Order matters: sleep spindles contribute to memory consolidation only when followed by rapid-eye-movement sleep

Sleep is known to benefit memory consolidation, but little is known about the contribution of sleep stages within the sleep cycle. The sequential hypothesis proposes that memories are first replayed during non-rapid-eye-movement (NREM or N) sleep and then integrated into existing networks during rapid-eye-movement (REM or R) sleep, two successive critical steps for memory consolidation. However, it lacks experimental evidence as N always precedes R sleep in physiological conditions. We tested this sequential hypothesis in patients with central hypersomnolence disorder, including patients with narcolepsy who present the unique, anti-physiological peculiarity of frequently falling asleep in R sleep before entering N sleep. Patients performed a visual perceptual learning task before and after daytime naps stopped after one sleep cycle, starting in N or R sleep and followed by the other stage (i.e. N-R vs. R-N sleep sequence). We compared over-nap changes in performance, reflecting memory consolidation, depending on the sleep sequence during the nap. Thirty-six patients who slept for a total of 67 naps were included in the analysis. Results show that sleep spindles are associated with memory consolidation only when N is followed by R sleep, that is in physiologically ordered N-R naps, thus providing support to the sequential hypothesis in humans. In addition, we found a negative effect of rapid-eye-movements in R sleep on perceptual consolidation, highlighting the complex role of sleep stages in the balance to remember and to forget.

Dyscoordination of Non-Rapid Eye Movement Sleep Oscillations in Autism Spectrum Disorder

Study Objectives Converging evidence from neuroimaging, sleep, and genetic studies suggests that dysregulation of thalamocortical interactions mediated by the thalamic reticular nucleus (TRN) contribute to autism spectrum disorder (ASD). Sleep spindles assay TRN function, and their coordination with cortical slow oscillations (SOs) indexes thalamocortical communication. These oscillations mediate memory consolidation during sleep. In the present study, we comprehensively characterized spindles and their coordination with SOs in relation to memory and age in children with ASD. Methods Nineteen children and adolescents with ASD, without intellectual disability, and 18 typically developing (TD) peers, aged 9-17, completed a home polysomnography study with testing on a spatial memory task before and after sleep. Spindles, SOs, and their coordination were characterized during stages 2 (N2) and 3 (N3) non-rapid eye movement sleep. Results ASD participants showed disrupted SO-spindle coordination during N2 sleep. Spindles peaked later in SO upstates and their timing was less consistent. They also showed a spindle density (#/min) deficit during N3 sleep. Both groups showed significant sleep-dependent memory consolidation, but its relations with spindle density differed. While TD participants showed the expected positive correlations, ASD participants showed the opposite. Conclusions The disrupted SO-spindle coordination and spindle deficit provide further evidence of abnormal thalamocortical interactions and TRN dysfunction in ASD. The inverse relations of spindle density with memory suggest a different function for spindles in ASD than TD. We propose that abnormal sleep oscillations reflect genetically mediated disruptions of TRN-dependent thalamocortical circuit development that contribute to the manifestations of ASD and are potentially treatable.

Eszopiclone and Zolpidem Produce Opposite Effects on Hippocampal Ripple Density

Clinical populations have memory deficits linked to sleep oscillations that can potentially be treated with sleep medications. Eszopiclone and zolpidem (two non-benzodiazepine hypnotics) both enhance sleep spindles. Zolpidem improved sleep-dependent memory consolidation in humans, but eszopiclone did not. These divergent results may reflect that the two drugs have different effects on hippocampal ripple oscillations, which correspond to the reactivation of neuronal ensembles that represent previous waking activity and contribute to memory consolidation. We used extracellular recordings in the CA1 region of rats and systemic dosing of eszopiclone and zolpidem to test the hypothesis that these two drugs differentially affect hippocampal ripples and spike activity. We report evidence that eszopiclone makes ripples sparser, while zolpidem increases ripple density. In addition, eszopiclone led to a drastic decrease in spike firing, both in putative pyramidal cells and interneurons, while zolpidem did not substantially alter spiking. These results provide an explanation of the different effects of eszopiclone and zolpidem on memory in human studies and suggest that sleep medications can be used to regulate hippocampal ripple oscillations, which are causally linked to sleep-dependent memory consolidation.

