Precise Slow Oscillation-Spindle Coupling Promotes Memory Consolidation in Younger and Older Adults

Oscillatory-Quality of sleep spindles links brain state with sleep regulation and function

Here, we characterized the dynamics of sleep spindles, focusing on their damping, which we estimated using a metric called oscillatory-Quality (o-Quality), derived by fitting an autoregressive model to electrophysiological signals, recorded from the cortex in mice. The o-Quality of sleep spindles correlates weakly with their amplitude, shows marked laminar differences and regional topography across cortical regions, reflects the level of synchrony within and between cortical networks, is strongly modulated by sleep-wake history, reflects the degree of sensory disconnection, and correlates with the strength of coupling between spindles and slow waves. As most spindle events are highly localized and not detectable with conventional low-density recording approaches, o-Quality thus emerges as a valuable metric that allows us to infer the spread and dynamics of spindle activity across the brain and directly links their spatiotemporal dynamics with local and global regulation of brain states, sleep regulation, and function.

Sleep Consolidation Potentiates Sensorimotor Adaptation

Contrary to its well-established role in declarative learning, the impact of sleep on motor memory consolidation remains a subject of debate. Current literature suggests that while motor skill learning benefits from sleep, consolidation of sensorimotor adaptation (SMA) depends solely on the passage of time. This has led to the proposal that SMA may be an exception to other types of memories. Here, we addressed this ongoing controversy in humans through three comprehensive experiments using the visuomotor adaptation paradigm (N = 290, 150 females). In Experiment 1, we investigated the impact of sleep on memory retention when the temporal gap between training and sleep was not controlled. In line with the previous literature, we found that memory consolidates with the passage of time. In Experiment 2, we used an anterograde interference protocol to determine the time window during which SMA memory is most fragile and, thus, potentially most sensitive to sleep intervention. Our results show that memory is most vulnerable during the initial hour post-training. Building on this insight, in Experiment 3, we investigated the impact of sleep when it coincided with the critical first hour of memory consolidation. This manipulation unveiled a benefit of sleep (30% memory enhancement) alongside an increase in spindle density and spindle-SO coupling during NREM sleep, two well-established neural markers of sleep consolidation. Our findings reconcile seemingly conflicting perspectives on the active role of sleep in motor learning and point to common mechanisms at the basis of memory formation.

Does slow oscillation-spindle coupling contribute to sleep-dependent memory consolidation? A Bayesian meta-analysis

The active system consolidation theory suggests that information transfer between the hippocampus and cortex during sleep underlies memory consolidation. Neural oscillations during sleep, including the temporal coupling between slow oscillations (SO) and sleep spindles (SP), may play a mechanistic role in memory consolidation. However, differences in analytical approaches and the presence of physiological and behavioral moderators have led to inconsistent conclusions. This meta-analysis, comprising 23 studies and 297 effect sizes, focused on four standard phase-amplitude coupling measures including coupling phase, strength, percentage, and SP amplitude, and their relationship with memory retention. We developed a standardized approach to incorporate non-normal circular-linear correlations. We found strong evidence supporting that precise and strong SO-fast SP coupling in the frontal lobe predicts memory consolidation. The strength of this association is mediated by memory type, aging, and dynamic spatio-temporal features, including SP frequency and cortical topography. In conclusion, SO-SP coupling should be considered as a general physiological mechanism for memory consolidation.

Spindle-slow wave coupling and problem-solving skills: impact of age

We examined how aging affects the role of sleep in the consolidation of newly learned cognitive strategies. Forty healthy young adults (20-35 years) and 30 healthy older adults (60-85 years) were included. Participants were trained on the Tower of Hanoi (ToH) task, then, half of each age group were assigned to either the 90-minute nap condition, or stayed awake, before retesting. The temporal co-occurrence between slow waves (SW) and sleep spindles (SP) during non-rapid eye movement sleep was examined as a function of age in relation to memory consolidation of problem-solving skills. We found that despite intact learning, older adults derived a reduced benefit of sleep for problem-solving skills relative to younger adults. As expected, the percentage of coupled spindles was lower in older compared to younger individuals from control to testing sessions. Furthermore, coupled spindles in young adults were more strongly coupled to the SW upstate compared to older individuals. Coupled spindles in older individuals were lower in amplitude (mean area under the curve; μV) compared to the young group. Lastly, there was a significant relationship between offline gains in accuracy on the ToH and percent change of spindles coupled to the upstate of the slow wave in older, but not younger adults. Multiple regression revealed that age accounted for differences in offline gains in accuracy, as did spindle coupling during the upstate. These results suggest that with aging, spindle-slow wave coupling decreases. However, the degree of the preservation of coupling with age correlates with the extent of problem-solving skill consolidation during sleep.

REM Sleep Preserves Affective Response to Social Stress-Experimental Study

Sleep's contribution to affective regulation is insufficiently understood. Previous human research has focused on memorizing or rating affective pictures and less on physiological affective responsivity. This may result in overlapping definitions of affective and declarative memories and inconsistent deductions for how rapid eye movement sleep (REMS) and slow-wave sleep (SWS) are involved. Literature associates REMS theta (4-8 Hz) activity with emotional memory processing, but its contribution to social stress habituation is unknown. Applying selective sleep stage suppression and oscillatory analyses, we investigated how sleep modulated affective adaptation toward social stress and retention of neutral declarative memories. Native Finnish participants (N = 29; age, M = 25.8 years) were allocated to REMS or SWS suppression conditions. We measured physiological (skin conductance response, SCR) and subjective stress response and declarative memory retrieval thrice: before laboratory night, the next morning, and after 3 d. Linear mixed models were applied to test the effects of condition and sleep parameters on emotional responsivity and memory retrieval. Greater overnight increase in SCR toward the stressor emerged after suppressed SWS (intact REMS) relative to suppressed REMS (20.1% vs 6.1%; p = 0.016). The overnight SCR increase was positively associated with accumulated REMS theta energy irrespective of the condition (r = 0.601; p = 0.002). Subjectively rated affective response and declarative memory recall were comparable between the conditions. The contributions of REMS and SWS to habituation of social stress are distinct. REMS theta activity proposedly facilitates the consolidation of autonomic affective responses. Declarative memory consolidation may not have greater dependence on intact SWS relative to intact REMS.

Effects of evening smartphone use on sleep and declarative memory consolidation in male adolescents and young adults

Exposure to short-wavelength light before bedtime is known to disrupt nocturnal melatonin secretion and can impair subsequent sleep. However, while it has been demonstrated that older adults are less affected by short-wavelength light, there is limited research exploring differences between adolescents and young adults. Furthermore, it remains unclear whether the effects of evening short-wavelength light on sleep architecture extend to sleep-related processes, such as declarative memory consolidation. Here, we recorded polysomnography from 33 male adolescents (15.42 ± 0.97 years) and 35 male young adults (21.51 ± 2.06 years) in a within-subject design during three different nights to investigate the impact of reading for 90 min either on a smartphone with or without a blue-light filter or from a printed book. We measured subjective sleepiness, melatonin secretion, sleep physiology and sleep-dependent memory consolidation. While subjective sleepiness remained unaffected, we observed a significant melatonin attenuation effect in both age groups immediately after reading on the smartphone without a blue-light filter. Interestingly, adolescents fully recovered from the melatonin attenuation in the following 50 min before bedtime, whereas adults still, at bedtime, exhibited significantly reduced melatonin levels. Sleep-dependent memory consolidation and the coupling between sleep spindles and slow oscillations were not affected by short-wavelength light in both age groups. Nevertheless, adults showed a reduction in N3 sleep during the first night quarter. In summary, avoiding smartphone use in the last hour before bedtime is advisable for adolescents and young adults to prevent sleep disturbances. Our research empirically supports general sleep hygiene advice and can inform future recommendations regarding the use of smartphones and other screen-based devices before bedtime.

