Topographic distribution of sleep spindles in young healthy subjects

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.

Sleep spindles in adolescents with major depressive disorder

Sleep spindle differences in adolescents with major depressive disorder (MDD) compared to healthy adolescents is an ongoing debate. Results mostly indicate decreased sleep spindle activity in adolescents with MDD. Given that sleep spindles predominate NREM and that acutely delaying the sleep period via a "sleep delay challenge" (SDC) increases non-rapid eye movement (NREM) sleep duration, it may be possible to increase spindle density in adolescents with MDD, which may provide a therapeutic benefit to depression symptoms. Here, we examined the impact of a SDC on spindle density and depression symptomology in adolescents with MDD (n = 66) and healthy controls (n = 62) tested across three nights: adaptation, normal sleep, and a SDC night which delayed bedtime by three hours. The results showed that; (1) there was no difference in spindle density between groups on the normal sleep night, (2) following the SDC, both males and females with MDD had a decrease in the frequency of slow spindles, while only females with MDD had an increase in the frequency of fast spindles, (3) acute SDC reduced depression symptoms in both groups, and (4) light sleep on the normal sleep night and slow spindle frequency at SDC predicted an 8 % improvement in depression symptoms, regardless of sex or MDD diagnosis. Taken together, these results suggest that; (a) spindles may be a useful biological marker of depression symptomatology regardless of clinical MDD diagnosis, and (b) that acute SDC may help alleviate depression symptoms in adolescents with MDD.

The influence of cognitive activity on subsequent daytime nap: A deep neural network model based on sleep spindles

OBJECTIVES

Understanding the influence of cognitive activity on subsequent sleep has both theoretical and applied implications. This study aims to investigate the effect of pre-sleep cognitive activity, in the context of avoiding emotional interference, on macro-sleep and sleep spindles.

METHODS

In a within-subjects design, participants' sleep electroencephalography was collected in both the with and without pre-sleep cognitive activity conditions. Subsequent macro-sleep (i.e., sleep stage distribution and sleep parameters) and spindle characteristics (i.e., density, amplitude, duration, and frequency) were analyzed. In addition, a novel machine learning framework (i.e., deep neural network, DNN) was used to discriminate between cognitive activity and control conditions.

RESULTS

There were no significant differences in macro-sleep and sleep spindles between the cognitive activity and control conditions. Spindles-based DNN models achieved over 96% accuracy in differentiating between the two conditions, with fast spindles performing better than full-range and slow spindles.

CONCLUSIONS

These results suggest a weak but positive effect of pre-sleep cognitive activity on subsequent sleep. It sheds light on a possible low-cost and easily accessible sleep intervention strategy for clinical and educational purposes.

Advantage conferred by overnight sleep on schema-related memory may last only a day

Study Objectives

Sleep contributes to declarative memory consolidation. Independently, schemas benefit memory. Here we investigated how sleep compared with active wake benefits schema consolidation 12 and 24 hours after initial learning.

Methods

Fifty-three adolescents (age: 15-19 years) randomly assigned into sleep and active wake groups participated in a schema-learning protocol based on transitive inference (i.e. If B > C and C > D then B > D). Participants were tested immediately after learning and following 12-, and 24-hour intervals of wake or sleep for both the adjacent (e.g. B-C, C-D; relational memory) and inference pairs: (e.g.: B-D, B-E, and C-E). Memory performance following the respective 12- and 24-hour intervals were analyzed using a mixed ANOVA with schema (schema, no-schema) as the within-participant factor, and condition (sleep, wake) as the between-participant factor.

Results

Twelve hours after learning, there were significant main effects of condition (sleep, wake) and schema, as well as a significant interaction, whereby schema-related memory was significantly better in the sleep condition compared to wake. Higher sleep spindle density was most consistently associated with greater overnight schema-related memory benefit. After 24 hours, the memory advantage of initial sleep was diminished.

Conclusions

Overnight sleep preferentially benefits schema-related memory consolidation following initial learning compared with active wake, but this advantage may be eroded after a subsequent night of sleep. This is possibly due to delayed consolidation that might occur during subsequent sleep opportunities in the wake group.

Clinical Trial Information

Name: Investigating Preferred Nap Schedules for Adolescents (NFS5) URL: https://clinicaltrials.gov/ct2/show/NCT04044885. Registration: NCT04044885.

Sleep spindles and slow waves are physiological markers for age-related changes in gray matter in brain regions supporting problem-solving skills

As we age, the added benefit of sleep for memory consolidation is lost. One of the hallmark age-related changes in sleep is the reduction of sleep spindles and slow waves. Gray matter neurodegeneration is related to both age-related changes in sleep and age-related changes in memory, including memory for problem-solving skills. Here, we investigated whether spindles and slow waves might serve as biological markers for neurodegeneration of gray matter and for the related memory consolidation deficits in older adults. Forty healthy young adults (20-35 yr) and 30 healthy older adults (60-85 yr) were assigned to either nap or wake conditions. Participants were trained on the Tower of Hanoi in the morning, followed by either a 90-min nap opportunity or period of wakefulness, and were retested afterward. We found that age-related changes in sleep spindles and slow waves were differentially related to gray matter intensity in young and older adults in brain regions that support sleep-dependent memory consolidation for problem-solving skills. Specifically, we found that spindles were related to gray matter in neocortical areas (e.g., somatosensory and parietal cortex), and slow waves were related to gray matter in the anterior cingulate, hippocampus, and caudate, all areas known to support problem-solving skills. These results suggest that both sleep spindles and slow waves may serve as biological markers of age-related neurodegeneration of gray matter and the associated reduced benefit of sleep for memory consolidation in older adults.

The effect of interictal epileptic discharges and following spindles on motor sequence learning in epilepsy patients

PURPOSE

Interictal epileptic discharges (IEDs) are known to affect cognitive function in patients with epilepsy, but the mechanism has not been elucidated. Sleep spindles appearing in synchronization with IEDs were recently demonstrated to impair memory consolidation in rat, but this has not been investigated in humans. On the other hand, the increase of sleep spindles at night after learning is positively correlated with amplified learning effects during sleep for motor sequence learning. In this study, we examined the effects of IEDs and IED-coupled spindles on motor sequence learning in patients with epilepsy, and clarified their pathological significance.

MATERIALS AND METHODS

Patients undergoing long-term video-electroencephalography (LT-VEEG) at our hospital from June 2019 to November 2021 and age-matched healthy subjects were recruited. Motor sequence learning consisting of a finger-tapping task was performed before bedtime and the next morning, and the improvement rate of performance was defined as the sleep-dependent learning effect. We searched for factors associated with the changes in learning effect observed between the periods of when antiseizure medications (ASMs) were withdrawn for LT-VEEG and when they were returned to usual doses after LT-VEEG.

RESULTS

Excluding six patients who had epileptic seizures at night after learning, nine patients and 11 healthy subjects were included in the study. In the patient group, there was no significant learning effect when ASMs were withdrawn. The changes in learning effect of the patient group during ASM withdrawal were not correlated with changes in sleep duration or IED density; however, they were significantly negatively correlated with changes in IED-coupled spindle density.

CONCLUSION

We found that the increase of IED-coupled spindles correlated with the decrease of sleep-dependent learning effects of procedural memory. Pathological IED-coupled sleep spindles could hinder memory consolidation, that is dependent on physiological sleep spindles, resulting in cognitive dysfunction in patients with epilepsy.

