy late midlife individuals (mean age = 59.3 ± 5.3 years; 68 women) and extracted SW parameters (density, amplitude, frequency) for all SW as well as according to their switcher type (slow vs. fast). We further used neurite orientation dispersion and density imaging (NODDI) to assess microstructural integrity over a frontal grey matter region of interest (ROI).

RESULTS

In statistical models adjusted for age, sex, and sleep duration, we found that a lower SW density, particularly for fast switcher SW, was associated with a reduced orientation dispersion of neurites in the frontal ROI (p = 0.018, R2β* = 0.06). In addition, overall SW frequency was positively associated with neurite density (p = 0.03, R2β* = 0.05). By contrast, we found no significant relationships between SW amplitude and NODDI metrics.

CONCLUSIONS

Our findings suggest that the complexity of neurite organization contributes specifically to the rate of fast switcher SW occurrence in healthy middle-aged individuals, corroborating slow and fast switcher SW as distinct types of SW. They further suggest that the density of frontal neurites plays a key role for neural synchronization during sleep.

TRIAL REGISTRATION NUMBER

EudraCT 2016-001436-35.

Sleep-dependent memory consolidation in breast cancer: Use of a virtual reality prospective memory task

Background

Previous studies have revealed both sleep alterations and prospective memory (PM) impairments in breast cancer (BC) patients. PM refers to memory of intended actions and is crucial for daily living tasks and treatment compliance. As sleep is known to favor memory consolidation, one may expect that changes in sleep quality related to BC would have an impact on PM performance. This study aimed at assessing sleep-dependent consolidation of intentions using an ecological, virtual reality-based PM task in BC patients not treated with chemotherapy.

Materials and methods

Thirty-seven early stages BC patients and 21 healthy controls (HC) participated in this study. PM was assessed using a virtual reality task, during which participants learnt a list of intentions and recalled them after a retention interval filled with a day awake or a night of sleep monitored by polysomnography. Sleep spindles and slow waves, brain oscillations involved in sleep-dependent memory consolidation, were quantified automatically using the Aseega software (Physip). Subjective sleep disturbances and markers of quality of life (psychological distress, fatigue, and well-being) were assessed by questionnaires.

Results

Greater PM performance was observed after sleep than after an equivalent period of daytime wakefulness for both groups (HC and BC). PM performance after sleep did not differ significantly between groups. Yet, BC patients reported greater sleep disturbances than HC which were related with poorer intentions retrieval, greater psychological distress, fatigue and poorer well-being. The frequency of spindles was higher and the amplitude of slow waves lower in BC patients compared to HC. However, no significant association was observed between polysomnography parameters and PM scores in the whole sample of participants.

Conclusion

Although subtle changes in brain oscillations involved in sleep-dependent memory consolidation were observed, these changes did not significantly impair overnight PM consolidation in BC patients. Nevertheless, poorer PM performance was associated with greater sleep complaints which in turn were related to poorer quality of life. Overall, these data suggest that sleep-dependent PM consolidation mechanisms are not altered in early stages BC patients not treated with chemotherapy. Further investigations are needed to understand the association between markers of quality of life and sleep-dependent memory consolidation.

Timely coupling of sleep spindles and slow waves is linked to early amyloid-β burden and predicts memory decline

Sleep alteration is a hallmark of ageing and emerges as a risk factor for Alzheimer’s disease (AD). While the fine-tuned coalescence of sleep microstructure elements may influence age-related cognitive trajectories, its association with AD processes is not fully established. Here, we investigated whether the coupling of spindles and slow waves (SW) is associated with early amyloid-β (Aβ) brain burden, a hallmark of AD neuropathology, and cognitive change over 2 years in 100 healthy individuals in late-midlife (50–70 years; 68 women). We found that, in contrast to other sleep metrics, earlier occurrence of spindles on slow-depolarisation SW is associated with higher medial prefrontal cortex Aβ burden (p=0.014, r²_β*=0.06) and is predictive of greater longitudinal memory decline in a large subsample (p=0.032, r²_β*=0.07, N=66). These findings unravel early links between sleep, AD-related processes, and cognition and suggest that altered coupling of sleep microstructure elements, key to its mnesic function, contributes to poorer brain and cognitive trajectories in ageing.

Sleep EEG-Based Approach to Detect Mild Cognitive Impairment

Mild Cognitive Impairment (MCI) is an early stage of dementia, which may lead to Alzheimer's disease (AD) in older adults. Therefore, early detection of MCI and implementation of treatment and intervention can effectively slow down or even inhibit the progression of the disease, thus minimizing the risk of AD. Currently, we know that published work relies on an analysis of awake EEG recordings. However, recent studies have suggested that changes in the structure of sleep may lead to cognitive decline. In this work, we propose a sleep EEG-based method for MCI detection, extracting specific features of sleep to characterize neuroregulatory deficit emergent with MCI. This study analyzed the EEGs of 40 subjects (20 MCI, 20 HC) with the developed algorithm. We extracted sleep slow waves and spindles features, combined with spectral and complexity features from sleep EEG, and used the SVM classifier and GRU network to identify MCI. In addition, the classification results of different feature sets (including with sleep features from sleep EEG and without sleep features from awake EEG) and different classification methods were evaluated. Finally, the MCI classification accuracy of the GRU network based on features extracted from sleep EEG was the highest, reaching 93.46%. Experimental results show that compared with the awake EEG, sleep EEG can provide more useful information to distinguish between MCI and HC. This method can not only improve the classification performance but also facilitate the early intervention of AD.

Sleep Measurements in Women

Sleep in women and men have been studied in several studies with higher prevalence of sleep complaints in women compared with men. Several factors can affect sleep and could be argued to contribute to sex and gender differences in general sleep. There are no differences in guidelines when measuring sleep in women but several sleep assessment tools have been validated or compared between sexes. Because there is still a lack of knowledge on sleep measurements in women, the present review aimed to produce an overview of the current knowledge of objective and subjective sleep measurements in women.