Episodic long-term memory formation during slow-wave sleep

We are unresponsive during slow-wave sleep but continue monitoring external events for survival. Our brain wakens us when danger is imminent. If events are non-threatening, our brain might store them for later consideration to improve decision-making. To test this hypothesis, we examined whether novel vocabulary consisting of simultaneously played pseudowords and translation words are encoded/stored during sleep, and which neural-electrical events facilitate encoding/storage. An algorithm for brain-state-dependent stimulation selectively targeted word pairs to slow-wave peaks or troughs. Retrieval tests were given 12 and 36 hr later. These tests required decisions regarding the semantic category of previously sleep-played pseudowords. The sleep-played vocabulary influenced awake decision-making 36 hr later, if targeted to troughs. The words' linguistic processing raised neural complexity. The words' semantic-associative encoding was supported by increased theta power during the ensuing peak. Fast-spindle power ramped up during a second peak likely aiding consolidation. Hence, new vocabulary played during slow-wave sleep was stored and influenced decision-making days later.

Comparing targeted memory reactivation during slow wave sleep and sleep stage 2

Sleep facilitates declarative memory consolidation, which is assumed to rely on the reactivation of newly encoded memories orchestrated by the temporal interplay of slow oscillations (SO), fast spindles and ripples. SO as well as the number of spindles coupled to SO are more frequent during slow wave sleep (SWS) compared to lighter sleep stage 2 (S2). But, it is unclear whether memory reactivation is more effective during SWS than during S2. To test this question, we applied Targeted Memory Reactivation (TMR) in a declarative memory design by presenting learning-associated sound cues during SWS vs. S2 in a counterbalanced within-subject design. Contrary to our hypothesis, memory performance was not significantly better when cues were presented during SWS. Event-related potential (ERP) amplitudes were significantly higher for cues presented during SWS than S2, and the density of SO and SO-spindle complexes was generally higher during SWS than during S2. Whereas SO density increased during and after the TMR period, SO-spindle complexes decreased. None of the parameters were associated with memory performance. These findings suggest that the efficacy of TMR does not depend on whether it is administered during SWS or S2, despite differential processing of memory cues in these sleep stages.

Coupled sleep rhythms for memory consolidation

How do passing moments turn into lasting memories? Sheltered from external tasks and distractions, sleep constitutes an optimal state for the brain to reprocess and consolidate previous experiences. Recent work suggests that consolidation is governed by the intricate interaction of slow oscillations (SOs), spindles, and ripples - electrophysiological sleep rhythms that orchestrate neuronal processing and communication within and across memory circuits. This review describes how sequential SO-spindle-ripple coupling provides a temporally and spatially fine-tuned mechanism to selectively strengthen target memories across hippocampal and cortical networks. Coupled sleep rhythms might be harnessed not only to enhance overnight memory retention, but also to combat memory decline associated with healthy ageing and neurodegenerative diseases.

Individualized temporal patterns dominate cortical upstate and sleep depth in driving human sleep spindle timing

Sleep spindles are critical for memory consolidation and strongly linked to neurological disease and aging. Despite their significance, the relative influences of factors like sleep depth, cortical up/down states, and spindle temporal patterns on individual spindle production remain poorly understood. Moreover, spindle temporal patterns are typically ignored in favor of an average spindle rate. Here, we analyze spindle dynamics in 1008 participants from the Multi-Ethnic Study of Atherosclerosis using a point process framework. Results reveal fingerprint-like temporal patterns, characterized by a refractory period followed by a period of increased spindle activity, which are highly individualized yet consistent night-to-night. We observe increased timing variability with age and distinct gender/age differences. Strikingly, and in contrast to the prevailing notion, individualized spindle patterns are the dominant determinant of spindle timing, accounting for over 70% of the statistical deviance explained by all of the factors we assessed, surpassing the contribution of slow oscillation (SO) phase (~14%) and sleep depth (~16%). Furthermore, we show spindle/SO coupling dynamics with sleep depth are preserved across age, with a global negative shift towards the SO rising slope. These findings offer novel mechanistic insights into spindle dynamics with direct experimental implications and applications to individualized electroencephalography biomarker identification.

A classification-based generative approach to selective targeting of global slow oscillations during sleep

Background

Given sleep's crucial role in health and cognition, numerous sleep-based brain interventions are being developed, aiming to enhance cognitive function, particularly memory consolidation, by improving sleep. Research has shown that Transcranial Alternating Current Stimulation (tACS) during sleep can enhance memory performance, especially when used in a closed-loop (cl-tACS) mode that coordinates with sleep slow oscillations (SOs, 0.5-1.5Hz). However, sleep tACS research is characterized by mixed results across individuals, which are often attributed to individual variability.

Objective/Hypothesis

This study targets a specific type of SOs, widespread on the electrode manifold in a short delay ("global SOs"), due to their close relationship with long-term memory consolidation. We propose a model-based approach to optimize cl-tACS paradigms, targeting global SOs not only by considering their temporal properties but also their spatial profile.

Methods

We introduce selective targeting of global SOs using a classification-based approach. We first estimate the current elicited by various stimulation paradigms, and optimize parameters to match currents found in natural sleep during a global SO. Then, we employ an ensemble classifier trained on sleep data to identify effective paradigms. Finally, the best stimulation protocol is determined based on classification performance.

Results

Our study introduces a model-driven cl-tACS approach that specifically targets global SOs, with the potential to extend to other brain dynamics. This method establishes a connection between brain dynamics and stimulation optimization.

Conclusion

Our research presents a novel approach to optimize cl-tACS during sleep, with a focus on targeting global SOs. This approach holds promise for improving cl-tACS not only for global SOs but also for other physiological events, benefiting both research and clinical applications in sleep and cognition.

Linking brain structure, cognition, and sleep: insights from clinical data

STUDY OBJECTIVES

To use relatively noisy routinely collected clinical data (brain magnetic resonance imaging (MRI) data, clinical polysomnography (PSG) recordings, and neuropsychological testing), to investigate hypothesis-driven and data-driven relationships between brain physiology, structure, and cognition.

METHODS

We analyzed data from patients with clinical PSG, brain MRI, and neuropsychological evaluations. SynthSeg, a neural network-based tool, provided high-quality segmentations despite noise. A priori hypotheses explored associations between brain function (measured by PSG) and brain structure (measured by MRI). Associations with cognitive scores and dementia status were studied. An exploratory data-driven approach investigated age-structure-physiology-cognition links.

RESULTS

Six hundred and twenty-three patients with sleep PSG and brain MRI data were included in this study; 160 with cognitive evaluations. Three hundred and forty-two participants (55%) were female, and age interquartile range was 52 to 69 years. Thirty-six individuals were diagnosed with dementia, 71 with mild cognitive impairment, and 326 with major depression. One hundred and fifteen individuals were evaluated for insomnia and 138 participants had an apnea-hypopnea index equal to or greater than 15. Total PSG delta power correlated positively with frontal lobe/thalamic volumes, and sleep spindle density with thalamic volume. rapid eye movement (REM) duration and amygdala volume were positively associated with cognition. Patients with dementia showed significant differences in five brain structure volumes. REM duration, spindle, and slow-oscillation features had strong associations with cognition and brain structure volumes. PSG and MRI features in combination predicted chronological age (R2 = 0.67) and cognition (R2 = 0.40).

CONCLUSIONS

Routine clinical data holds extended value in understanding and even clinically using brain-sleep-cognition relationships.

Improving the detection of sleep slow oscillations in electroencephalographic data

Study objectives

We aimed to build a tool which facilitates manual labeling of sleep slow oscillations (SOs) and evaluate the performance of traditional sleep SO detection algorithms on such a manually labeled data set. We sought to develop improved methods for SO detection.