Sleep spindle dynamics suggest over-consolidation in post-traumatic stress disorder

Devastating and persisting traumatic memories are a central symptom of post-traumatic stress disorder (PTSD). Sleep problems are highly co-occurrent with PTSD and intertwined with its etiology. Notably, sleep hosts memory consolidation processes, supported by sleep spindles (11–16 Hz). Here we assess the hypothesis that intrusive memory symptoms in PTSD may arise from excessive memory consolidation, reflected in exaggerated spindling. We use a newly developed spindle detection method, entailing minimal assumptions regarding spindle phenotype, to assess spindle activity in PTSD patients and traumatized controls. Our results show increased spindle activity in PTSD, which positively correlates with daytime intrusive memory symptoms. Together, these findings provide a putative mechanism through which the profound sleep disturbance in PTSD may contribute to memory problems. Due to its uniform and unbiased approach, the new, minimal assumption spindle analysis seems a promising tool to detect aberrant spindling in psychiatric disorders.

The space-time profiles of sleep spindles and their coordination with slow oscillations on the electrode manifold

Sleep spindles are important for sleep quality and cognitive functions, with their coordination with slow oscillations (SOs) potentially organizing cross-region reactivation of memory traces. Here, we describe the organization of spindles on the electrode manifold and their relation to SOs. We analyzed the sleep night EEG of 34 subjects and detected spindles and SOs separately at each electrode. We compared spindle properties (frequency, duration, and amplitude) in slow wave sleep (SWS) and Stage 2 sleep (S2); and in spindles that coordinate with SOs or are uncoupled. We identified different topographical spindle types using clustering analysis that grouped together spindles co-detected across electrodes within a short delay (±300 ms). We then analyzed the properties of spindles of each type, and coordination to SOs. We found that SWS spindles are shorter than S2 spindles, and spindles at frontal electrodes have higher frequencies in S2 compared to SWS. Furthermore, S2 spindles closely following an SO (about 10% of all spindles) show faster frequency, shorter duration, and larger amplitude than uncoupled ones. Clustering identified Global, Local, Posterior, Frontal-Right and Left spindle types. At centro-parietal locations, Posterior spindles show faster frequencies compared to other types. Furthermore, the infrequent SO-spindle complexes are preferentially recruiting Global SO waves coupled with fast Posterior spindles. Our results suggest a non-uniform participation of spindles to complexes, especially evident in S2. This suggests the possibility that different mechanisms could initiate an SO-spindle complex compared to SOs and spindles separately. This has implications for understanding the role of SOs-spindle complexes in memory reactivation.

Alterations of sleep oscillations in Alzheimer's disease: A potential role for GABAergic neurons in the cortex, hippocampus, and thalamus

Sleep abnormalities are widely reported in patients with Alzheimer's disease (AD) and are linked to cognitive impairments. Sleep abnormalities could be potential biomarkers to detect AD since they are often observed at the preclinical stage. Moreover, sleep could be a target for early intervention to prevent or slow AD progression. Thus, here we review changes in brain oscillations observed during sleep, their connection to AD pathophysiology and the role of specific brain circuits. Slow oscillations (0.1-1 Hz), sleep spindles (8-15 Hz) and their coupling during non-REM sleep are consistently reduced in studies of patients and in AD mouse models although the timing and magnitude of these alterations depends on the pathophysiological changes and the animal model studied. Changes in delta (1-4 Hz) activity are more variable. Animal studies suggest that hippocampal sharp-wave ripples (100-250 Hz) are also affected. Reductions in REM sleep amount and slower oscillations during REM are seen in patients but less consistently in animal models. Thus, changes in a variety of sleep oscillations could impact sleep-dependent memory consolidation or restorative functions of sleep. Recent mechanistic studies suggest that alterations in the activity of GABAergic neurons in the cortex, hippocampus and thalamic reticular nucleus mediate sleep oscillatory changes in AD and represent a potential target for intervention. Longitudinal studies of the timing of AD-related sleep abnormalities with respect to pathology and dysfunction of specific neural networks are needed to identify translationally relevant biomarkers and guide early intervention strategies to prevent or delay AD progression.

A Novel Approach to Estimating the Cortical Sources of Sleep Spindles Using Simultaneous EEG/MEG

Sleep spindles, defining oscillations of stage II non-rapid eye movement sleep (N2), mediate sleep-dependent memory consolidation. Spindles are disrupted in several neurodevelopmental, neuropsychiatric, and neurodegenerative disorders characterized by cognitive impairment. Increasing spindles can improve memory suggesting spindles as a promising physiological target for the development of cognitive enhancing therapies. This effort would benefit from more comprehensive and spatially precise methods to characterize spindles. Spindles, as detected with electroencephalography (EEG), are often widespread across electrodes. Available evidence, however, suggests that they act locally to enhance cortical plasticity in the service of memory consolidation. Here, we present a novel method to enhance the spatial specificity of cortical source estimates of spindles using combined EEG and magnetoencephalography (MEG) data constrained to the cortex based on structural MRI. To illustrate this method, we used simultaneous EEG and MEG recordings from 25 healthy adults during a daytime nap. We first validated source space spindle detection using only EEG data by demonstrating strong temporal correspondence with sensor space EEG spindle detection (gold standard). We then demonstrated that spindle source estimates using EEG alone, MEG alone and combined EEG/MEG are stable across nap sessions. EEG detected more source space spindles than MEG and each modality detected non-overlapping spindles that had distinct cortical source distributions. Source space EEG was more sensitive to spindles in medial frontal and lateral prefrontal cortex, while MEG was more sensitive to spindles in somatosensory and motor cortices. By combining EEG and MEG data this method leverages the differential spatial sensitivities of the two modalities to obtain a more comprehensive and spatially specific source estimation of spindles than possible with either modality alone.

A sleep schedule incorporating naps benefits the transformation of hierarchical knowledge

Study Objectives

The learning brain establishes schemas (knowledge structures) that benefit subsequent learning. We investigated how sleep and having a schema might benefit initial learning followed by rearranged and expanded memoranda. We concurrently examined the contributions of sleep spindles and slow-wave sleep to learning outcomes.

Methods

Fifty-three adolescents were randomly assigned to an 8 h Nap schedule (6.5 h nocturnal sleep with a 90-minute daytime nap) or an 8 h No-Nap, nocturnal-only sleep schedule. The study spanned 14 nights, simulating successive school weeks. We utilized a transitive inference task involving hierarchically ordered faces. Initial learning to set up the schema was followed by rearrangement of the hierarchy (accommodation) and hierarchy expansion (assimilation). The expanded sequence was restudied. Recall of hierarchical knowledge was tested after initial learning and at multiple points for all subsequent phases. As a control, both groups underwent a No-schema condition where the hierarchy was introduced and modified without opportunity to set up a schema. Electroencephalography accompanied the multiple sleep opportunities.

Results

There were main effects of Nap schedule and Schema condition evidenced by superior recall of initial learning, reordered and expanded memoranda. Improved recall was consistently associated with higher fast spindle density but not slow-wave measures. This was true for both nocturnal sleep and daytime naps.

Conclusion

A sleep schedule incorporating regular nap opportunities compared to one that only had nocturnal sleep benefited building of robust and flexible schemas, facilitating recall of the subsequently rearranged and expanded structured knowledge. These benefits appear to be strongly associated with fast spindles.

Clinical Trial registration

NCT04044885 (https://clinicaltrials.gov/ct2/show/NCT04044885).

EEG sleep macrostructure and sleep spindles in early infancy

Study Objectives

Sleep features in infancy are potential biomarkers for brain maturation but poorly characterized. We describe normative values for sleep macrostructure and sleep spindles at 4–5 months of age.

