Spindle Frequency Research Articles

A comparative analysis of sleep spindle characteristics of sleep-disordered patients and normal subjects.

Spindles differ in density, amplitude, and frequency, and these variations reflect different physiological processes. Sleep disorders are characterized by difficulty in falling asleep and maintaining sleep. In this study, we proposed a new spindle wave detection algorithm, which was more effective compared with traditional detection algorithms such as wavelet algorithm. Besides, we recorded EEG data from 20 subjects with sleep disorders and 10 normal subjects, and then we compared the spindle characteristics of sleep-disordered subjects and normal subjects (those without any sleep disorder) to assess the spindle activity during human sleep. Specifically, we scored 30 subjects on the Pittsburgh Sleep Quality Index and then analyzed the association between their sleep quality scores and spindle characteristics, reflecting the effect of sleep disorders on spindle characteristics. We found a significant correlation between the sleep quality score and spindle density (p = 1.84 × 10-8, p-value <0.05 was considered statistically significant.). We, therefore, concluded that the higher the spindle density, the better the sleep quality. The correlation analysis between the sleep quality score and mean frequency of spindles yielded a p-value of 0.667, suggesting that the spindle frequency and sleep quality score were not significantly correlated. The p-value between the sleep quality score and spindle amplitude was 1.33 × 10-4, indicating that the mean amplitude of the spindle decreases as the score increases, and the mean spindle amplitude is generally slightly higher in the normal population than in the sleep-disordered population. The normal and sleep-disordered groups did not show obvious differences in the number of spindles between symmetric channels C3/C4 and F3/F4. The difference in the density and amplitude of the spindles proposed in this paper can be a reference characteristic for the diagnosis of sleep disorders and provide valuable objective evidence for clinical diagnosis. In summary, our proposed detection method can effectively improve the accuracy of sleep spindle wave detection with stable performance. Meanwhile, our study shows that the spindle density, frequency and amplitude are different between the sleep-disordered and normal populations.

Thalamic control of sensory processing and spindles in a biophysical somatosensory thalamoreticular circuit model of wakefulness and sleep

Thalamoreticular circuitry plays a key role in arousal, attention, cognition, and sleep spindles, and is linked to several brain disorders. A detailed computational model of mouse somatosensory thalamus and thalamic reticular nucleus has been developed to capture the properties of over 14,000 neurons connected by 6 million synapses. The model recreates the biological connectivity of these neurons, and simulations of the modelreproduce multiple experimental findings in different brain states. The model shows that inhibitory rebound produces frequency-selective enhancement of thalamic responses during wakefulness. We find that thalamic interactions are responsible for the characteristic waxing and waning of spindle oscillations. In addition, we find that changes in thalamic excitability control spindle frequency and their incidence. The model is made openly available to provide a new tool for studying the function and dysfunction of the thalamoreticular circuitry in various brain states.

An infant sleep electroencephalographic marker of thalamocortical connectivity predicts behavioral outcome in late infancy