Method

SOs in polysomnographic recordings acquired during nap time from ten older adults were manually labeled using a custom built graphical user interface tool. Three automatic SO detection algorithms previously used in the literature were evaluated on this data set. Additional machine learning and deep learning algorithms were trained on the manually labeled data set.

Results

Our custom built tool significantly decreased the time needed for manual labeling, allowing us to manually inspect 96,277 potential SO events. The three automatic SO detection algorithms showed relatively low accuracy (max. 61.08%), but results were qualitatively similar, with SO density and amplitude increasing with sleep depth. The machine learning and deep learning algorithms showed higher accuracy (best: 99.20%) while maintaining a low prediction time.

Conclusions

Accurate detection of SO events is important for investigating their role in memory consolidation. In this context, our tool and proposed methods can provide significant help in identifying these events.

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.

Slow oscillation-spindle cross-frequency coupling predicts overnight declarative memory consolidation in older adults

Cross-frequency coupling (CFC) between brain oscillations during non-rapid-eye-movement (NREM) sleep (e.g. slow oscillations [SO] and spindles) may be a neural mechanism of overnight memory consolidation. Declines in CFC across the lifespan might accompany coinciding memory problems with ageing. However, there are few reports of CFC changes during sleep after learning in older adults, controlling for baseline effects. Our objective was to examine NREM CFC in healthy older adults, with an emphasis on spindle activity and SOs from frontal electroencephalogram (EEG), during a learning night after a declarative learning task, as compared to a baseline night without learning. Twenty-five older adults (M [SD] age = 69.12 [5.53] years; 64% female) completed a two-night study, with a pre- and post-sleep word-pair associates task completed on the second night. SO-spindle coupling strength and a measure of coupling phase distance from the SO up-state were both examined for between-night differences and associations with memory consolidation. Coupling strength and phase distance from the up-state peak were both stable between nights. Change in coupling strength between nights was not associated with memory consolidation, but a shift in coupling phase towards (vs. away from) the up-state peak after learning predicted better memory consolidation. Also, an exploratory interaction model suggested that associations between coupling phase closer to the up-state peak and memory consolidation may be moderated by higher (vs. lower) coupling strength. This study supports a role for NREM CFC in sleep-related memory consolidation in older adults.

Association of spermidine blood levels with microstructure of sleep-implications from a population-based study

Deteriorations in slow wave sleep (SWS) have been linked to brain aging and Alzheimer's disease (AD), possibly due to its key role in clearance of amyloid-beta and tau (Aß/tau), two pathogenic hallmarks of AD. Spermidine administration has been shown to improve sleep quality in animal models. So far, the association between spermidine levels in humans and parameters of SWS physiology are unknown but may be valuable for therapeutic strategies. Data from 216 participants (age range 50-81 years) of the population-based Study of Health in Pomerania TREND were included in our analysis. We investigated associations between spermidine plasma levels, key parameters of sleep macroarchitecture and microarchitecture that were previously associated with AD pathology, and brain health measured via a marker of structural brain atrophy (AD score). Higher spermidine levels were significantly associated with lower coupling between slow oscillations and spindle activity. No association was evident for SWS, slow oscillatory, and spindle activity throughout non-rapid eye movement sleep. Furthermore, elevated spermidine blood levels were significantly associated with a higher AD score, while sleep markers revealed no association with AD score. The association between higher spermidine levels and brain health was not mediated by coupling between slow oscillations and spindle activity. We report that higher spermidine blood levels are associated not only with deteriorated brain health but also with less advantageous markers of sleep quality in older adults. Future studies need to evaluate whether sleep, spermidine, and Aß/tau deposition are interrelated and whether sleep may play a mediating role.

A visual paired associate learning (vPAL) paradigm to study memory consolidation during sleep

Sleep improves the consolidation and long-term stability of newly formed memories and associations. Most research on human declarative memory and its consolidation during sleep uses word-pair associations requiring exhaustive learning. In the present study, we present the visual paired association learning (vPAL) paradigm, in which participants learn new associations between images of celebrities and animals. The vPAL is based on a one-shot exposure that resembles learning in natural conditions. We tested if vPAL can reveal a role for sleep in memory consolidation by assessing the specificity of memory recognition, and the cued recall performance, before and after sleep. We found that a daytime nap improved the stability of recognition memory and discrimination abilities compared to identical intervals of wakefulness. By contrast, cued recall of associations did not exhibit significant sleep-dependent effects. High-density electroencephalography during naps further revealed an association between sleep spindle density and stability of recognition memory. Thus, the vPAL paradigm opens new avenues for future research on sleep and memory consolidation across ages and heterogeneous populations in health and disease.

Mapping sleep's oscillatory events as a biomarker of Alzheimer's disease

INTRODUCTION

Memory-associated neural circuits produce oscillatory events including theta bursts (TBs), sleep spindles (SPs), and slow waves (SWs) in sleep electroencephalography (EEG). Changes in the "coupling" of these events may indicate early Alzheimer's disease (AD) pathogenesis.

METHODS

We analyzed 205 aging adults using single-channel sleep EEG, cerebrospinal fluid (CSF) AD biomarkers, and Clinical Dementia Rating® (CDR®) scale. We mapped SW-TB and SW-SP neural circuit coupling precision to amyloid positivity, cognitive impairment, and CSF AD biomarkers.

RESULTS

Cognitive impairment correlated with lower TB spectral power in SW-TB coupling. Cognitively unimpaired, amyloid positive individuals demonstrated lower precision in SW-TB and SW-SP coupling compared to amyloid negative individuals. Significant biomarker correlations were found in oscillatory event coupling with CSF Aβ42 /Aβ40 , phosphorylated- tau181 , and total-tau.

DISCUSSION

Sleep-dependent memory processing integrity in neural circuits can be measured for both SW-TB and SW-SP coupling. This breakdown associates with amyloid positivity, increased AD pathology, and cognitive impairment.

HIGHLIGHTS

At-home sleep EEG is a potential biomarker of neural circuits linked to memory. Circuit precision is associated with amyloid positivity in asymptomatic aging adults. Levels of CSF amyloid and tau also correlate with circuit precision in sleep EEG. Theta burst EEG power is decreased in very early mild cognitive impairment. This technique may enable inexpensive wearable EEGs for monitoring brain health.

Neural reactivation during human sleep

Sleep promotes memory consolidation: the process by which newly acquired memories are stabilised, strengthened, and integrated into long-term storage. Pioneering research in rodents has revealed that memory reactivation in sleep is a primary mechanism underpinning sleep's beneficial effect on memory. In this review, we consider evidence for memory reactivation processes occurring in human sleep. Converging lines of research support the view that memory reactivation occurs during human sleep, and is functionally relevant for consolidation. Electrophysiology studies have shown that memory reactivation is tightly coupled to the cardinal neural oscillations of non-rapid eye movement sleep, namely slow oscillation-spindle events. In addition, functional imaging studies have found that brain regions recruited during learning become reactivated during post-learning sleep. In sum, the current evidence paints a strong case for a mechanistic role of neural reactivation in promoting memory consolidation during human sleep.

Respiration modulates sleep oscillations and memory reactivation in humans

The beneficial effect of sleep on memory consolidation relies on the precise interplay of slow oscillations and spindles. However, whether these rhythms are orchestrated by an underlying pacemaker has remained elusive. Here, we tested the relationship between respiration, which has been shown to impact brain rhythms and cognition during wake, sleep-related oscillations and memory reactivation in humans. We re-analysed an existing dataset, where scalp electroencephalography and respiration were recorded throughout an experiment in which participants (N = 20) acquired associative memories before taking a nap. Our results reveal that respiration modulates the emergence of sleep oscillations. Specifically, slow oscillations, spindles as well as their interplay (i.e., slow-oscillation_spindle complexes) systematically increase towards inhalation peaks. Moreover, the strength of respiration - slow-oscillation_spindle coupling is linked to the extent of memory reactivation (i.e., classifier evidence in favour of the previously learned stimulus category) during slow-oscillation_spindles. Our results identify a clear association between respiration and memory consolidation in humans and highlight the role of brain-body interactions during sleep.