Methods

Healthy term infants were recruited at birth and had daytime sleep electroencephalograms (EEGs) at 4–5 months. Sleep staging was performed and five features were analyzed. Sleep spindles were annotated and seven quantitative features were extracted. Features were analyzed across sex, recording time (am/pm), infant age, and from first to second sleep cycles.

Results

We analyzed sleep recordings from 91 infants, 41% females. Median (interquartile range [IQR]) macrostructure results: sleep duration 49.0 (37.8–72.0) min (n = 77); first sleep cycle duration 42.8 (37.0–51.4) min; rapid eye movement (REM) percentage 17.4 (9.5–27.7)% (n = 68); latency to REM 36.0 (30.5–41.1) min (n = 66). First cycle median (IQR) values for spindle features: number 241.0 (193.0–286.5), density 6.6 (5.7–8.0) spindles/min (n = 77); mean frequency 13.0 (12.8–13.3) Hz, mean duration 2.9 (2.6–3.6) s, spectral power 7.8 (4.7–11.4) µV², brain symmetry index 0.20 (0.16–0.29), synchrony 59.5 (53.2–63.8)% (n = 91). In males, spindle spectral power (µV²) was 24.5% lower (p = .032) and brain symmetry index 24.2% higher than females (p = .011) when controlling for gestational and postnatal age and timing of the nap. We found no other significant associations between studied sleep features and sex, recording time (am/pm), or age. Spectral power decreased (p < .001) on the second cycle.

Conclusion

This normative data may be useful for comparison with future studies of sleep dysfunction and atypical neurodevelopment in infancy.

Clinical Trial Registration: BABY SMART (Study of Massage Therapy, Sleep And neurodevelopMenT) (BabySMART)

URL: https://clinicaltrials.gov/ct2/show/results/NCT03381027?view=results.

ClinicalTrials.gov Identifier: NCT03381027

Sleep spindles comprise a subset of a broader class of electroencephalogram events

STUDY OBJECTIVES

Sleep spindles are defined based on expert observations of waveform features in the electroencephalogram (EEG) traces. This is a potentially limiting characterization, as transient oscillatory bursts like spindles are easily obscured in the time domain by higher amplitude activity at other frequencies or by noise. It is therefore highly plausible that many relevant events are missed by current approaches based on traditionally defined spindles. Given their oscillatory structure, we reexamine spindle activity from first principles, using time-frequency activity in comparison to scored spindles.

METHODS

Using multitaper spectral analysis, we observe clear time-frequency peaks in the sigma (10-16 Hz) range (TFσ peaks). While nearly every scored spindle coincides with a TFσ peak, numerous similar TFσ peaks remain undetected. We therefore perform statistical analyses of spindles and TFσ peaks using manual and automated detection methods, comparing event cooccurrence, morphological similarities, and night-to-night consistency across multiple datasets.

RESULTS

On average, TFσ peaks have more than three times the rate of spindles (mean rate: 9.8 vs. 3.1 events/minute). Moreover, spindles subsample the most prominent TFσ peaks with otherwise identical spectral morphology. We further demonstrate that detected TFσ peaks have stronger night-to-night rate stability (ρ = 0.98) than spindles (ρ = 0.67), while covarying with spindle rates across subjects (ρ = 0.72).

CONCLUSIONS

These results provide compelling evidence that traditionally defined spindles constitute a subset of a more generalized class of EEG events. TFσ peaks are therefore a more complete representation of the underlying phenomenon, providing a more consistent and robust basis for future experiments and analyses.

The Aging Slow Wave: A Shifting Amalgam of Distinct Slow Wave and Spindle Coupling Subtypes Define Slow Wave Sleep Across the Human Lifespan

STUDY OBJECTIVES

Slow wave and spindle coupling supports memory consolidation, and loss of coupling is linked with cognitive decline and neurodegeneration. Coupling is proposed to be a possible biomarker of neurological disease, yet little is known about the different subtypes of coupling that normally occur throughout human development and aging. Here we identify distinct subtypes of spindles within slow wave upstates and describe their relationships with sleep stage across the human lifespan.

METHODS

Coupling within a cross-sectional cohort of 582 subjects was quantified from stages N2 and N3 sleep across ages 6-88 years old. Results were analyzed across the study population via mixed model regression. Within a subset of subjects, we further utilized coupling to identify discrete subtypes of slow waves by their coupled spindles.

RESULTS

Two different subtypes of spindles were identified during the upstates of (distinct) slow waves: an "early-fast" spindle, more common in stage N2 sleep, and a "late-fast" spindle, more common in stage N3. We further found stages N2 and N3 sleep contain a mixture of discrete subtypes of slow waves, each identified by their unique coupled-spindle timing and frequency. The relative contribution of coupling subtypes shifts across the human lifespan, and a deeper sleep phenotype prevails with increasing age.

CONCLUSIONS

Distinct subtypes of slow waves and coupled spindles form the composite of slow wave sleep. Our findings support a model of sleep-dependent synaptic regulation via discrete slow wave/spindle coupling subtypes and advance a conceptual framework for the development of coupling-based biomarkers in age-associated neurological disease.

Macro and micro sleep architecture and cognitive performance in older adults

We sought to determine which facets of sleep neurophysiology were most strongly linked to cognitive performance in 3,819 older adults from two independent cohorts, using whole-night electroencephalography. From over 150 objective sleep metrics, we identified 23 that predicted cognitive performance, and processing speed in particular, with effects that were broadly independent of gross changes in sleep quality and quantity. These metrics included rapid eye movement duration, features of the electroencephalography power spectra derived from multivariate analysis, and spindle and slow oscillation morphology and coupling. These metrics were further embedded within broader associative networks linking sleep with aging and cardiometabolic disease: individuals who, compared with similarly aged peers, had better cognitive performance tended to have profiles of sleep metrics more often seen in younger, healthier individuals. Taken together, our results point to multiple facets of sleep neurophysiology that track coherently with underlying, age-dependent determinants of cognitive and physical health trajectories in older adults.

Estimation of Time-Varying Spectral Peaks and Decomposition of EEG Spectrograms

Detection of spectral peaks and estimation of their properties, including frequency and amplitude, are fundamental to many applications of signal processing. Electroencephalography (EEG) of sleep, in particular, displays characteristic oscillations that change continuously throughout the night. Capturing these dynamics is essential to understanding the sleep process and characterizing the heterogeneity observed across individuals. Most sleep EEG analyses rely on either time-averaged spectra or bandpassed amplitude/power. Unfortunately, these approaches obscure the time-variability of peak properties, require specification of a priori criteria, and cannot distinguish power from nearby oscillations. More sophisticated approaches, using various spectral models, have been proposed to better estimate oscillatory properties, but these too have limitations. We present an improved approach to spectrogram decomposition, tracking time-varying parameterized peak functions and dynamically estimating their parameters using a modified form of the iterated extended Kalman filter (IEKF) that incorporates discrete On/Off-switching of peak combinations and a sampling step to draw the initial reference trajectory. We evaluate this approach on two types of simulated examples-one nearly within the model class and one outside. We find excellent performance, in terms of spectral fits and accuracy of estimated states, for both simulation types. We then apply the approach to real EEG data of sleep onset, obtaining quality spectral estimates with estimated peak combinations closely matching the expert-scored sleep stages. This approach offers not only the ability to estimate time-varying parameters of spectral peaks but, moving forward, the potential to estimate the governing dynamics and analyze their variability across nights, subjects, and clinical groups.

Sleep and Memory in Children

Purpose of Review

This short review article aims at emphasizing interesting and important new insights about investigating sleep and memory in children aged between 6 and 13 years (middle childhood).