Infancy represents a critical period during which thalamocortical brain connections develop and mature. Deviations in the maturation of thalamocortical connectivity are linked to neurodevelopmental disorders. There is a lack of early biomarkers to detect and localize neuromaturational deviations, which can be overcome with mapping through high-density electroencephalography (hdEEG) assessed in sleep. Specifically, slow waves and spindles in non-rapid eye movement (NREM) sleep are generated by the thalamocortical system, and their characteristics, slow wave slope and spindle density, are closely related to neuroplasticity and learning. Spindles are often subdivided into slow (11.0-13.0 Hz) and fast (13.5-16.0 Hz) frequencies, for which not only different functions have been proposed, but for which also distinctive developmental trajectories have been reported across the first years of life. Recent studies further suggest that information processing during sleep underlying sleep-dependent learning is promoted by the temporal coupling of slow waves and spindles, yet slow wave-spindle coupling remains unexplored in infancy. Thus, we evaluated three potential biomarkers: 1) slow wave slope, 2) spindle density, and 3) the temporal coupling of slow waves with spindles. We use hdEEG to first examine the occurrence and spatial distribution of these three EEG features in healthy infants and second to evaluate a predictive relationship with later behavioral outcomes. We report four key findings: First, infants’ EEG features appear locally: slow wave slope is maximal in occipital and frontal areas, whereas slow and fast spindle density is most pronounced frontocentrally. Second, slow waves and spindles are temporally coupled in infancy, with maximal coupling strength in the occipital areas of the brain. Third, slow wave slope, fast spindle density, and slow wave-spindle coupling are not associated with concurrent behavioral status (6 months). Fourth, fast spindle density in central and frontocentral regions at age 6 months predicts overall developmental status at age 12 months, and motor skills at age 12 and 24 months. Neither slow wave slope nor slow wave-spindle coupling predict later behavioral development. We further identified spindle frequency as a determinant of slow and fast spindle density, which accordingly, also predicts motor skills at 24 months. Our results propose fast spindle density, or alternatively spindle frequency, as early EEG biomarker for identifying thalamocortical maturation, which can potentially be used for early diagnosis of neurodevelopmental disorders in infants. These findings are in support of a role of sleep spindles in sensorimotor microcircuitry development. A crucial next step will be to evaluate whether early therapeutic interventions may be effective to reverse deviations in identified individuals at risk.

Sleep spindles in the healthy brain from birth through 18 years.

Sleep spindles are present from birth and reflect cognitive functions across the lifespan, but normative values for this cognitive biomarker across development are lacking. This study aims to establish normative spindle features over development. All available normal 19-channel electroencephalograms from developmentally normal children between February 2002 and June 2021 in the MGH EEG lab were analyzed. Approximately, 20 000 spindles were hand-marked to train and validate an automated spindle detector across ages. Normative values for spindle rate, duration, frequency, refractory period, and interhemispheric lag are provided for each channel and each age. Sleep EEGs from 567 developmentally normal children (range 0 days to 18 years) were included. The detector had excellent performance (F1 = 0.47). Maximal spindle activity is seen over central regions during infancy and adolescence and frontopolar regions during childhood. Spindle rate and duration increase nonlinearly, with the most rapid changes during the first 4 months of life and between ages 3 and 14 years. Peak spindle frequency follows a U-shaped curve and discrete frontal slow and central fast spindles are evident by 18 months. Spindle refractory periods decrease between ages 1 and 14 years while interhemispheric asynchrony decreases over the first 3 months of life and between ages 1 and 14 years. These data provide age- and region-specific normative values for sleep spindles across development, where measures that deviate from these values can be considered pathological. As spindles provide a noninvasive biomarker for cognitive function across the lifespan, these normative measures can accelerate the discovery and diagnosis in neurodevelopmental disorders.

Virtual vibration absorber for active forced vibration reduction

Forced vibrations caused by unbalance can negatively impact the surface finish of high-precision grinding. This paper presents a model-free virtual vibration absorber control law, which effectively reduces vibration levels by emulating a physical vibration absorber. The control law's tuning parameters can be adjusted in real-time to track the spindle frequency, ensuring the excitation frequency always matches the anti-resonance created by the virtual vibration absorber. The control law is first experimentally validated on a flexure and then applied to a high-precision vertical grinding machine achieving a reduction of the forced vibration amplitude due to spindle unbalance by up to 85%.

Sleep spindles in people with schizophrenia, schizoaffective disorders or bipolar disorders: a pilot study in a general population-based cohort