Acoustic stimulation during sleep predicts long-lasting increases in memory performance and beneficial amyloid response in older adults

BACKGROUND

Sleep and neurodegeneration are assumed to be locked in a bi-directional vicious cycle. Improving sleep could break this cycle and help to prevent neurodegeneration. We tested multi-night phase-locked acoustic stimulation (PLAS) during slow wave sleep (SWS) as a non-invasive method to improve SWS, memory performance and plasma amyloid levels.

METHODS

32 healthy older adults (agemean: 68.9) completed a between-subject sham-controlled three-night intervention, preceded by a sham-PLAS baseline night.

RESULTS

PLAS induced increases in sleep-associated spectral-power bands as well as a 24% increase in slow wave-coupled spindles, known to support memory consolidation. There was no significant group-difference in memory performance or amyloid-beta between the intervention and control group. However, the magnitude of PLAS-induced physiological responses were associated with memory performance up to 3 months post intervention and beneficial changes in plasma amyloid. Results were exclusive to the intervention group.

DISCUSSION

Multi-night PLAS is associated with long-lasting benefits in memory and metabolite clearance in older adults, rendering PLAS a promising tool to build upon and develop long-term protocols for the prevention of cognitive decline.

Towards Optimization of Oscillatory Stimulation During Sleep

BACKGROUND

Oscillatory rhythms during sleep, such as slow oscillations (SOs) and spindles and, most importantly, their coupling, are thought to underlie processes of memory consolidation. External slow oscillatory transcranial direct current stimulation (so-tDCS) with a frequency of 0.75 Hz has been shown to improve this coupling and memory consolidation; however, effects varied quite markedly between individuals, studies, and species. In this study, we aimed to determine how precisely the frequency of stimulation must match the naturally occurring SO frequency in individuals to best improve SO-spindle coupling. Moreover, we systematically tested stimulation durations necessary to induce changes.

MATERIALS AND METHODS

We addressed these questions by comparing so-tDCS with individualized frequency to standardized frequency of 0.75 Hz in a within-subject design with 28 older participants during napping while stimulation train durations were systematically varied between 30 seconds, 2 minutes, and 5 minutes.

RESULTS

Stimulation trains as short as 30 seconds were sufficient to modulate the coupling between SOs and spindle activity. Contrary to our expectations, so-tDCS with standardized frequency indicated stronger aftereffects regarding SO-spindle coupling than individualized frequency. Angle and variance of spindle maxima occurrence during the SO cycle were similarly modulated.

CONCLUSIONS

In sum, short stimulation trains were sufficient to induce significant changes in sleep physiology, allowing for more trains of stimulation, which provides methodological advantages and possibly even larger behavioral effects in future studies. Regarding individualized stimulation frequency, further options of optimization need to be investigated, such as closed-loop stimulation, to calibrate stimulation frequency to the SO frequency at the time of stimulation onset.

CLINICAL TRIAL REGISTRATION

The Clinicaltrials.gov registration number for the study is NCT04714879.

Sleep spindle maturity promotes slow oscillation-spindle coupling across child and adolescent development

The synchronization of canonical fast sleep spindle activity (12.5-16 Hz, adult-like) precisely during the slow oscillation (0.5-1 Hz) up peak is considered an essential feature of adult non-rapid eye movement sleep. However, there is little knowledge on how this well-known coalescence between slow oscillations and sleep spindles develops. Leveraging individualized detection of single events, we first provide a detailed cross-sectional characterization of age-specific patterns of slow and fast sleep spindles, slow oscillations, and their coupling in children and adolescents aged 5-6, 8-11, and 14-18 years, and an adult sample of 20- to 26-year-olds. Critically, based on this, we then investigated how spindle and slow oscillation maturity substantiate age-related differences in their precise orchestration. While the predominant type of fast spindles was development-specific in that it was still nested in a frequency range below the canonical fast spindle range for the majority of children, the well-known slow oscillation-spindle coupling pattern was evident for sleep spindles in the adult-like canonical fast spindle range in all four age groups-but notably less precise in children. To corroborate these findings, we linked personalized measures of fast spindle maturity, which indicate the similarity between the prevailing development-specific and adult-like canonical fast spindles, and slow oscillation maturity, which reflects the extent to which slow oscillations show frontal dominance, with individual slow oscillation-spindle coupling patterns. Importantly, we found that fast spindle maturity was uniquely associated with enhanced slow oscillation-spindle coupling strength and temporal precision across the four age groups. Taken together, our results suggest that the increasing ability to generate adult-like canonical fast sleep spindles actuates precise slow oscillation-spindle coupling patterns from childhood through adolescence and into young adulthood.

Memory ability and retention performance relate differentially to sleep depth and spindle type

Temporal interactions between non-rapid eye movement (NREM) sleep rhythms especially the coupling between cortical slow oscillations (SO, ∼1 Hz) and thalamic spindles (∼12 Hz) have been proposed to contribute to multi-regional interactions crucial for memory processing and cognitive ability. We investigated relationships between NREM sleep depth, sleep spindles and SO-spindle coupling regarding memory ability and memory consolidation in healthy humans. Findings underscore the functional relevance of spindle dynamics (slow versus fast), SO-phase, and most importantly NREM sleep depth for cognitive processing. Cross-frequency coupling analyses demonstrated stronger precise temporal coordination of slow spindles to SO down-state in N2 for subjects with higher general memory ability. A GLM model underscored this relationship, and furthermore that fast spindle properties were predictive of overnight memory consolidation. Our results suggest cognitive fingerprints dependent on conjoint fine-tuned SO-spindle temporal coupling, spindle properties, and brain sleep state.

Spindle-dependent memory consolidation in healthy adults: A meta-analysis

Accumulating evidence suggests a central role for sleep spindles in the consolidation of new memories. However, no meta-analysis of the association between sleep spindles and memory performance has been conducted so far. Here, we report meta-analytical evidence for spindle-memory associations and investigate how multiple factors, including memory type, spindle type, spindle characteristics, and EEG topography affect this relationship. The literature search yielded 53 studies reporting 1427 effect sizes, resulting in a small to moderate effect for the average association. We further found that spindle-memory associations were significantly stronger for procedural memory than for declarative memory. Neither spindle types nor EEG scalp topography had an impact on the strength of the spindle-memory relation, but we observed a distinct functional role of global and fast sleep spindles, especially for procedural memory. We also found a moderation effect of spindle characteristics, with power showing the largest effect sizes. Collectively, our findings suggest that sleep spindles are involved in learning, thereby representing a general physiological mechanism for memory consolidation.

Right-lateralized sleep spindles are associated with neutral over emotional bias in picture recognition: An overnight study

Sleep is especially important for emotional memories, although the mechanisms for prioritizing emotional content are insufficiently known. As during waking, emotional processing during sleep may be hemispherically asymmetric; right-lateralized rapid-eye movement (REM) sleep theta (~4-7 Hz) is reportedly associated with emotional memory retention. No research exists on lateralized non-REM sleep oscillations. However, sleep spindles, especially when coupled with slow oscillations (SOs), facilitate off-line memory consolidation.Our primary goal was to examine how the lateralization (right-to-left contrast) of REM theta, sleep spindles, and SO-spindle coupling is associated with overnight recognition memory in a task consisting of neutral and emotionally aversive pictures. Thirty-two healthy adults encoded 150 target pictures before overnight sleep. The recognition of target pictures among foils (discriminability, d') was tested immediately, 12 hours, and 24 hours after encoding.Recognition discriminability between targets and foils was similar for neutral and emotional pictures in immediate and 12-h retrievals. After 24 hours, emotional pictures were less accurately discriminated (p < 0.001). Emotional difference at 24-h retrieval was associated with right-to-left contrast in frontal fast spindle density (p < 0.001). The lateralization of SO-spindle coupling was associated with higher neutral versus emotional difference across all retrievals (p = 0.004).Our findings contribute to a largely unstudied area in sleep-related memory research. Hemispheric asymmetry in non-REM sleep oscillations may contribute to how neutral versus emotional information is processed. This is presumably underlain by both mechanistic offline memory consolidation and a trait-like cognitive/affective bias that influences memory encoding and retrieval. Methodological choices and participants' affective traits are likely involved.