Optimal Spindle Detection Parameters for Predicting Cognitive Performance

Study Objectives Alterations in sleep spindles have been linked to cognitive impairment. This finding has contributed to a growing interest in identifying sleep-based biomarkers of cognition and neurodegeneration, including sleep spindles. However, flexibility surrounding spindle definitions and algorithm parameter settings present a methodological challenge. The aim of this study was to characterize how spindle detection parameter settings influence the association between spindle features and cognition and to identify parameters with the strongest association with cognition. Methods Adult patients (n=167, 49 ± 18 years) completed the NIH Toolbox Cognition Battery after undergoing overnight diagnostic polysomnography recordings for suspected sleep disorders. We explored 1000 combinations across seven parameters in Luna, an open-source spindle detector, and used four features of detected spindles (amplitude, density, duration, and peak frequency) to fit linear multiple regression models to predict cognitive scores. Results Spindle features (amplitude, density, duration, and mean frequency) were associated with the ability to predict raw fluid cognition scores (r=0.503) and age-adjusted fluid cognition scores (r=0.315) with the best spindle parameters. Fast spindle features generally showed better performance relative to slow spindle features. Spindle features weakly predicted total cognition and poorly predicted crystallized cognition regardless of parameter settings. Conclusion Our exploration of spindle detection parameters identified optimal parameters for studies of fluid cognition and revealed the role of parameter interactions for both slow and fast spindles. Our findings support sleep spindles as a sleep-based biomarker of fluid cognition.

The adolescent pattern of sleep spindle development revealed by HD-EEG polisomnography

Sleep spindles are developmentally relevant cortical oscillatory patterns; however, they have mostly been studied by considering the entire spindle frequency range (11 to 15 Hz) without a distinction between the functionally and topographically different slow and fast spindles, using relatively few electrodes and analysing wide age-ranges. Here, we employ HD-EEG polysomnography in three age-groups between 12 to 20 years of age, with an equal distribution between the two genders, and analyse the adolescent developmental pattern of the four major parameters of slow and fast sleep spindles. Most of our findings corroborate those very few previous studies that also make a distinction between slow and fast spindles in their developmental analysis. We find spindle frequency increasing with age, although spindle density change is not obvious in our study. We confirm the declining tendencies for amplitude and duration, although within narrower, more specific age-windows than previously. Spindle frequency seems to be higher in females in the oldest age-group. Based on the pattern of our findings, we suggest that HD-EEG, specifically targeting slow and fast spindle ranges and relatively narrow age-ranges would advance the understanding of both adolescent development and the functional relevance of sleep spindles in general.

The human thalamus orchestrates neocortical oscillations during NREM sleep.

A hallmark of non-rapid eye movement (NREM) sleep is the coordinated interplay of slow oscillations (SOs) and sleep spindles. Traditionally, a cortico-thalamo-cortical loop is suggested to coordinate these rhythms: neocortically-generated SOs trigger spindles in the thalamus that are projected back to neocortex. Here, we used direct intrathalamic recordings from human epilepsy patients to test this canonical interplay. We show that SOs in the anterior thalamus precede neocortical SOs, whereas concurrently-recorded SOs in the mediodorsal thalamus are led by neocortical SOs. Furthermore, sleep spindles, detected in both thalamic nuclei, preceded their neocortical counterparts and were initiated during early phases of thalamic SOs. Our findings indicate an active role of the anterior thalamus in organizing the cardinal sleep rhythms in the neocortex and highlight the functional diversity of specific thalamic nuclei in humans. The concurrent coordination of sleep oscillations by the thalamus could have broad implications for the mechanisms underlying memory consolidation.