BackgroundSleep spindles have been involved in sleep stabilization and sleep-related memory mechanisms and their deficit emerged as possible biomarker in schizophrenia. However, whether this sleep phenotype is also present in other disorders that share psychotic symptoms remains unclear. To address this gap, we assessed sleep spindles in participants of a prospective population-based cohort who underwent psychiatric assessment (CoLaus|PsyCoLaus) and polysomnographic recording (HypnoLaus).MethodsSleep was recorded using ambulatory polysomnography in participants (N = 1037) to the PsyCoLaus study. Sleep spindle parameters were measured in people with a lifelong diagnosis of schizophrenia (SZ), schizoaffective depressive (SAD), schizoaffective manic (SAM), bipolar disorder type I (BP-I) and type II (BP-II). The associations between lifetime diagnostic status (independent variables, SZ, SAD, SAM, BPD-I, BPD-II, controls) and spindle parameters (dependent variables) including density, duration, frequency and maximum amplitude, for all (slow and fast), slow- and fast-spindle were assessed using linear mixed models. Pairwise comparisons of the different spindle parameters between the SZ group and each of the other psychiatric groups was performed using a contrast testing framework from our multiple linear mixed models.ResultsOur results showed a deficit in the density and duration of sleep spindles in people with SZ. They also indicated that participants with a diagnosis of SAD, SAM, BP-I and BP-II exhibited different sleep spindle phenotypes. Interestingly, spindle densities and frequencies were different in people with a history of manic symptoms (SAM, BP-I, and BP-II) from those without (SZ, SAD).ConclusionsAlthough carried out on a very small number of participants due to the low prevalence of these disorders in general population, this pilot study brought new elements that argued in favor of a deficit of sleep spindles density and duration in people with schizophrenia. In addition, while we could expect a gradual change in intensity of the same sleep spindle parameters through psychotic diagnoses, our results seem to indicate a more complex situation in which the frequency of sleep spindles might be more impacted by diagnoses including a history of mania or hypomania. Further studies with a larger number of participants are required to confirm these effects.

Age-related changes in fast spindle clustering during non-rapid eye movement sleep and their relevance for memory consolidation.

Sleep plays a crucial role in memory consolidation. Recent data in rodents and young adults revealed that fast spindle band power fluctuates at a 0.02-Hz infraslow scale during non-rapid eye movement (NREM) sleep. These fluctuations result from a periodic temporal clustering of spindles and may modulate sleep maintenance and memory consolidation. With age, sleep undergoes substantial changes but age-related changes in spindle clustering have never been investigated. Polysomnography data were collected in 147 older (mean age ± SD: 69.3 ± 4.1 years) and 32 young-middle aged (34.5 ± 10.9 years) adults. Sleep-dependent memory consolidation was assessed in a subsample of 57 older adults using a visuospatial memory task. We analyzed power fluctuations in fast spindle frequency band, detected fast spindles, and quantified their clustering during the night separating encoding and retrieval. Fast spindle band power fluctuated at a 0.02-Hz infraslow scale in young-middle aged and older adults. However, the proportion of clustered fast spindles decreased non-linearly with age (p < .001). This effect was not mediated by NREM sleep fragmentation. The clustering level of fast spindles modulated their characteristics (p < .001). Finally, the mean size of spindle clusters was positively associated with memory consolidation (p = .036) and negatively with NREM sleep micro-arousal density (p = .033). These results suggest that clusters of fast spindles may constitute stable sleep periods promoting off-line processes such as memory consolidation. We emphasize the relevance of considering spindle dynamics, obviously impaired during aging, to understand the impact of age-related sleep changes on memory. Clinical Trial Information: Name: Study in Cognitively Intact Seniors Aiming to Assess the Effects of Meditation Training (Age-Well). URL: https://clinicaltrials.gov/ct2/show/NCT02977819?term=Age-Well&draw=2&rank=1. See STROBE_statement_AGEWELL.doc in supplementary material. Registration: EudraCT: 2016-002441-36; IDRCB: 2016-A01767-44; ClinicalTrials.gov Identifier: NCT02977819.

Conserved Population Dynamics in the Cerebro-Cerebellar System between Waking and Sleep.