Recent Findings

That sleep in comparison to wakefulness benefits the consolidation of memories is well established—especially for the adult population. However, the underlying theoretical frameworks trying to explain the benefits of sleep for memory still strive for more substantiate findings including biological and physiological correlates.

Summary

Based on the most recent literature about sleep-related memory consolidation and its physiological markers during middle childhood, this article provides a review and highlights recent updates in this field.

A role for spindles in the onset of rapid eye movement sleep

Sleep spindle generation classically relies on an interplay between the thalamic reticular nucleus (TRN), thalamo-cortical (TC) relay cells and cortico-thalamic (CT) feedback during non-rapid eye movement (NREM) sleep. Spindles are hypothesized to stabilize sleep, gate sensory processing and consolidate memory. However, the contribution of non-sensory thalamic nuclei in spindle generation and the role of spindles in sleep-state regulation remain unclear. Using multisite thalamic and cortical LFP/unit recordings in freely behaving mice, we show that spike-field coupling within centromedial and anterodorsal (AD) thalamic nuclei is as strong as for TRN during detected spindles. We found that spindle rate significantly increases before the onset of rapid eye movement (REM) sleep, but not wakefulness. The latter observation is consistent with our finding that enhancing spontaneous activity of TRN cells or TRN-AD projections using optogenetics increase spindle rate and transitions to REM sleep. Together, our results extend the classical TRN-TC-CT spindle pathway to include non-sensory thalamic nuclei and implicate spindles in the onset of REM sleep.

During NREM sleep, spindles emerge from thalamocortical interactions. Here the authors carry out multisite thalamic and cortical recordings in freely behaving mice, to investigate the role of other non-classical thalamic sites in sleep spindle generation.

Slow-wave activity and sigma activities are associated with psychomotor development at 8 months of age

STUDY OBJECTIVES

The electrophysiological properties of non-rapid eye movement sleep (NREM) EEG are homeostatically modulated on global and local use-dependent levels. Furthermore, the local NREM quality reflects age-dependent brain maturation and individual, age-independent, and psychomotor potential. Cortical maturation and its electrophysiological marker, Slow-wave activity (SWA), as well as sleep spindles are known to change in topography and quality during the early years of life, but their associations with psychomotor development in infants are unknown. Therefore, we aimed to evaluate the local properties of SWA and spindles (sigma power) and ascertain whether they correlate with psychomotor development in 8-month-old infants.

METHODS

Ambulatory polysomnographies were recorded in 56 infants at 8 months of age to calculate the local SWA and sigma powers. The associations between the SWA and sigma powers and psychomotor development (Bayley-III) were examined in 36 of these infants.

RESULTS

In both hemispheres, the highest SWA and sigma powers were found occipitally and centrally, respectively, with higher powers in the right hemisphere than in the left. The Bayley-III correlated with local SWA and sigma powers: the occipital SWA and centro-occipital sigma correlated with cognitive scales, and the frontal and occipital SWA and centro-occipital sigma correlated with language and fine motor scales. Most of the correlations were unilateral.

CONCLUSIONS

In 8-month-old infants, the NREM sleep quality shows local differences that are mostly attributable to the topical phase of brain maturation. The local NREM parameters correlate with psychomotor development.

Sleep spindle abnormalities related to Alzheimer's disease: a systematic mini-review

Accumulating evidence supports a bidirectional relationship between sleep disruption and Alzheimer's disease (AD) pathology. Among various sleep electroencephalography activities, the sleep spindle is one specific electroencephalographic rhythm that has potential to be a biomarker for AD. This review explores the association between sleep spindles and AD-related dementia from a neuropsychological perspective by a systematic re-examining of recent findings. In general, sleep spindles, characterized by density, amplitude, duration, and frequency, are disrupted in AD. Moreover, its functional coupling with slow oscillation also suffers in AD. While preliminary, our observations and comparisons suggest that spindle density rather than frequency and fast spindles rather than slow spindles could be more sensitive to AD-related dementia, and spindle plasticity provides possibilities for targeted interference. In conclusion, quantitative and qualitative features of sleep spindles represent potential non-invasive and cost-effective biomarkers for AD and provide both therapeutic and public health implications.

Predicting future handedness and hemispheric dominance during infancy by analyzing sleep spindles

OBJECTIVE

To investigate whether sleep spindles asynchrony (SSA) using scalp sleep electroencephalogram (EEG) among children below 2 years of age can predict future handedness.

METHODS

This is a retrospective study conducted from October 2016 until June 2017 at the King Fahad Medical City (KFMC), Riyadh, Kingdom of Saudi Arabia. We retrospectively reviewed 300 EEGs recorded at our neurophysiology laboratory.We included EEGs performed during sleep for infants aged 2 months to 2 years who have already attained their handedness or those aged above 2 years. We excluded records of children younger than 2 months or above 2 years of age (at the time of the EEG) or those aged below 2 years (at the time of the interview), and severely abnormal tracings and those without sleep or enough SSA.

RESULTS

The lateralization of Sleep Spindles (SS) was mostly right-hemispheric (52%) compared to left-hemispheric (36.4%). The overall SS laterality did not correlate with handedness (p=0.81). In the majority of right-handed (64%) and left-handed (60%) children, the SSA was contralateral to the side of hand preference; however, it did not correlate statistically (p=0.377).

CONCLUSION

We were unable to prove a statistically significant correlation between SSA and future hand preference. Further research involving larger cohorts is still needed.

Slow oscillation-spindle coupling predicts enhanced memory formation from childhood to adolescence

Precise temporal coordination of slow oscillations (SO) and sleep spindles is a fundamental mechanism of sleep-dependent memory consolidation. SO and spindle morphology changes considerably throughout development. Critically, it remains unknown how the precise temporal coordination of these two sleep oscillations develops during brain maturation and whether their synchronization indexes the development of memory networks. Here, we use a longitudinal study design spanning from childhood to adolescence, where participants underwent polysomnography and performed a declarative word-pair learning task. Performance on the memory task was better during adolescence. After disentangling oscillatory components from 1/f activity, we found frequency shifts within SO and spindle frequency bands. Consequently, we devised an individualized cross-frequency coupling approach, which demonstrates that SO-spindle coupling strength increases during maturation. Critically, this increase indicated enhanced memory formation from childhood to adolescence. Our results provide evidence that improved coordination between SOs and spindles indexes the development of sleep-dependent memory networks.

Sleeping with Hippocampal Damage

The hippocampus plays a critical role in sleep-related memory processes [1-3], but it is unclear which specific sleep features are dependent upon this brain structure. The examination of sleep physiology in patients with focal bilateral hippocampal damage and amnesia could supply important evidence regarding these links. However, there is a dearth of such studies, despite these patients providing compelling insights into awake cognition [4, 5]. Here, we sought to identify the contribution of the hippocampus to the sleep phenotype by characterizing sleep via comprehensive qualitative and quantitative analyses in memory-impaired patients with selective bilateral hippocampal damage and matched control participants using in-home polysomnography on 4 nights. We found that, compared to control participants, patients had significantly reduced slow-wave sleep-likely due to decreased density of slow waves-as well as slow-wave activity. In contrast, slow and fast spindles were indistinguishable from those of control participants. Moreover, patients expressed slow oscillations (SOs), and SO-fast spindle coupling was observed. However, on closer scrutiny, we noted that the timing of spindles within the SO cycle was delayed in the patients. The shift of patients' spindles into the later phase of the up-state within the SO cycle may indicate a mismatch in timing across the SO-spindle-ripple events that are associated with memory consolidation [6, 7]. The substantial effect of selective bilateral hippocampal damage on large-scale oscillatory activity in the cortex suggests that, as with awake cognition, the hippocampus plays a significant role in sleep physiology, which may, in turn, be necessary for efficacious episodic memory.