Multivariate prediction of cognitive performance from the sleep electroencephalogram

Human cognitive performance is a key function whose biological foundations have been partially revealed by genetic and brain imaging studies. The sleep electroencephalogram (EEG) is tightly linked to structural and functional features of the central nervous system and serves as another promising biomarker. We used data from MrOS, a large cohort of older men and cross-validated regularized regression to link sleep EEG features to cognitive performance in cross-sectional analyses. In independent validation samples 2.5-10% of variance in cognitive performance can be accounted for by sleep EEG features, depending on the covariates used. Demographic characteristics account for more covariance between sleep EEG and cognition than health variables, and consequently reduce this association by a greater degree, but even with the strictest covariate sets a statistically significant association is present. Sigma power in NREM and beta power in REM sleep were associated with better cognitive performance, while theta power in REM sleep was associated with worse performance, with no substantial effect of coherence and other sleep EEG metrics. Our findings show that cognitive performance is associated with the sleep EEG (r = 0.283), with the strongest effect ascribed to spindle-frequency activity. This association becomes weaker after adjusting for demographic (r = 0.186) and health variables (r = 0.155), but its resilience to covariate inclusion suggest that it also partially reflects trait-like differences in cognitive ability.

Sleep and memory consolidation in aging: A neuroimaging perspective

Recently acquired information is strengthened and consolidated during sleep. For hippocampus-dependent memory, this process is assumed to occur mainly during slow wave sleep. Changes in sleep patterns in older adults can contribute to the disruption of the consolidation process during sleep and thus lead to cognitive impairment. Current findings suggest that reduced gray matter volume, particularly in frontal areas, Aβ and tau accumulation in combination with age-related changes of specific oscillations during sleep may contribute to memory deficits. This non-exhaustive review aims at providing a comprehensive picture of the associations between sleep changes and memory consolidation in aging, mainly based on neuroimaging studies. Overall, data confirm the utmost importance of sleep for healthy aging and the need to develop interventions aiming at improving sleep to reduce cognitive decline observed with advancing age.

Effects of deep brain stimulation on quantitative sleep electroencephalogram during non-rapid eye movement in Parkinson's disease

Introduction

Sleep dysfunction is frequently experienced by people with Parkinson's disease (PD) and negatively influences quality of life. Although subthalamic nucleus (STN) deep brain stimulation (DBS) can improve sleep in PD, sleep microstructural features such as sleep spindles provide additional insights about healthy sleep. For example, sleep spindles are important for better cognitive performance and for sleep consolidation in healthy adults. We hypothesized that conventional STN DBS settings would yield a greater enhancement in spindle density compared to OFF and low frequency DBS.

Methods

In a previous within-subject, cross-sectional study, we evaluated effects of low (60 Hz) and conventional high (≥130 Hz) frequency STN DBS settings on sleep macroarchitectural features in individuals with PD. In this post hoc, exploratory analysis, we conducted polysomnography (PSG)-derived quantitative electroencephalography (qEEG) assessments in a cohort of 15 individuals with PD who had undergone STN DBS treatment a median 13.5 months prior to study participation. Fourteen participants had unilateral DBS and 1 had bilateral DBS. During three nonconsecutive nights of PSG, the participants were assessed under three different DBS conditions: DBS OFF, DBS LOW frequency (60 Hz), and DBS HIGH frequency (≥130 Hz). The primary objective of this study was to investigate the changes in sleep spindle density across the three DBS conditions using repeated-measures analysis of variance. Additionally, we examined various secondary outcomes related to sleep qEEG features. For all participants, PSG-derived EEG data underwent meticulous manual inspection, with the exclusion of any segments affected by movement artifact. Following artifact rejection, sleep qEEG analysis was conducted on frontal and central leads. The measures included slow wave (SW) and spindle density and morphological characteristics, SW-spindle phase-amplitude coupling, and spectral power analysis during non-rapid eye movement (NREM) sleep.

Results

The analysis revealed that spindle density was significantly higher in the DBS HIGH condition compared to the DBS LOW condition. Surprisingly, we found that SW amplitude during NREM was significantly higher in the DBS LOW condition compared to DBS OFF and DBS HIGH conditions. However, no significant differences were observed in the other sleep qEEG features during sleep at different DBS conditions.

Conclusion

This study presents preliminary evidence suggesting that conventional HIGH frequency DBS settings enhance sleep spindle density in PD. Conversely, LOW frequency settings may have beneficial effects on increasing slow wave amplitude during sleep. These findings may inform mechanisms underlying subjective improvements in sleep quality reported in association with DBS. Moreover, this work supports the need for additional research on the influence of surgical interventions on sleep disorders, which are prevalent and debilitating non-motor symptoms in PD.

Quantitative sleep electroencephalogram and cognitive performance in Parkinson's disease with and without rapid eye movement sleep behavior disorder

Introduction

Parkinson's disease (PD) patients with REM sleep behavior disorder (RBD) are at greater risk for cognitive decline and RBD has been associated with alterations in sleep-related EEG oscillations. This study evaluates differences in sleep quantitative EEG (qEEG) and cognition in PD participants with (PD-RBD) and without RBD (PD-no-RBD).

Methods

In this cross-sectional study, polysomnography (PSG)-derived qEEG and a comprehensive level II neuropsychological assessment were compared between PD-RBD (n = 21) and PD-no-RBD (n = 31). Following artifact rejection, qEEG analysis was performed in the frontal and central leads. Measures included Scalp-slow wave (SW) density, spindle density, morphological properties of SW and sleep spindles, SW-spindle phase-amplitude coupling, and spectral power analysis in NREM and REM. The neurocognitive battery had at least two tests per domain, covering five cognitive domains as recommended by the Movement Disorders Society Task Force for PD-MCI diagnosis. Differences in qEEG features and cognitive performance were compared between the two groups. Stepwise linear regression was performed to evaluate predictors of cognitive performance. Multiple comparisons were corrected using the Benjamini-Hochberg method.

Results

Spindle density and SW-spindle co-occurrence percent were lower in participants with PD-RBD compared to PD-no-RBD. The PD-RBD group also demonstrated higher theta spectral power during REM. Sleep spindles and years of education, but not RBD, were predictors of cognitive performance.

Conclusion

PD participants with RBD have alterations in sleep-related qEEG compared to PD participants without RBD. Although PD-RBD participants had worse cognitive performance compared to PD-no-RBD, regression models suggest that lower sleep spindle density, rather than presence of RBD, predicts worse comprehensive cognitive score. Future studies should include longitudinal evaluation to determine whether sleep-related qEEG alterations are associated with more rapid cognitive decline in PD-RBD.