Despite the importance of the cerebellum for motor learning, and the recognized role of sleep in motor memory consolidation, surprisingly little is known about neural activity in the sleeping cerebro-cerebellar system. Here, we used wireless recording from primary motor cortex (M1) and the cerebellum in three female monkeys to examine the relationship between patterns of single-unit spiking activity observed during waking behavior and in natural sleep. Across the population of recorded units, we observed similarities in the timing of firing relative to local field potential features associated with both movements during waking and up state during sleep. We also observed a consistent pattern of asymmetry in pairwise cross-correlograms, indicative of preserved sequential firing in both wake and sleep at low frequencies. Despite the overall similarity in population dynamics between wake and sleep, there was a global change in the timing of cerebellar activity relative to motor cortex, from contemporaneous in the awake state to motor cortex preceding the cerebellum in sleep. We speculate that similar population dynamics in waking and sleep may imply that cerebellar internal models are activated in both states, despite the absence of movement when asleep. Moreover, spindle frequency coherence between the cerebellum and motor cortex may provide a mechanism for cerebellar computations to influence sleep-dependent learning processes in the motor cortex.SIGNIFICANCE STATEMENT It is well known that sleep can lead to improved motor performance. One possibility is that off-line learning results from neural activity during sleep in brain areas responsible for the control of movement. In this study we show for the first time that neuronal patterns in the cerebro-cerebellar system are conserved during both movements and sleep up-states, albeit with a shift in the relative timing between areas. Additionally, we show the presence of simultaneous M1-cerebellar spike coherence at spindle frequencies associated with up-state replay and postulate that this is a mechanism whereby a cerebellar internal model can shape plasticity in neocortical circuits during sleep.

Networks of cortical activity in infants with epilepsy.

Epilepsy in infancy links to a significant risk of neurodevelopmental delay, calling for a better understanding of its underlying mechanisms. Here, we studied cortical activity networks in infants with early-onset epilepsy to identify network properties that could pre-empt infants' neurodevelopmental course. We studied high-density (64 channel) electroencephalogram during non-rapid eye movement (N2) sleep in n = 49 infants at 1 year of age after being diagnosed with epilepsy during their first year of life. We computed frequency-specific networks in the cortical source space for two intrinsic brain modes: amplitude-amplitude and phase-phase correlations. Cortical activity networks of all frequency bands and connectivity modes were compared between the syndrome groups as well as between the three categories of neurocognitive development. The group differences were studied at three spatial levels: global, regional, and individual connections. Cortical mechanisms related to infant epilepsy were further compared with physiological networks using an automatic spindle detection algorithm. Our results show that global connectivity does not significantly differ between epilepsy syndromes; however, it co-varies with neurocognitive development. The largest network differences were observed at the lowest (<1 Hz) and mid-range (10-15 Hz) frequency bands. An algorithmic removal of sleep spindles from the data partially reduced the mid-range frequency network's strength. The centrocentral and frontocentral networks at the spindle frequencies were found to be strongest in infants with a persistent age-typical neurocognitive performance, while their low-frequency (< 1 Hz) networks were weaker for both amplitude-amplitude [P = 0.008, effect size = 0.61] and phase-phase correlations (P = 0.02, effect size = 0.54) at low (< 1 Hz). However, subjects with persistent mild neurocognitive delay from 1 to 2 years of age had higher amplitude-amplitude (P = 0.02, effect size = 0.73) and phase-phase (P = 0.06, effect size = 0.59) at low frequencies than those that deteriorated from mild to severely delayed from 1 to 2 years of age. Our findings suggest that cortical activity networks reflect the underlying clinical course of infants' epilepsy, and measures of spectrally and spatially resolved networks might become useful in better understanding infantile epilepsy as a network disease.

Amygdala and hippocampus dialogue with neocortex during human sleep and wakefulness.