Sleep Spindles: Mechanisms and Functions

Sleep spindles are burstlike signals in the electroencephalogram (EEG) of the sleeping mammalian brain and electrical surface correlates of neuronal oscillations in thalamus. As one of the most inheritable sleep EEG signatures, sleep spindles probably reflect the strength and malleability of thalamocortical circuits that underlie individual cognitive profiles. We review the characteristics, organization, regulation, and origins of sleep spindles and their implication in non-rapid-eye-movement sleep (NREMS) and its functions, focusing on human and rodent. Spatially, sleep spindle-related neuronal activity appears on scales ranging from small thalamic circuits to functional cortical areas, and generates a cortical state favoring intracortical plasticity while limiting cortical output. Temporally, sleep spindles are discrete events, part of a continuous power band, and elements grouped on an infraslow time scale over which NREMS alternates between continuity and fragility. We synthesize diverse and seemingly unlinked functions of sleep spindles for sleep architecture, sensory processing, synaptic plasticity, memory formation, and cognitive abilities into a unifying sleep spindle concept, according to which sleep spindles 1) generate neural conditions of large-scale functional connectivity and plasticity that outlast their appearance as discrete EEG events, 2) appear preferentially in thalamic circuits engaged in learning and attention-based experience during wakefulness, and 3) enable a selective reactivation and routing of wake-instated neuronal traces between brain areas such as hippocampus and cortex. Their fine spatiotemporal organization reflects NREMS as a physiological state coordinated over brain and body and may indicate, if not anticipate and ultimately differentiate, pathologies in sleep and neurodevelopmental, -degenerative, and -psychiatric conditions.

Large-scale structure and individual fingerprints of locally coupled sleep oscillations

Slow oscillations and sleep spindles, the canonical electrophysiological oscillations of nonrapid eye movement sleep, are thought to gate incoming sensory information, underlie processes of sleep-dependent memory consolidation, and are altered in various neuropsychiatric disorders. Accumulating evidence of the predominantly local expression of these individual oscillatory rhythms suggests that their cross-frequency interactions may have a similar local component. However, it is unclear whether locally coordinated sleep oscillations exist across the cortex, and whether and how these dynamics differ between fast and slow spindles, and sleep stages. Moreover, substantial individual variability in the expression of both spindles and slow oscillations raises the possibility that their temporal organization shows similar individual differences. Using two nights of multichannel electroencephalography recordings from 24 healthy individuals, we characterized the topography of slow oscillation-spindle coupling. We found that while slow oscillations are highly restricted in spatial extent, the phase of the local slow oscillation modulates local spindle activity at virtually every cortical site. However, coupling dynamics varied with spindle class, sleep stage, and cortical region. Moreover, the slow oscillation phase at which spindles were maximally expressed differed markedly across individuals while remaining stable across nights. These findings both add an important spatial aspect to our understanding of the temporal coupling of sleep oscillations and demonstrate the heterogeneity of coupling dynamics, which must be taken into account when formulating mechanistic accounts of sleep-related memory processing.

Heterogeneous profiles of coupled sleep oscillations in human hippocampus

Cross-frequency coupling of sleep oscillations is thought to mediate memory consolidation. While the hippocampus is deemed central to this process, detailed knowledge of which oscillatory rhythms interact in the sleeping human hippocampus is lacking. Combining intracranial hippocampal and non-invasive electroencephalography from twelve neurosurgical patients, we characterized spectral power and coupling during non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. Hippocampal coupling was extensive, with the majority of channels expressing spectral interactions. NREM consistently showed delta–ripple coupling, but ripples were also modulated by slow oscillations (SOs) and sleep spindles. SO–delta and SO–theta coupling, as well as interactions between delta/theta and spindle/beta frequencies also occurred. During REM, limited interactions between delta/theta and beta frequencies emerged. Moreover, oscillatory organization differed substantially between i) hippocampus and scalp, ii) sites along the anterior-posterior hippocampal axis, and iii) individuals. Overall, these results extend and refine our understanding of hippocampal sleep oscillations.

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Sleep oscillations in human hippocampus exhibit cross-frequency coupling during non-rapid eye movement sleep

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Coupling occurs between various frequency pairs, including slow oscillation, delta, theta, spindle, beta, and ripple bands

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Oscillatory organization varies between hippocampus and scalp, sites along the hippocampal axis, and individuals

Age-related differences and sexual dimorphism in canine sleep spindles

Non-REM bursts of activity in the sigma range (9-16 Hz) typical of sleep spindles predict learning in dogs, similar to humans and rats. Little is known, however, about the age-related changes in amplitude, density (spindles/minute) and frequency (waves/second) of canine spindles. We investigated a large sample (N = 155) of intact and neutered pet dogs of both sexes, varying in breed and age, searching for spindles in segments of non-REM sleep. We recorded EEG from both a frontal midline electrode (Fz) and a central midline electrode (Cz) in 55.5% of the dogs, in the remaining animals only the Fz electrode was active (bipolar derivation). A similar topography was observed for fast (≥13 Hz) spindle occurrence as in humans (fast spindle number, density on Cz > Fz). For fast spindles, density was higher in females, and increased with age. These effects were more pronounced among intact animals and on Fz. Slow spindle density declined and fast spindle frequency increased with age on Cz, while on Fz age-related amplitude decline was observed. The frequency of fast spindles on Fz and slow spindles on Cz was linked to both sex and neutering, suggesting modulation by sexual hormones. Intact females displayed higher frequencies than males and neutered females. Our findings support the argument that sigma bursts in the canine non-REM sleep are analogous to human sleep spindles, and suggest that slow and fast spindles display different trajectories related to age, of which an increase in frontal fast spindles is unique to dogs.

Spatiotemporal Dynamics of Sleep Spindle Sources Across NREM Sleep Cycles

The existence of two different types of sleep spindles (slow and fast) is well-established, according to their topographical distribution at scalp- and cortical-level. Our aim was to provide a systematic investigation focused on the temporal evolution of sleep spindle sources during non-rapid eye movement (NREM) sleep. Spindle activity was recorded and automatically detected in 20 healthy subjects. Low resolution brain electromagnetic tomography (LORETA) was applied for the EEG source localization. Aiming to evaluate the time course of the detected slow and fast spindle sources, we considered the first four NREM sleep cycles and divided each cycle into five intervals of equal duration. We confirmed the preferential localization in the frontal (Brodmann area 10) and parietal (Brodmann area 7) cortical regions, respectively for slow (11.0-12.5) and fast (13.0-14.5) spindles. Across subsequent NREM sleep episodes, the maximal source activation remained systematically located in Brodmann area 10 and Brodmann area 7, showing the topographical stability of the detected generators. However, a different time course was observed as a function of the type of spindles: a linear decrease across subsequent cycles was found for slow spindle but not for fast spindle source. The intra-cycle variations followed a "U" shaped curve for both spindle source, with a trough around third and fourth interval (middle part) and the highest values at the beginning and the end of the considered temporal window. We confirmed the involvement of the frontal and parietal brain regions in spindle generation, showing for the first time their changes within and between consecutive NREM sleep episodes. Our results point to a correspondence between the scalp-recorded electrical activity and the underlying source topography, supporting the notion that spindles are not uniform phenomena: complex region- and time-specific patterns are involved in their generation and manifestation.