The Hierarchy of Coupled Sleep Oscillations Reverses with Aging in Humans

A well orchestrated coupling hierarchy of slow waves and spindles during slow-wave sleep supports memory consolidation. In old age, the duration of slow-wave sleep and the number of coupling events decrease. The coupling hierarchy deteriorates, predicting memory loss and brain atrophy. Here, we investigate the dynamics of this physiological change in slow wave-spindle coupling in a frontocentral electroencephalography position in a large sample (N = 340; 237 females, 103 males) spanning most of the human life span (age range, 15-83 years). We find that, instead of changing abruptly, spindles gradually shift from being driven by slow waves to driving slow waves with age, reversing the coupling hierarchy typically seen in younger brains. Reversal was stronger the lower the slow-wave frequency, and starts around midlife (age range, ∼40-48 years), with an established reversed hierarchy between 56 and 83 years of age. Notably, coupling strength remains unaffected by age. In older adults, deteriorating slow wave-spindle coupling, measured using the phase slope index (PSI) and the number of coupling events, is associated with blood plasma glial fibrillary acidic protein levels, a marker for astrocyte activation. Data-driven models suggest that decreased sleep time and higher age lead to fewer coupling events, paralleled by increased astrocyte activation. Counterintuitively, astrocyte activation is associated with a backshift of the coupling hierarchy (PSI) toward a "younger" status along with increased coupling occurrence and strength, potentially suggesting compensatory processes. As the changes in coupling hierarchy occur gradually starting at midlife, we suggest there exists a sizable window of opportunity for early interventions to counteract undesirable trajectories associated with neurodegeneration.SIGNIFICANCE STATEMENT Evidence accumulates that sleep disturbances and cognitive decline are bidirectionally and causally linked, forming a vicious cycle. Improving sleep quality could break this cycle. One marker for sleep quality is a clear hierarchical structure of sleep oscillations. Previous studies showed that sleep oscillations decouple in old age. Here, we show that, rather, the hierarchical structure gradually shifts across the human life span and reverses in old age, while coupling strength remains unchanged. This shift is associated with markers for astrocyte activation in old age. The shifting hierarchy resembles brain maturation, plateau, and wear processes. This study furthers our comprehension of this important neurophysiological process and its dynamic evolution across the human life span.

Emotional memory consolidation during sleep is associated with slow oscillation-spindle coupling strength in young and older adults

Emotional memories are processed during sleep; however, the specific mechanisms are unclear. Understanding such mechanisms may provide critical insight into preventing and treating mood disorders. Consolidation of neutral memories is associated with the coupling of NREM sleep slow oscillations (SOs) and sleep spindles (SPs). Whether SO-SP coupling is likewise involved in emotional memory processing is unknown. Furthermore, there is an age-related emotional valence bias such that sleep consolidates and preserves reactivity to negative but not positive emotional memories in young adults and positive but not negative emotional memories in older adults. If SO-SP coupling contributes to the effect of sleep on emotional memory, then it may selectively support negative memory in young adults and positive memory in older adults. To address these questions, we examined whether emotional memory recognition and overnight change in emotional reactivity were associated with the strength of SO-SP coupling in young (n = 22) and older (n = 32) adults. In younger adults, coupling strength predicted negative but not positive emotional memory performance after sleep. In contrast, coupling strength predicted positive but not negative emotional memory performance after sleep in older adults. Coupling strength was not associated with emotional reactivity in either age group. Our findings suggest that SO-SP coupling may play a mechanistic role in sleep-dependent consolidation of emotional memories.

How coupled slow oscillations, spindles and ripples coordinate neuronal processing and communication during human sleep

Learning and plasticity rely on fine-tuned regulation of neuronal circuits during offline periods. An unresolved puzzle is how the sleeping brain, in the absence of external stimulation or conscious effort, coordinates neuronal firing rates (FRs) and communication within and across circuits to support synaptic and systems consolidation. Using intracranial electroencephalography combined with multiunit activity recordings from the human hippocampus and surrounding medial temporal lobe (MTL) areas, we show that, governed by slow oscillation (SO) up-states, sleep spindles set a timeframe for ripples to occur. This sequential coupling leads to a stepwise increase in (1) neuronal FRs, (2) short-latency cross-correlations among local neuronal assemblies and (3) cross-regional MTL interactions. Triggered by SOs and spindles, ripples thus establish optimal conditions for spike-timing-dependent plasticity and systems consolidation. These results unveil how the sequential coupling of specific sleep rhythms orchestrates neuronal processing and communication during human sleep.

Overnight declarative memory consolidation and non-rapid eye movement sleep electroencephalographic oscillations in older adults with obstructive sleep apnea

STUDY OBJECTIVES

To compare overnight declarative memory consolidation and non-rapid eye movement (NREM) sleep electroencephalogram (EEG) oscillations in older adults with obstructive sleep apnea (OSA) to a control group and assess slow-wave activity (SWA) and sleep spindles as correlates of memory consolidation.

METHODS

Forty-six older adults (24 without OSA and 22 with OSA) completed a word-pair associate's declarative memory task before and after polysomnography. Recall and recognition were expressed as a percentage of the morning relative to evening scores. Power spectral analysis was performed on EEG recorded at frontal (F3-M2, F4-M1) and central (C3-M2, C4-M1) sites. We calculated NREM absolute slow oscillation (0.25-1 Hz) and delta (0.5-4.5 Hz) EEG power, and slow (11-13 Hz) spindle density (number of events per minute of N2 sleep) and fast (13-16 Hz) spindle density.

RESULTS

There were no significant differences in overnight recall and recognition between OSA (mean age 58.7 ± 7.1 years, apnea-hypopnea index (AHI) 41.9 ± 29.7 events/hour) and non-OSA (age 61.1 ± 10.3 years, AHI 6.6 ± 4.2 events/hour) groups. The OSA group had lower fast spindle density in the frontal region (p = 0.007). No between-group differences in SWA were observed. In the Control group, overnight recognition positively correlated with slow spindle density in frontal (rho = 0.555, p = 0.020) and central regions (rho = 0.490, p = 0.046). Overnight recall was not related to SWA or spindle measures in either group.

CONCLUSIONS

Older adults with OSA had deficits in fast sleep spindles but showed preserved overnight declarative memory consolidation. It is possible that compensatory mechanisms are being recruited by OSA patients to preserve declarative memory consolidation despite the presence of sleep spindle deficits.

Accelerating Maturation of Spatial Memory Systems by Experience: Evidence from Sleep Oscillation Signatures of Memory Processing

During early development, memory systems gradually mature over time, in parallel with the gradual accumulation of knowledge. Yet, it is unknown whether and to what extent maturation is driven by discrete experience. Sleep is thought to contribute to the formation of long-term memory and knowledge through a systems consolidation process that is driven by specific sleep oscillations (i.e., ripples, spindles, and slow oscillations) in cortical and hippocampal networks. Based on these oscillatory signatures, we show here in rats that discrete spatial experience speeds the functional maturation of spatial memory systems during development. Juvenile male rats were exposed for 5 min periods to changes in the spatial configuration of two identical objects on postnatal day (PD)25, PD27, and PD29 (Spatial experience group), while a Control group was exposed on these occasions to the same two objects without changing their positions. On PD31, both groups were tested on a classical Object Place Recognition (OPR) task with a 3 h retention interval during which the sleep-associated EEG and hippocampal local field potentials were recorded. On PD31, consistent with forgoing studies, Control rats still did not express OPR memory. By contrast, rats with Spatial experience formed significant OPR memory and, in parallel, displayed an increased percentage of hippocampal ripples coupled to parietal slow oscillation-spindle complexes, and a stronger ripple-spindle phase-locking during the retention sleep. Our findings support the idea that experience promotes the maturation of memory systems during development by enhancing cortico-hippocampal information exchange and the formation of integrated knowledge representations during sleep.SIGNIFICANCE STATEMENT Cognitive and memory capabilities mature early in life. We show here that and how discrete spatial experience contributes to this process. Using a simple recognition paradigm in developing rats, we found that exposure of the rat pups to three short-lasting experiences enhances spatial memory capabilities to adult-like levels. The adult-like capability of building spatial memory was connected to a more precise coupling of ripples in the hippocampus with slow oscillation-spindle complexes in the thalamo-cortical system when the memory was formed during sleep. Our findings support the view that discrete experience accelerates maturation of cognitive and memory capabilities by enhancing the dialogue between hippocampus and cortex when these experiences are reprocessed during sleep.

Quantitative Sleep Electroencephalogram in Parkinson's Disease: A Case-Control Study

BACKGROUND

Sleep disorders are common in Parkinson's disease (PD) and include alterations in sleep-related EEG oscillations.