Previous studies have described synchronic electroencephalographic (EEG) patterns of the background activity that is characteristic of several vigilance states. To explore whether the background synchronous activity of the amygdala-hippocampal-neocortical circuit is modified during sleep in the delta, theta, alpha, sigma, beta, and gamma bands characteristic of each sleep state. By simultaneously recording intracranial and noninvasive scalp EEG (10-20 system) in epileptic patients who were candidates for neurosurgery, we explored synchronous activity among the amygdala, hippocampus, and neocortex during wakefulness (W), Non-Rapid Eye Movement (NREM), and Rapid-Eye Movement (REM) sleep. Our findings reveal that hippocampal-cortical synchrony in the sleep spindle frequencies was spread across the cortex and was higher during NREM versus W and REM, whereas the amygdala showed punctual higher synchronization with the temporal lobe. Contrary to expectations, delta synchrony between the amygdala and frontal lobe and between the hippocampus and temporal lobe was higher during REM than NREM. Gamma and alpha showed higher synchrony between limbic structures and the neocortex during wakefulness versus sleep, while synchrony among deep structures showed a mixed pattern. On the one hand, amygdala-hippocampal synchrony resembled cortical activity (i.e. higher gamma and alpha synchrony in W); on the other, it showed its own pattern in slow frequency oscillations. This is the first study to depict diverse patterns of synchronic interaction among the frequency bands during distinct vigilance states in a broad human brain circuit with direct anatomical and functional connections that play a crucial role in emotional processes and memory.

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

BackgroundPrevious studies have revealed both sleep alterations and prospective memory (PM) impairments in breast cancer (BC) patients. PM refers to memory of intended actions and is crucial for daily living tasks and treatment compliance. As sleep is known to favor memory consolidation, one may expect that changes in sleep quality related to BC would have an impact on PM performance. This study aimed at assessing sleep-dependent consolidation of intentions using an ecological, virtual reality-based PM task in BC patients not treated with chemotherapy.Materials and methodsThirty-seven early stages BC patients and 21 healthy controls (HC) participated in this study. PM was assessed using a virtual reality task, during which participants learnt a list of intentions and recalled them after a retention interval filled with a day awake or a night of sleep monitored by polysomnography. Sleep spindles and slow waves, brain oscillations involved in sleep-dependent memory consolidation, were quantified automatically using the Aseega software (Physip). Subjective sleep disturbances and markers of quality of life (psychological distress, fatigue, and well-being) were assessed by questionnaires.ResultsGreater PM performance was observed after sleep than after an equivalent period of daytime wakefulness for both groups (HC and BC). PM performance after sleep did not differ significantly between groups. Yet, BC patients reported greater sleep disturbances than HC which were related with poorer intentions retrieval, greater psychological distress, fatigue and poorer well-being. The frequency of spindles was higher and the amplitude of slow waves lower in BC patients compared to HC. However, no significant association was observed between polysomnography parameters and PM scores in the whole sample of participants.ConclusionAlthough subtle changes in brain oscillations involved in sleep-dependent memory consolidation were observed, these changes did not significantly impair overnight PM consolidation in BC patients. Nevertheless, poorer PM performance was associated with greater sleep complaints which in turn were related to poorer quality of life. Overall, these data suggest that sleep-dependent PM consolidation mechanisms are not altered in early stages BC patients not treated with chemotherapy. Further investigations are needed to understand the association between markers of quality of life and sleep-dependent memory consolidation.

Sleep EEG in young people with 22q11.2 deletion syndrome: A cross-sectional study of slow-waves, spindles and correlations with memory and neurodevelopmental symptoms.