Correlation of sleep microstructure with daytime sleepiness and cognitive function in young and middle-aged adults with obstructive sleep apnea syndrome

PURPOSE

To compare microstructural features of sleep in young and middle-aged adults with differing severities of obstructive sleep apnea syndrome (OSAS), and to investigate the relationship between sleep microstructural fragmentation and cognitive impairment, as well as daytime sleepiness, in these patients.

METHODS

A total of 134 adults with snoring (mean age, 37.54 ± 7.66 years) were classified into four groups based on apnea-hypopnea index: primary snoring, mild OSAS, moderate OSAS, and severe OSAS. Overnight polysomnography was performed to assess respiratory, sleep macrostructure (N1, N2, N3, and R), and sleep microstructure (arousal, cyclic alternating pattern [CAP]) parameters. Cognitive function and daytime sleepiness were assessed using Montreal Cognitive Assessment (MoCA) and Epworth Sleepiness Scale (ESS).

RESULTS

As OSAS severity increased, MoCA gradually decreased and ESS gradually increased. N1%, N2%, and N3% sleep were significantly different between the severe OSAS group and the primary snoring, mild OSAS, and moderate OSAS groups (all P < 0.05). Overall arousal index, respiratory-related arousal index, CAP time, CAP rate, phase A index, number of CAP cycles, and phase A average time differed significantly in the moderate and severe OSAS groups compared with the mild OSAS and primary snoring groups (all P < 0.05). The strongest correlations identified by stepwise multiple regression analysis were between phase A3 index and the MoCA and ESS scores.

CONCLUSIONS

Sleep microstructure exhibited significant fragmentation in patients with moderate and severe OSAS, which was associated with decreased MoCA and increased ESS scores. This suggests that phase A3 index is a sensitive indicator of sleep fragmentation in OSAS.

Brain Activation Time-Locked to Sleep Spindles Associated With Human Cognitive Abilities

Simultaneous electroencephalography and functional magnetic resonance imaging (EEG–fMRI) studies have revealed brain activations time-locked to spindles. Yet, the functional significance of these spindle-related brain activations is not understood. EEG studies have shown that inter-individual differences in the electrophysiological characteristics of spindles (e.g., density, amplitude, duration) are highly correlated with “Reasoning” abilities (i.e., “fluid intelligence”; problem solving skills, the ability to employ logic, identify complex patterns), but not short-term memory (STM) or verbal abilities. Spindle-dependent reactivation of brain areas recruited during new learning suggests night-to-night variations reflect offline memory processing. However, the functional significance of stable, trait-like inter-individual differences in brain activations recruited during spindle events is unknown. Using EEG–fMRI sleep recordings, we found that a subset of brain activations time-locked to spindles were specifically related to Reasoning abilities but were unrelated to STM or verbal abilities. Thus, suggesting that individuals with higher fluid intelligence have greater activation of brain regions recruited during spontaneous spindle events. This may serve as a first step to further understand the function of sleep spindles and the brain activity which supports the capacity for Reasoning.

The impact of frequent napping and nap practice on sleep-dependent memory in humans

Napping benefits long-term memory formation and is a tool many individuals use to improve daytime functioning. Despite its potential advantages, approximately 47% of people in the United States eschew napping. The goal of this study was to determine whether people who endorse napping at least once a week (nap+) show differences in nap outcomes, including nap-dependent memory consolidation, compared with people who rarely or never nap (nap-). Additionally, we tested whether four weeks of nap practice or restriction would change sleep and performance profiles. Using a perceptual learning task, we found that napping enhanced performance to a greater degree in nap+ compared with nap- individuals (at baseline). Additionally, performance change was associated with different electrophysiological sleep features in each group. In the nap+ group, spindle density was positively correlated with performance improvement, an effect specific to spindles in the hemisphere contralateral to the trained visual field. In the nap- group, slow oscillatory power (0.5-1 Hz) was correlated with performance. Surprisingly, no changes to performance or brain activity during sleep emerged after four weeks of nap practice or restriction. These results suggest that individual differences may impact the potential benefits of napping on performance and the ability to become a better napper.

Developmental changes of sleep spindles and their impact on sleep-dependent memory consolidation and general cognitive abilities: A longitudinal approach

Sleep spindles are related to sleep‐dependent memory consolidation and general cognitive abilities. However, they undergo drastic maturational changes during adolescence. Here we used a longitudinal approach (across 7 years) to explore whether developmental changes in sleep spindle density can explain individual differences in sleep‐dependent memory consolidation and general cognitive abilities. Ambulatory polysomnography was recorded during four nights in 34 healthy subjects (24 female) with two nights (baseline and experimental) at initial recording (age range 8–11 years) and two nights at follow‐up recording (age range 14–18 years). For declarative learning, participants encoded word pairs with a subsequent recall before and after sleep. General cognitive abilities were measured by the Wechsler Intelligence Scale. Higher slow (11–13 Hz) than fast (13–15 Hz) spindle density at frontal, central, and parietal sites during initial recordings, followed by a shift to higher fast than slow spindle density at central and parietal sites during follow‐up recordings, suggest that mature spindle topography develops throughout adolescence. Fast spindle density increases from baseline to experimental night were positively related to sleep‐dependent memory consolidation. In addition, we found that the development of fast spindles predicted the improvement in memory consolidation across the two longitudinal measurements, a finding that underlines a crucial role for mature fast spindles for sleep‐dependent memory consolidation. Furthermore, slow spindle changes across adolescence were related to general cognitive abilities, a relationship that could indicate the maturation of frontal networks relevant for efficient cognitive processing. A video abstract of this article can be viewed at: https://www.youtube.com/watch?v=7NXJzm8HbIw and https://www.youtube.com/watch?v=iuMQY1OIJ0s

Closed-Loop Targeted Memory Reactivation during Sleep Improves Spatial Navigation

Sounds associated with newly learned information that are replayed during non-rapid eye movement (NREM) sleep can improve recall in simple tasks. The mechanism for this improvement is presumed to be reactivation of the newly learned memory during sleep when consolidation takes place. We have developed an EEG-based closed-loop system to precisely deliver sensory stimulation at the time of down-state to up-state transitions during NREM sleep. Here, we demonstrate that applying this technology to participants performing a realistic navigation task in virtual reality results in a significant improvement in navigation efficiency after sleep that is accompanied by increases in the spectral power especially in the fast (12-15 Hz) sleep spindle band. Our results show promise for the application of sleep-based interventions to drive improvement in real-world tasks.

Does sleep facilitate the consolidation of allocentric or egocentric representations of implicitly learned visual-motor sequence learning?

Sleep facilitates the consolidation (i.e., enhancement) of simple, explicit (i.e., conscious) motor sequence learning (MSL). MSL can be dissociated into egocentric (i.e., motor) or allocentric (i.e., spatial) frames of reference. The consolidation of the allocentric memory representation is sleep-dependent, whereas the egocentric consolidation process is independent of sleep or wake for explicit MSL. However, it remains unclear the extent to which sleep contributes to the consolidation of implicit (i.e., unconscious) MSL, nor is it known what aspects of the memory representation (egocentric, allocentric) are consolidated by sleep. Here, we investigated the extent to which sleep is involved in consolidating implicit MSL, specifically, whether the egocentric or the allocentric cognitive representations of a learned sequence are enhanced by sleep, and whether these changes support the development of explicit sequence knowledge across sleep but not wake. Our results indicate that egocentric and allocentric representations can be behaviorally dissociated for implicit MSL. Neither representation was preferentially enhanced across sleep nor were developments of explicit awareness observed. However, after a 1-wk interval performance enhancement was observed in the egocentric representation. Taken together, these results suggest that like explicit MSL, implicit MSL has dissociable allocentric and egocentric representations, but unlike explicit sequence learning, implicit egocentric and allocentric memory consolidation is independent of sleep, and the time-course of consolidation differs significantly.

