Sleep spindles in midday naps enhance learning in preschool children.
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ABSTRACT:
SUBMITTER: Kurdziel L
PROVIDER: S-EPMC3808582 | biostudies-other | 2013 Oct
REPOSITORIES: biostudies-other
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Project description:BackgroundChildren with Down syndrome (DS) are at increased risk of sleep-disordered breathing (SDB). We investigated sleep spindle activity, as a marker of sleep quality, and its relationship with daytime functioning in children with DS compared to typically developing (TD) children.MethodsChildren with DS and SDB (n = 44) and TD children matched for age, sex and SDB severity underwent overnight polysomnography. Fast or Slow sleep spindles were identified manually during N2/N3 sleep. Spindle activity was characterized as spindle number, density (number of spindles/h) and intensity (density × average duration) on central (C) and frontal (F) electrodes. Parents completed the Child Behavior Check List and OSA-18 questionnaires.ResultsIn children with DS, spindle activity was lower compared to TD children for F Slow and F Slow&Fast spindles combined (p < 0.001 for all). Furthermore, there were no correlations between spindle activity and CBCL subscales; however, spindle activity for C Fast and C Slow&Fast was negatively correlated with OSA-18 emotional symptoms and caregiver concerns and C Fast activity was also negatively correlated with daytime function and total problems.ConclusionsReduced spindle activity in children with DS may underpin the increased sleep disruption and negative effects of SDB on quality of life and behavior.ImpactChildren with Down syndrome (DS) are at increased risk of sleep-disordered breathing (SDB), which is associated with sleep disruption affecting daytime functioning. Sleep spindles are a sensitive marker of sleep quality. We identified for the first time that children with DS had reduced sleep spindle activity compared to typically developing children matched for SDB severity. The reduced spindle activity likely underpins the more disrupted sleep and may be associated with reduced daytime functioning and quality of life and may also be an early biomarker for an increased risk of developing dementia later in life in children with DS.
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Project description:Sleep spindles (SSs) and K-complexes (KCs) are brain patterns involved in cognitive functions that appear during sleep. Large-scale sleep studies would benefit from precise and robust automatic sleep event detectors, capable of adapting the variability in both electroencephalography (EEG) signals and expert annotation rules. We introduce the Sleep EEG Event Detector (SEED), a deep learning system that outperforms existing approaches in SS and KC detection, reaching an F1-score of 80.5% and 83.7%, respectively, on the MASS2 dataset. SEED transfers well and requires minimal fine-tuning for new datasets and annotation styles. Remarkably, SEED substantially reduces the required amount of annotated data by using a novel pretraining approach that leverages the rule-based detector A7. An analysis of 11,224 subjects revealed that SEED's detections provide better estimates of SS population statistics than existing approaches. SEED is a powerful resource for obtaining sleep-event statistics that could be useful for establishing population norms.
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Project description:Word learning plays a central role in language development and is a key predictor for later academic success. The underlying neural basis of successful word learning in children is still unknown. Here, we took advantage of the opportunity afforded by diffusion-weighted magnetic resonance imaging to investigate neural plasticity in the white matter of typically developing preschool children as they learn words. We demonstrate that after 3 weeks of word learning, children showed significantly larger increases of fractional anisotropy (FA) in the left precentral white matter compared to two control groups. Average training accuracy was correlated with FA change in the white matter underlying the left dorsal postcentral gyrus, with children who learned more slowly showing larger FA increases in this region. Moreover, we found that the status of white matter in the left middle temporal gyrus, assumed to support semantic processes, is predictive for early stages of word learning. Our findings provide the first evidence for white matter plasticity following word learning in preschool children. The present results on learning novel words in children point to a key involvement of the left fronto-parietal fiber connection, known to be implicated in top-down attention as well as working memory. While working memory and attention have been discussed to participate in word learning in children, our training study provides evidence that the neural structure supporting these cognitive processes plays a direct role in word learning.
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Project description:BACKGROUND AND AIM:Predisposing factors place certain individuals at higher risk for insomnia, especially in the presence of precipitating conditions such as stressful life events. Sleep spindles have been shown to play an important role in the preservation of sleep continuity. Lower spindle density might thus constitute an objective predisposing factor for sleep reactivity to stress. The aim of this study was therefore to evaluate the relationship between baseline sleep spindle density and the prospective change in insomnia symptoms in response to a standardized academic stressor. METHODS:Twelve healthy students had a polysomnography recording during a period of lower stress at the beginning of the academic semester, along with an assessment of insomnia complaints using the insomnia severity index (ISI). They completed a second ISI assessment at the end of the semester, a period coinciding with the week prior to final examinations and thus higher stress. Spindle density, amplitude, duration, and frequency, as well as sigma power were computed from C4-O2 electroencephalography derivation during stages N2-N3 of non-rapid-eye-movement (NREM) sleep, across the whole night and for each NREM sleep period. To test for the relationship between spindle density and changes in insomnia symptoms in response to academic stress, spindle measurements at baseline were correlated with changes in ISI across the academic semester. RESULTS:Spindle density (as well as spindle amplitude and sigma power), particularly during the first NREM sleep period, negatively correlated with changes in ISI (p?<?0.05). CONCLUSION:Lower spindle activity, especially at the beginning of the night, prospectively predicted larger increases in insomnia symptoms in response to stress. This result indicates that individual differences in sleep spindle activity contribute to the differential vulnerability to sleep disturbances in the face of precipitating factors.
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Project description: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. 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. 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. 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.
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Project description:Sleep spindles have been implicated in motor learning in human subjects, but their occurrence, timing in relation to cortical slow oscillations, and relationship to offline gains in motor learning have not been examined in animal models. In this study, we recorded EEG over bilateral primary motor cortex in conjunction with EMG for 24?h following a period of either baseline handling or following rotarod motor learning to monitor sleep. We measured several biophysical properties of sleep spindles and their temporal coupling with cortical slow oscillations (SO, <1?Hz) and cortical delta waves (1-4?Hz). Following motor learning, we found an increase in spindles during an early period of NREM sleep (1-4?h) without changes to biophysical properties such as spindle power, peak frequency and coherence. In this same period of early NREM sleep, both SO and delta power increased after motor learning. Notably, a vast majority of spindles were associated with minimal SO power, but in the subset that were associated with significant SO power (>1 z-score above the population mean), spindle-associated SO power was greater in spindles following motor learning compared to baseline sleep. Also, we did not observe a group-level preferred phase in spindle-SO or spindle-delta coupling. While SO power alone was not predictive of motor performance in early NREM sleep, both spindle density and the difference in the magnitude of the mean resultant vector length of the phase angle for SO-associated spindles, a measure of its coupling precision, were positively correlated with offline change in motor performance. These findings support a role for sleep spindles and their coupling to slow oscillations in motor learning and establish a model in which spindle timing and the brain circuits that support offline plasticity can be mechanistically explored.
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