OBJECTIVE

This case-control study tested the hypothesis that patients with PD would have a lower density of Scalp-Slow Wave (SW) oscillations and higher slow-to-fast frequencies ratio in rapid eye movement (REM) sleep than non-PD controls. Other sleep-related quantitative EEG (qEEG) features were also examined, including SW morphology, sleep spindles, and Scalp-SW spindle phase-amplitude coupling.

METHODS

Polysomnography (PSG)-derived sleep EEG was compared between PD participants (n = 56) and non-PD controls (n = 30). Following artifact rejection, sleep qEEG analysis was performed in frontal and central leads. Measures included SW density and morphological features of SW and sleep spindles, SW-spindle phase-amplitude coupling, and spectral power analysis in Non-REM (NREM) and REM. Differences in qEEG features between PD and non-PD controls were compared using two-tailed Welch's t-tests, and correction for multiple comparisons was performed per the Benjamini-Hochberg method.

RESULTS

SW density was lower in PD than in non-PD controls (F = 13.5, p' = 0.003). The PD group also exhibited higher ratio of slow REM EEG frequencies (F = 4.23, p' = 0.013), higher slow spindle peak frequency (F = 24.7, p' <  0.002), and greater SW-spindle coupling angle distribution non-uniformity (strength) (F = 7.30, p' = 0.034).

CONCLUSION

This study comprehensively evaluates sleep qEEG including SW-spindle phase amplitude coupling in PD compared to non-PD controls. These findings provide novel insights into how neurodegenerative disease disrupts electrophysiological sleep rhythms. Considering the role of sleep oscillatory activity on neural plasticity, future studies should investigate the influence of these qEEG markers on cognition in PD.

The sleep and wake electroencephalogram over the lifespan

Both sleep and wake encephalograms (EEG) change over the lifespan. While prior studies have characterized age-related changes in the EEG, the datasets span a particular age group, or focused on sleep and wake macrostructure rather than the microstructure. Here, we present sex-stratified data from 3372 community-based or clinic-based otherwise neurologically and psychiatrically healthy participants ranging from 11 days to 80 years of age. We estimate age norms for key sleep and wake EEG parameters including absolute and relative powers in delta, theta, alpha, and sigma bands, as well as sleep spindle density, amplitude, duration, and frequency. To illustrate the potential use of the reference measures developed herein, we compare them to sleep EEG recordings from age-matched participants with Alzheimer's disease, severe sleep apnea, depression, osteoarthritis, and osteoporosis. Although the partially clinical nature of the datasets may bias the findings towards less normal and hence may underestimate pathology in practice, age-based EEG reference values enable objective screening of deviations from healthy aging among individuals with a variety of disorders that affect brain health.

A circuit-level biomarker of Rett syndrome based on ectopic phase-amplitude coupling during slow-wave-sleep

Rett syndrome (RTT) is a neurodevelopmental disorder characterized by loss of purposeful hand use and spoken language following an initial period of normal development. Although much is known about the genetic and molecular underpinnings of RTT, less is known about the circuit-level etiopathology. Coupling of oscillations during slow-wave-sleep (SWS) underlies important neurocognitive processes in adulthood, yet its emergence has yet to be described in early typical development (TD) or in RTT. We therefore addressed these unknowns by describing SWS cross-frequency coupling in both RTT and early TD using a retrospective study design. We found that in TD, phase-amplitude coupling (PAC) during SWS was dominated by coupling of slow-wave (0.5-2 Hz) phase to theta amplitude (5-8 Hz, "SW:T") as well as slow-wave to spindle-range (12-15 Hz, "SW:S"). Coupling exhibited characteristic vertex-prominent spatial topography, which emerged during an early developmental window. This topography failed to develop in patients with RTT due to persistent ectopic coupling. Furthermore, we found that subtypes of RTT exhibit distinct PAC topographic profiles, and that ectopic PAC correlates with clinical severity. These findings suggest that altered PAC dynamics and spatial organization during SWS may underlie the circuit-level pathophysiology of RTT and suggest that ectopic coupling may contribute to RTT pathogenesis.

Mapping Sleep's Oscillatory Events as a Biomarker of Alzheimer's Disease

Objective

Memory-associated neural circuits produce oscillatory events within single-channel sleep electroencephalography (EEG), including theta bursts (TBs), sleep spindles (SPs) and multiple subtypes of slow waves (SWs). Changes in the temporal "coupling" of these events are proposed to serve as a biomarker for early stages of Alzheimer's disease (AD) pathogenesis.

Methods

We analyzed data from 205 aging adults, including single-channel sleep EEG, cerebrospinal fluid (CSF) AD-associated biomarkers, and Clinical Dementia Rating® (CDR®) scale. Individual SW events were sorted into high and low transition frequencies (TF) subtypes. We utilized time-frequency spectrogram locations within sleep EEG to "map" the precision of SW-TB and SW-SP neural circuit coupling in relation to amyloid positivity (by CSF Aβ 42 /Aβ 40 threshold), cognitive impairment (by CDR), and CSF levels of AD-associated biomarkers.

Results

Cognitive impairment was associated with lower TB spectral power in both high and low TF SW-TB coupling (p<0.001, p=0.001). Cognitively unimpaired, amyloid positive aging adults demonstrated lower precision of the neural circuits propagating high TF SW-TB (p<0.05) and low TF SW-SP (p<0.005) event coupling, compared to cognitively unimpaired amyloid negative individuals. Biomarker correlations were significant for high TF SW-TB coupling with CSF Aβ 42 /Aβ 40 (p=0.005), phosphorylated-tau 181 (p<0.005), and total-tau (p<0.05). Low TF SW-SP coupling was also correlated with CSF Aβ 42 /Aβ 40 (p<0.01).

Interpretation

Loss of integrity in neural circuits underlying sleep-dependent memory processing can be measured for both SW-TB and SW-SP coupling in spectral time-frequency space. Breakdown of sleep's memory circuit integrity is associated with amyloid positivity, higher levels of AD-associated pathology, and cognitive impairment.

Associations between objectively measured sleep parameters and cognition in healthy older adults: A meta-analysis

Multiple studies have examined associations between sleep and cognition in older adults, but a majority of these depend on self-reports on sleep and utilize cognitive tests that assess overall cognitive function. The current meta-analysis involved 72 independent studies and sought to quantify associations between objectively measured sleep parameters and cognitive performance in healthy older adults. Both sleep macrostructure (e.g., sleep duration, continuity, and stages) and microstructure (e.g., slow wave activity and spindle activity) were evaluated. For macrostructure, lower restlessness at night was associated with better memory performance (r = 0.43, p = 0.02), while lower sleep onset latency was associated with better executive functioning (r = 0.28, p = 0.03). Greater relative amount of N2 and REM sleep, but not N3, positively correlated with cognitive performance. The association between microstructure and cognition in older adults was marginally significant. This relationship was moderated by age (z = 0.07, p < 0.01), education (z = 0.26, p = 0.03), and percentage of female participants (z = 0.01, p < 0.01). The current meta-analysis emphasizes the importance of considering objective sleep measures to understand the relationship between sleep and cognition in healthy older adults. These results also form a base from which researchers using wearable sleep technology and measuring behavior through computerized testing tools can evaluate their findings.

To sleep or not to sleep - Effects on memory in normal aging and disease

Sleep behavior undergoes significant changes across the lifespan, and aging is associated with marked alterations in sleep amounts and quality. The primary sleep changes in healthy older adults include a shift in sleep timing, reduced slow-wave sleep, and impaired sleep maintenance. However, neurodegenerative and psychiatric disorders are more common among the elderly, which further worsen their sleep health. Irrespective of the cause, insufficient sleep adversely affects various bodily functions including energy metabolism, mood, and cognition. In this review, we will focus on the cognitive changes associated with inadequate sleep during normal aging and the underlying neural mechanisms.