Young people living with 22q11.2 Deletion Syndrome (22q11.2DS) are at increased risk of schizophrenia, intellectual disability, attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). In common with these conditions, 22q11.2DS is also associated with sleep problems. We investigated whether abnormal sleep or sleep-dependent network activity in 22q11.2DS reflects convergent, early signatures of neural circuit disruption also evident in associated neurodevelopmental conditions. In a cross-sectional design, we recorded high-density sleep EEG in young people (6-20 years) with 22q11.2DS (n=28) and their unaffected siblings (n=17), quantifying associations between sleep architecture, EEG oscillations (spindles and slow waves) and psychiatric symptoms. We also measured performance on a memory task before and after sleep. 22q11.2DS was associated with significant alterations in sleep architecture, including a greater proportion of N3 sleep and lower proportions of N1 and REM sleep than in siblings. During sleep, deletion carriers showed broadband increases in EEG power with increased slow-wave and spindle amplitudes, increased spindle frequency and density, and stronger coupling between spindles and slow-waves. Spindle and slow-wave amplitudes correlated positively with overnight memory in controls, but negatively in 22q11.2DS. Mediation analyses indicated that genotype effects on anxiety, ADHD and ASD were partially mediated by sleep EEG measures. This study provides a detailed description of sleep neurophysiology in 22q11.2DS, highlighting alterations in EEG signatures of sleep which have been previously linked to neurodevelopment, some of which were associated with psychiatric symptoms. Sleep EEG features may therefore reflect delayed or compromised neurodevelopmental processes in 22q11.2DS, which could inform our understanding of the neurobiology of this condition and be biomarkers for neuropsychiatric disorders. This research was funded by a Lilly Innovation Fellowship Award (UB), the National Institute of Mental Health (NIMH 5UO1MH101724; MvdB), a Wellcome Trust Institutional Strategic Support Fund (ISSF) award (MvdB), the Waterloo Foundation (918-1234; MvdB), the Baily Thomas Charitable Fund (2315/1; MvdB), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment (IMAGINE) (MR/L011166/1; JH, MvdB and MO), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment 2 (IMAGINE-2) (MR/T033045/1; MvdB, JH and MO); Wellcome Trust Strategic Award 'Defining Endophenotypes From Integrated Neurosciences' Wellcome Trust (100202/Z/12/Z MO, JH). NAD was supported by a National Institute for Health Research Academic Clinical Fellowship in Mental Health and MWJ by a Wellcome Trust Senior Research Fellowship in Basic Biomedical Science (202810/Z/16/Z). CE and HAM were supported by Medical Research Council Doctoral Training Grants (C.B.E. 1644194, H.A.M MR/K501347/1). HMM and UB were employed by Eli Lilly & Co during the study; HMM is currently an employee of Boehringer Ingelheim Pharma GmbH & Co KG. The views and opinions expressed are those of the author(s), and not necessarily those of the NHS, the NIHR or the Department of Health funders.

Sleep spindle alterations relate to working memory deficits in individuals at clinical high-risk for psychosis.

Sleep spindles are waxing and waning EEG waves exemplifying the main fast oscillatory activity occurring during NREM sleep. Several recent studies have established that sleep spindle abnormalities are present in schizophrenia spectrum disorders, including in early-course and first-episode patients, and those spindle deficits are associated with some of the cognitive impairments commonly observed in these patients. Cognitive deficits are often observed before the onset of psychosis and seem to predict poor functional outcomes in individuals at clinical high-risk for psychosis (CHR). Yet, the presence of spindle abnormalities and their relationship with cognitive dysfunction has not been investigated in CHR. In this study, overnight high-density (hd)-EEG recordings were collected in 24 CHR and 24 healthy control (HC) subjects. Spindle density, duration, amplitude, and frequency were computed and compared between CHR and HC. Furthermore, WM was assessed for both HC and CHR, and its relationship with spindle parameters was examined. CHR had reduced spindle duration in centro-parietal and prefrontal regions, with the largest decrease in the right prefrontal area. Moderation analysis showed that the relation between spindle duration and spindle frequency was altered in CHR relative to HC. Furthermore, CHR had reduced WM performance compared to HC, which was predicted by spindle frequency, whereas in HC spindle frequency, duration, and density all predicted working memory performance. Altogether, these findings indicate that sleep spindles are altered in CHR individuals, and spindle alterations are associated with their cognitive deficits, thus representing a sleep-specific putative neurophysiological biomarker of cognitive dysfunction in psychosis risk.

Enhancement of Hippocampal-Thalamocortical Temporal Coordination during Slow-Frequency Long-Duration Anterior Thalamic Spindles.