Different maturational changes of fast and slow sleep spindles in the first four years of life

OBJECTIVE/BACKGROUND

Massive changes in brain morphology and function in the first years of life reveal a postero-anterior trajectory of cortical maturation accompanied by regional modifications of NREM sleep. One of the most sensible marker of this maturation process is represented by electroencephalographic (EEG) activity within the frequency range of sleep spindles. However, direct evidence that these changes actually reflect maturational modifications of fast and slow spindles still lacks. Our study aimed at answering the following questions: 1. Do cortical changes at 11.50 Hz frequency correspond to slow spindles? 2. Do fast and slow spindles show different age trajectories and different topographical distributions? 3. Do changes in peak frequency explain age changes of slow and fast spindles?

PATIENTS/METHODS

We measured the antero-posterior changes of slow and fast spindles in the first 60 min of nightly sleep of 39 infants and children (0-48 mo.).

RESULTS

We found that (A) changes of slow spindles from birth to childhood mostly affect frontal areas (B) variations of fast and slow spindles across age groups go in opposite direction, the latter progressively increasing across ages; (C) this process is not merely reducible to changes of spindle frequency.

CONCLUSIONS

As a main finding, our cross-sectional study shows that the first form of mature spindle (i.e., corresponding to the adult phasic event of NREM sleep) is marked by the emergence of slow spindles on anterior regions around the age of 12 months.

EEG Transients in the Sigma Range During non-REM Sleep Predict Learning in Dogs

Sleep spindles are phasic bursts of thalamo-cortical activity, visible in the cortex as transient oscillations in the sigma range (usually defined in humans as 12-14 or 9-16 Hz). They have been associated with sleep-dependent memory consolidation and sleep stability in humans and rodents. Occurrence, frequency, amplitude and duration of sleep spindles co-vary with age, sex and psychiatric conditions. Spindle analogue activity in dogs has been qualitatively described, but never quantified and related to function. In the present study we used an adjusted version of a detection method previously validated in children to test whether detections in the dogs show equivalent functional correlates as described in the human literature. We found that the density of EEG transients in the 9-16 Hz range during non-REM sleep relates to memory and is characterized by sexual dimorphism similarly as in humans. The number of transients/minute was larger in the learning condition and for female dogs, and correlated with the increase of performance during recall. It can be concluded that in dogs, automatic detections in the 9-16 Hz range, in particular the slow variant (<13 Hz), are functional analogues of human spindles.

Individual Differences in Frequency and Topography of Slow and Fast Sleep Spindles

Sleep spindles are transient oscillatory waveforms that occur during non-rapid eye movement (NREM) sleep across widespread cortical areas. In humans, spindles can be classified as either slow or fast, but large individual differences in spindle frequency as well as methodological difficulties have hindered progress towards understanding their function. Using two nights of high-density electroencephalography recordings from 28 healthy individuals, we first characterize the individual variability of NREM spectra and demonstrate the difficulty of determining subject-specific spindle frequencies. We then introduce a novel spatial filtering approach that can reliably separate subject-specific spindle activity into slow and fast components that are stable across nights and across N2 and N3 sleep. We then proceed to provide detailed analyses of the topographical expression of individualized slow and fast spindle activity. Group-level analyses conform to known spatial properties of spindles, but also uncover novel differences between sleep stages and spindle classes. Moreover, subject-specific examinations reveal that individual topographies show considerable variability that is stable across nights. Finally, we demonstrate that topographical maps depend nontrivially on the spindle metric employed. In sum, our findings indicate that group-level approaches mask substantial individual variability of spindle dynamics, in both the spectral and spatial domains. We suggest that leveraging, rather than ignoring, such differences may prove useful to further our understanding of the physiology and functional role of sleep spindles.

Characterizing sleep spindles in 11,630 individuals from the National Sleep Research Resource

Sleep spindles are characteristic electroencephalogram (EEG) signatures of stage 2 non-rapid eye movement sleep. Implicated in sleep regulation and cognitive functioning, spindles may represent heritable biomarkers of neuropsychiatric disease. Here we characterize spindles in 11,630 individuals aged 4 to 97 years, as a prelude to future genetic studies. Spindle properties are highly reliable but exhibit distinct developmental trajectories. Across the night, we observe complex patterns of age- and frequency-dependent dynamics, including signatures of circadian modulation. We identify previously unappreciated correlates of spindle activity, including confounding by body mass index mediated by cardiac interference in the EEG. After taking account of these confounds, genetic factors significantly contribute to spindle and spectral sleep traits. Finally, we consider topographical differences and critical measurement issues. Taken together, our findings will lead to an increased understanding of the genetic architecture of sleep spindles and their relation to behavioural and health outcomes, including neuropsychiatric disorders.

Sleep patterns vary and are associated with health and disease. Here Purcell et al characterize sleep spindle activity in 11,630 individuals and describe age-related changes, genetic influences, and possible confounding effects, serving as a resource for further understanding the physiology of sleep.

Sleep spindle detection based on non-experts: A validation study

Accurate and efficient detection of sleep spindles is a methodological challenge. The present study describes a method of using non-experts for manual detection of sleep spindles. We recruited five experts and 168 non-experts to manually identify spindles in stage N2 and stage N3 sleep data using a MATLAB interface. Scorers classified each spindle into definite and indefinite spindle (with weights of 1 and 0.5, respectively). First, a method of optimizing the thresholds of the expert/non-expert group consensus according to the results of experts and non-experts themselves is described. Using this method, we established expert and non-expert group standards from expert and non-expert scorers, respectively, and evaluated the performance of the non-expert group standards by compared with the expert group standard (termed EGS). The results indicated that the highest performance was the non-expert group standard when definite spindles were only considered (termed nEGS-1; F1 score = 0.78 for N2; 0.68 for N3). Second, four automatic spindle detection methods were compared with the EGS. We found that the performance of nEGS-1 versus EGS was higher than that of the four automated methods. Our results also showed positive correlation between the mean F1 score of individual expert in EGS and the F1 score of nEGS-1 versus EGS across 30 segments of stage N2 data (r = 0.61, P < 0.001). Further, we found that six and nine non-experts were needed to manually identify spindles in stages N2 and N3, respectively, while maintaining acceptable performance of nEGS-1 versus EGS (F1 score = 0.79 for N2; 0.64 for N3). In conclusion, this study establishes a detailed process for detection of sleep spindles by non-experts in a crowdsourcing scheme.

CPAP Treatment Partly Normalizes Sleep Spindle Features in Obstructive Sleep Apnea

Objective. Obstructive sleep apnea (OSA) decreases sleep spindle density and frequency. We evaluated the effects of continuous positive airway pressure (CPAP) treatment on different features of sleep spindles. Methods. Twenty OSA patients underwent two night polysomnographies in a diagnostic phase and one night polysomnography after 6 months of CPAP treatment. The control group comprised 20 healthy controls. Sleep spindles were analyzed by a previously developed automated method. Unilateral and bilateral spindles were identified in central and frontopolar brain locations. Spindle density and frequency were determined for the first and last half of the NREM time. Results. The density of bilateral central spindles, which did not change in the untreated OSA patients, increased towards the morning hours during CPAP treatment and in the controls. Central spindles did not become faster with sleep in OSA patients and the central spindles remained slow in the left hemisphere even with CPAP. Conclusion. CPAP treatment normalized spindle features only partially. The changes may be associated with deficits in thalamocortical spindle generating loops. Significance. This study shows that some sleep spindle changes persist after CPAP treatment in OSA patients. The association of these changes to daytime symptoms in OSA patients needs to be further evaluated.