Understanding the Need for Sleep to Improve Cognition

The restorative function of sleep is shaped by its duration, timing, continuity, subjective quality, and efficiency. Current sleep recommendations specify only nocturnal duration and have been largely derived from sleep self-reports that can be imprecise and miss relevant details. Sleep duration, preferred timing, and ability to withstand sleep deprivation are heritable traits whose expression may change with age and affect the optimal sleep prescription for an individual. Prevailing societal norms and circumstances related to work and relationships interact to influence sleep opportunity and quality. The value of allocating time for sleep is revealed by the impact of its restriction on behavior, functional brain imaging, sleep macrostructure, and late-life cognition. Augmentation of sleep slow oscillations and spindles have been proposed for enhancing sleep quality, but they inconsistently achieve their goal. Crafting bespoke sleep recommendations could benefit from large-scale, longitudinal collection of objective sleep data integrated with behavioral and self-reported data.

Do naps benefit novel word learning? Developmental differences and white matter correlates

Memory representations of newly learned words undergo changes during nocturnal sleep, as evidenced by improvements in explicit recall and lexical integration (i.e., after sleep, novel words compete with existing words during online word recognition). Some studies have revealed larger sleep-benefits in children relative to adults. However, whether daytime naps play a similar facilitatory role is unclear. We investigated the effect of a daytime nap (relative to wake) on explicit memory (recall/recognition) and lexical integration (lexical competition) of newly learned novel words in young adults and children aged 10-12 years, also exploring white matter correlates of the pre- and post-nap effects of word learning in the child group with diffusion weighted MRI. In both age groups, a nap maintained explicit memory of novel words and wake led to forgetting. However, there was an age group interaction when comparing change in recall over the nap: children showed a slight improvement whereas adults showed a slight decline. There was no evidence of lexical integration at any point. Although children spent proportionally more time in slow-wave sleep (SWS) than adults, neither SWS nor spindle parameters correlated with over-nap changes in word learning. For children, increased fractional anisotropy (FA) in the uncinate fasciculus and arcuate fasciculus were associated with the recognition of novel words immediately after learning, and FA in the right arcuate fasciculus was further associated with changes in recall of novel words over a nap, supporting the importance of these tracts in the word learning and consolidation process. These findings point to a protective role of naps in word learning (at least under the present conditions), and emphasize the need to better understand both the active and passive roles that sleep plays in supporting vocabulary consolidation over development.

Non-REM sleep in major depressive disorder

Disturbed sleep is a key symptom in major depressive disorder (MDD). REM sleep alterations are well described in the current literature, but little is known about non-REM sleep alterations. Additionally, sleep disturbances relate to a variety of cognitive symptoms in MDD, but which features of non-REM sleep EEG contribute to this, remains unknown. We comprehensively analyzed non-REM sleep EEG features in two central channels in three independently collected datasets (N = 284 recordings of 216 participants). This exploratory and descriptive study included MDD patients with a broad age range, varying duration and severity of depression, unmedicated or medicated, age- and gender-matched to healthy controls. We explored changes in sleep architecture including sleep stages and cycles, spectral power, sleep spindles, slow waves (SW), and SW-spindle coupling. Next, we analyzed the association of these sleep features with acute measures of depression severity and overnight consolidation of procedural memory. Overall, no major systematic alterations in non-REM sleep architecture were found in patients compared to controls. For the microstructure of non-REM sleep, we observed a higher spindle amplitude in unmedicated patients compared to controls, and after the start of antidepressant medication longer SWs with lower amplitude and a more dispersed SW-spindle coupling. In addition, long-term, but not short-term medication seemed to lower spindle density. Overnight procedural memory consolidation was impaired in medicated patients and associated with lower sleep spindle density. Our results suggest that alterations of non-REM sleep EEG in MDD might be more subtle than previously reported. We discuss these findings in the context of antidepressant medication intake and age.

Shaping overnight consolidation via slow-oscillation closed-loop targeted memory reactivation

Sleep constitutes a privileged state for new memories to reactivate and consolidate. Previous work has demonstrated that consolidation can be bolstered experimentally either via delivery of reminder cues (targeted memory reactivation [TMR]) or via noninvasive brain stimulation geared toward enhancing endogenous sleep rhythms. Here, we combined both approaches, controlling the timing of TMR cues with respect to ongoing slow-oscillation (SO) phases. Prior to sleep, participants learned associations between unique words and a set of repeating images (e.g., car) while hearing a prototypical image sound (e.g., engine starting). Memory performance on an immediate test vs. a test the next morning quantified overnight memory consolidation. Importantly, two image sounds were designated as TMR cues, with one cue delivered at SO UP states and the other delivered at SO DOWN states. A novel sound was used as a TMR control condition. Behavioral results revealed a significant reduction of overnight forgetting for words associated with UP-state TMR compared with words associated with DOWN-state TMR. Electrophysiological results showed that UP-state cueing led to enhancement of the ongoing UP state and was followed by greater spindle power than DOWN-state cueing. Moreover, UP-state (and not DOWN-state) cueing led to reinstatement of target image representations. Together, these results unveil the behavioral and mechanistic effects of delivering reminder cues at specific phases of endogenous sleep rhythms and mark an important step for the endeavor to experimentally modulate memories during sleep.

Contributions of memory and brain development to the bioregulation of naps and nap transitions in early childhood

The transition from multiple sleep bouts each day to a single overnight sleep bout (i.e., nap transition) is a universal process in human development. Naps are important during infancy and early childhood as they enhance learning through memory consolidation. However, a normal part of development is the transition out of naps. Understanding nap transitions is essential in order to maximize early learning and promote positive long-term cognitive outcomes. Here, we propose a novel hypothesis regarding the cognitive, physiological, and neural changes that accompany nap transitions. Specifically, we posit that maturation of the hippocampal-dependent memory network results in more efficient memory storage, which reduces the buildup of homeostatic sleep pressure across the cortex (as reflected by slow-wave activity), and eventually, contributes to nap transitions. This hypothesis synthesizes evidence of bioregulatory mechanisms underlying nap transitions and sheds new light on an important window of change in development. This framework can be used to evaluate multiple untested predictions from the field of sleep science and ultimately, yield science-based guidelines and policies regarding napping in childcare and early education settings.

Brain Microtubule Electrical Oscillations-Empirical Mode Decomposition Analysis

Microtubules (MTs) are essential cytoskeletal polymers of eukaryote cells implicated in various cell functions, including cell division, cargo transfer, and cell signaling. MTs also are highly charged polymers that generate electrical oscillations that may underlie their ability to act as nonlinear transmission lines. However, the oscillatory composition and time-frequency differences of the MT electrical oscillations have not been identified. Here, we applied the Empirical Mode Decomposition (EMD) to bovine brain MT sheet recordings to determine the number and fundamental frequencies of the Intrinsic Modes Functions (IMF) and evaluate their energetic contribution to the electrical signal. As previously reported, raw signals were obtained from cow brain MTs (Cantero et al. Sci Rep 6:27143, 2016), sampled, filtered, and subjected to signal decomposition from representative experiments. Filtered signals (200 Hz) allowed us to identify either six or seven IMFs. The reconstructed tracings faithfully resembled the original signals, with identifiable frequency peaks. To extend the analysis to obtain time-frequency information and the energy implicated in each IMF, we applied the Hilbert-Huang Transform (HHT) and the Continuous Wavelet Transform (CWT) to the same samples. The analyses disclosed the presence of more fundamental frequency peaks than initially reported and evidenced the advantages and disadvantages of each transform. The study indicates that the EMD is a robust approach to quantifying signal decomposition of brain MT oscillations and suggests novel similarities with human brain wave electroencephalogram (EEG) recordings. The evidence points to the potentially fundamental role of MT oscillations in brain electrical activity.