Temporal nesting of cortical slow oscillations, thalamic spindles, and hippocampal ripples indicates multiregional neuronal interactions required for memory consolidation. However, how the thalamic activity during spindles organizes hippocampal dynamics remains largely undetermined. We analyzed simultaneous recordings of anterodorsal thalamus and CA1 in male mice to determine the contribution of thalamic spindles in cross-regional synchronization. Our results indicated that temporal hippocampo-thalamocortical coupling was more enhanced during slower and longer thalamic spindles. Additionally, spindles occurring closer to slow oscillation trough were more strongly coupled to ripples. We found that the temporal association between CA1 spiking/ripples and thalamic spindles was stronger following spatial exploration compared with baseline sleep. We further developed a hippocampal-thalamocortical model to explain the mechanism underlying the duration and frequency-dependent coupling of thalamic spindles to hippocampal activity. Our findings shed light on our understanding of the functional role of thalamic activity during spindles on multiregional information transfer.SIGNIFICANCE STATEMENT The contribution of thalamic spindles with differential properties to cross-regional synchronization and information transfer still remains poorly understood. Using simultaneous anterodorsal thalamic and hippocampal recordings from naturally sleeping mice before and after exploration, we found strong coupling of CA1 units to anterodorsal thalamic spindles and increase of this coupling following spatial experience. We further showed that the temporal coupling of CA1 units and hippocampal ripples with thalamic spindles and the spindle-associated modulation of CA1 units with ripples were stronger for spindles with slower frequency of oscillations. Our experimental as well as computational findings using a hippocampal-thalamocortical model provide the first demonstration that spindle frequency and duration can provide valuable information about the underlying multiregional interactions essential for memory consolidation computations.

Sleep spindle and slow wave activity in Parkinson disease with excessive daytime sleepiness.

Excessive daytime sleepiness (EDS) is a common and devastating symptom in Parkinson disease (PD), but surprisingly most studies showed that EDS is independent from nocturnal sleep disturbance measured with polysomnography. Quantitative electroencephalography (EEG) may reveal additional insights by measuring the EEG hallmarks of non-rapid eye movement (NREM) sleep, namely slow waves and spindles. Here, we tested the hypothesis that EDS in PD is associated with nocturnal sleep disturbance revealed by quantitative NREM sleep EEG markers. Patients with PD (n = 130) underwent polysomnography followed by spectral analysis to calculate spindle frequency activity, slow-wave activity (SWA), and overnight SWA decline, which reflects the dissipation of homeostatic sleep pressure. We used the Epworth Sleepiness Scale (ESS) to assess subjective daytime sleepiness and define EDS (ESS > 10). All examinations were part of an evaluation for deep brain stimulation. Patients with EDS (n = 46) showed reduced overnight decline of SWA (p = 0.036) and reduced spindle frequency activity (p = 0.032) compared with patients without EDS. Likewise, more severe daytime sleepiness was associated with reduced SWA decline (ß= -0.24 p = 0.008) and reduced spindle frequency activity (ß= -0.42, p < 0.001) across all patients. Reduced SWA decline, but not daytime sleepiness, was associated with poor sleep quality and continuity at polysomnography. Our data suggest that daytime sleepiness in PD patients is associated with sleep disturbance revealed by quantitative EEG, namely reduced overnight SWA decline and reduced spindle frequency activity. These findings could indicate that poor sleep quality, with incomplete dissipation of homeostatic sleep pressure, may contribute to EDS in PD.

0191 Characteristics of sleep spindles across development in males with Duchenne/Becker Muscular Dystrophy Disorder

Abstract Introduction Sleep supports cognition, in particular, the consolidation of memories. Sleeping brain rhythms, such as slow oscillations (1hz) and spindles (9-15 Hz), play a key role in facilitating this consolidation. Our prior research reported age-associated declines in slow oscillations in Duchenne and Becker Muscular Dystrophy (DMD/BMD) (Simon et al., 2020). Here, we characterize age-associated changes in sleep spindle characteristics across development in this group. Methods Following our 2020 analysis, we retrospectively analyzed the clinical sleep studies of 28 DMD/BMD males (Age span: 4 to 20 years). We applied our spindle detection algorithm to six electrodes (F3, F4, C3, C4, 01, O2). We assessed spindle density, frequency, and amplitude based on age (child, early adolescent, and late adolescent). Results We conducted rmANOVAs to evaluate each spindle characteristics using within-factors (Stage and Electrode) and between-factor (Age). We found significantly more spindles with longer durations in N2 than N3; greater spindle density at frontal compared to occipital regions; and higher amplitudes at central compared to frontal sites. We found no age-associated changes in these spindle metrics. We did find an age-associated change in the frequency of spindles, with significantly greater average spindle amplitude increasing significantly with age. Conclusion In line with prior research, we found more spindles in N2 than N3 and greater spindle density at frontal compared to posterior electrodes. In contrast to our previous research demonstrating age-associated declines in slow oscillations, our current analyses show minimal age-associated changes in spindle characteristics from 4 to 20 years. Further analysis is required to assess for age-associated changes in spindle-slow oscillation coupling occur across development. Our findings have implications for functional changes in sleep-dependent cognition mechanisms across development in BMD/DMD. Support (If Any)