The association between obstructive sleep apnea and sleep spindles in middle-aged and older men: A community-based cohort study

Study objectives Sleep spindles show morphological changes in obstructive sleep apnea (OSA). However, previous small studies have limited generalisability, leaving associations between OSA severity measures and spindle metrics uncertain. This study examined cross-sectional associations between OSA severity measures and spindle metrics among a large population-based sample of men. Methods Community-dwelling men with no previous OSA diagnosis underwent home-based polysomnography. All-night EEG (F4-M1) recordings were processed for artefacts and spindle events identified using previously validated algorithms. Spindle metrics of interest included frequency (Hz), amplitude (µV 2), overall density (11–16 Hz), slow density (11–13 Hz), and fast density (13–16 Hz) (number/minute). Multivariable linear regression models controlling for demographic, biomedical, and behavioural confounders were used to examine cross-sectional associations between OSA severity measures and spindle metrics. Results In adjusted analyses, higher apnea-hypopnea index (AHI/h, as a continuous variable) and percentage total sleep time with oxygen saturation <90% (TST90) were associated with decreased slow spindle density (AHI, B= -0.003, p=0.032; TST90, B= -0.004, p=0.047) but increased frequency (AHI, B=0.002, p=0.009; TST90, B=0.002, p=0.043). Higher TST90 was also associated with greater spindle amplitude (N2 sleep, B=0.04, p=0.011; N3 sleep, B=0.11, p<0.001). Furthermore, higher arousal index was associated with greater spindle amplitude during N2 sleep (B=0.31, p<0.001) but decreased overall density (B= -1.27, p=0.030) and fast density (B= -4.36, p=0.028) during N3 sleep. Conclusions Among this large population-based sample of men, OSA severity measures were independently associated with spindle abnormalities. Further population studies are needed to determine associations between spindle metrics and functional outcomes.

Altered sleep spindles and slow waves during space shuttle missions

Sleep deficiencies and associated performance decrements are common among astronauts during spaceflight missions. Previously, sleep in space was analyzed with a focus on global measures while the intricate structure of sleep oscillations remains largely unexplored. This study extends previous findings by analyzing how spaceflight affects characteristics of sleep spindles and slow waves, two sleep oscillations associated with sleep quality and quantity, in four astronauts before, during and after two Space Shuttle missions. Analysis of these oscillations revealed significantly increased fast spindle density, elevated slow spindle frequency, and decreased slow wave amplitude in space compared to on Earth. These results reflect sleep characteristics during spaceflight on a finer electrophysiological scale and provide an opportunity for further research on sleep in space.

EEG sleep macrostructure and sleep spindles in early infancy

Study Objectives Sleep features in infancy are potential biomarkers for brain maturation but poorly characterised. 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 EEGs at 4-5 months. Sleep staging was performed and 5 features were analysed. Sleep spindles were annotated and 7 quantitative features were extracted. Features were analysed across sex, recording time (am/pm), infant age and from first to second sleep cycles. Results We analysed sleep recordings from 91 infants, 41% girls. Median (IQR) macrostructure results: sleep duration 49.0 (37.8-72.0) minutes (n=77); first sleep cycle duration 42.8 (37.0 – 51.4) minutes; REM percentage 17.4 (9.5 - 27.7)% (n=68); latency to REM 36.0 (30.5-41.1) minutes (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 -1(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)µV 2, brain symmetry index 0.20 (0.16-0.29), synchrony 59.5 (53.2-63.8)% (n=91). In males, spindle spectral power (µV 2) is 24.5% lower (p=0.032) and brain symmetry index 24.2% higher than females (p=0.011) 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<0.001) on the second cycle. Conclusion This normative data may be useful for comparison with future studies of sleep dysfunction and atypical neurodevelopment in infancy.