Sleep Spindles and Intellectual Ability: Epiphenomenon or Directly Related?

Sleep spindles—short, phasic, oscillatory bursts of activity that characterize non-rapid eye movement sleep—are one of the only electrophysiological oscillations identified as a biological marker of human intelligence (e.g., cognitive abilities commonly assessed using intelligence quotient tests). However, spindles are also important for sleep maintenance and are modulated by circadian factors. Thus, the possibility remains that the relationship between spindles and intelligence quotient may be an epiphenomenon of a putative relationship between good quality sleep and cognitive ability or perhaps modulated by circadian factors such as morningness–eveningness tendencies. We sought to ascertain whether spindles are directly or indirectly related to cognitive abilities using mediation analysis. Here, we show that fast (13.5–16 Hz) parietal but not slow (11–13.5 Hz) frontal spindles in both non-rapid eye movement stage 2 sleep and slow wave sleep are directly related to reasoning abilities (i.e., cognitive abilities that support “fluid intelligence,” such as the capacity to identify complex patterns and relationships and the use of logic to solve novel problems) but not verbal abilities (i.e., cognitive abilities that support “crystalized intelligence”; accumulated knowledge and experience) or cognitive abilities that support STM (i.e., the capacity to briefly maintain information in an available state). The relationship between fast spindles and reasoning abilities is independent of the indicators of sleep maintenance and circadian chronotype, thus suggesting that spindles are indeed a biological marker of cognitive abilities and can serve as a window to further explore the physiological and biological substrates that give rise to human intelligence.

Effects of Sleep after Experimental Trauma on Intrusive Emotional Memories

STUDY OBJECTIVES

To investigate sleep's effect in the immediate aftermath of experiencing an analog trauma in the laboratory on reducing intrusive emotional memory formation.

METHODS

Sixty-five healthy women were exposed to an experimental laboratory trauma. They viewed a neutral and a trauma film in the laboratory and were randomly allocated to either a group that slept following film viewing or a group that remained awake. Sleep was recorded with electroencephalogram in a subgroup of participants in the sleep group. All participants recorded intrusive memories in the week following the film.

RESULTS

The sleep group experienced fewer and less distressing intrusive trauma memories compared to the wake group. These effects were particularly evident toward the end of the week. Duration spent in stage N2 as opposed to light N1 sleep, a higher number of fast parietal sleep spindles and a lower rapid eye movement sleep density predicted intrusion frequency.

CONCLUSIONS

Our results have clinical implications and set the ground for early-intervention sleep studies following trauma and prevention of chronic posttrauma disorders.

Advanced Analysis of Pharmaco-Sleep Data in Humans

Pharmaco-sleep studies in humans aim at the description of the effects of drugs, most frequently substances that act on the central nervous system, by means of quantitative analysis of biosignals recorded in subjects during sleep. Up to 2007, the only standard for the classification of sleep macrostructure that found worldwide acceptance were the rules published in 1968 by Rechtschaffen and Kales. In May 2007, the AASM Manual for the Scoring of Sleep and Associated Events was published by the American Academy of Sleep Medicine, and concerning the classification of sleep stages, these new rules are supposed to replace those developed by Rechtschaffen and Kales. As compared to the rather low interrater reliability of manual sleep scoring, semiautomated approaches may achieve a reliability close to 1 (Cohen's kappa 0.99 for 2 semiautomated scorings as compared to 0.76 for 2 manual scorings) without any decline in validity. Depending on the aim of the pharmaco-sleep study, additional analyses concerning sleep fragmentation, sleep microstructure, sleep depth, sleep processes and local aspects of sleep should be considered. For some of these additional features, rules for visual scoring have been established, while for others automatic analysis is obligatory. Generally, for reasons of cost-effectiveness but also reliability, automatic analysis is preferable to visual analysis. However, the validity of the automatic method applied has to be proven.

Sleep spindles: a physiological marker of age-related changes in gray matter in brain regions supporting motor skill memory consolidation

Sleep is necessary for the optimal consolidation of procedural learning, and in particular, for motor sequential skills. Motor sequence learning remains intact with age, but sleep-dependent consolidation is impaired, suggesting that memory deficits for procedural skills are specifically impacted by age-related changes in sleep. Age-related changes in spindles may be responsible for impaired motor sequence learning consolidation, but the morphological basis for this deficit is unknown. Here, we found that gray matter in the hippocampus and cerebellum was positively correlated with both sleep spindles and offline improvements in performance in young participants but not in older participants. These results suggest that age-related changes in gray matter in the hippocampus relate to spindles and may underlie age-related deficits in sleep-related motor sequence memory consolidation. In this way, spindles can serve as a biological marker for structural brain changes and the related memory deficits in older adults.

Sleep Changes in Adolescents Following Procedural Task Training

Recent research has suggested that some of the inter-individual variation in sleep spindle activity is due to innate learning ability. Sleep spindles have also been observed to vary following learning in both young and older adults. We examined the effect of procedural task acquisition on sleep stages and on sleep spindles in an adolescent sample. Participants were 32 adolescents (17 females) between the ages of 12 and 19 years. Spindle activity was examined in three different frequency ranges: 11.00–13.50 Hz (slow), 13.51–16.00 Hz (fast), and 16.01–18.50 Hz (superfast). No changes in spindle density were observed after successful learning of the pursuit rotor task. This result was in contrast to a number of studies reporting spindle density increases following successful learning. In the present study, participants who successfully learned the task showed no changes in their sleep stage proportions, but participants who were not successful showed a decrease in the proportion of stage 2 and increases in both SWS and REM sleep. We suggest that these changes in the sleep stages are consistent with the two stage model of sleep and memory proposed by Smith et al. (2004a).

Spatiotemporal Organization and Cross-Frequency Coupling of Sleep Spindles in Primate Cerebral Cortex

STUDY OBJECTIVES

The sleep spindle has been implicated in thalamic sensory gating, cortical development, and memory consolidation. These multiple functions may depend on specific spatiotemporal emergence and interactions with other spindles and other forms of brain activity. Therefore, we measured sleep spindle cortical distribution, regional heterogeneity, synchronization, and phase relationships with other electroencephalographic components in freely moving primates.

METHODS

Transcortical field potentials were recorded from Japanese monkeys via telemetry and were analyzed using the Hilbert-Huang transform.

RESULTS

Spindle (12-20 Hz) current sources were identified over a wide region of the frontoparietal cortex. Most spindles occurred independently in their own frequency, but some appeared concordant between cortical areas with frequency interdependence, particularly in nearby regions and bilaterally symmetrical regions. Spindles in the dorsolateral prefrontal cortex appeared around the surface-positive and depth-negative phase of transcortically recorded slow oscillations (< 1 Hz), whereas centroparietal spindles emerged around the opposite phase. The slow-oscillation phase reversed between the prefrontal and central regions. Gamma activities increased before spindle onset. Several regional heterogeneities in properties of human spindles were replicated in the monkeys, including frequency, density, and inter-cortical time lags, although their topographic patterns were different from those of humans. The phase-amplitude coupling between spindle and gamma activity was also replicated.

CONCLUSIONS

Spindles in widespread cortical regions are possibly driven by independent rhythm generators, but are temporally associated to spindles in other regions and to slow and gamma oscillations by corticocortical and thalamocortical pathways.