0190 Association of Sleep Spindle Activity with Cognition in Youth from the General Population

Abstract Introduction Sleep spindle activity has been increasingly studied as an underlying mechanism of cognition. In youth, it appears the relationship between spindle activity and cognition depends upon the spindle metric and cognitive domain examined. Prior research has been conducted primarily in highly selective experimental studies of typically developing youth. We aimed to clarify the relationship between spindle activity and lower and higher order cognitive functions in children and adolescents from the general population. Methods We studied 639 children aged 5-12y (median 9y) and 418 adolescents aged 12-23y (median 16y) from a population-based cohort. All subjects underwent a 9-hour, in-lab polysomnography. We calculated sleep spindle density (SSD), the total number of spindles per minute of stage 2 of non-rapid eye movement sleep, and peak spindle frequency (PSF) in the 10-16 Hz range at central, frontal and fronto-occipital derivations. Wechsler intelligence testing assessed verbal and non-verbal intelligence quotients (IQ), processing speed (coding) and working memory (digit span backward [DSB]). Multivariable-adjusted linear regression models with age, sex, race/ethnicity, body mass index, apnea/hypopnea index, and insomnia symptoms as covariates examined the association between SSD and PSF with cognitive outcomes. Results At ages 5-12, central SSD was positively associated with verbal IQ (p=0.04), non-verbal IQ (p=0.03), coding (p=0.01) and DSB (p&amp;lt;0.01); additionally, frontal SSD was positively associated with coding and DSB (both p&amp;lt;0.01) and fronto-occipital SSD with DSB (p&amp;lt;0.01). Also, central (p&amp;lt;0.01) and frontal (p=0.01) PSF was positively associated with DSB. At ages 12-23, fronto-occipital SSD was positively associated with non-verbal IQ (p=0.02), while no other statistically significant associations were observed for SSD or PSF with cognitive outcomes (all p≥0.08). Conclusion Spindle density is a strong correlate of general ability (both verbal and non-verbal IQ) in childhood, and it remains for non-verbal IQ in adolescence. Both increased spindle density and peak frequency are associated with better working memory in childhood, yet not in adolescence. These developmental differences may be due to cortical (e.g., synaptic pruning) and thalamocortical (e.g., increased myelination) maturational changes occurring during adolescence. Support (If Any) National Institutes of Health (R01MH118308, UL1TR000127)

0185 N2 Sleep Spindle Activity is Associated with Better Next-Day Emotion Regulation in Healthy Children

Abstract Introduction Children's day-to-day mental health is dependent on adequate quantity and quality of sleep, but far less is known about the microstructural sleep features that support emotional functioning in children. NREM sleep spindles (rhythmic EEG oscillations between 10 and 15 Hz) are closely linked with intellectual abilities and cognitive processing, and have also been shown to relate to children’s emotional behavior, both concurrently and longitudinally. For example, socially-anxious youth showed reduction in sleep spindle activity compared to healthy controls, which correlated negatively with subjective reports of arousal in response to negative images (Wilhelm et al., 2017). In younger children, greater NREM 2 spindle density was associated with greater prosocial behavior concurrently and fewer behavioral and social problems one year later (Mikoteit et al., 2012; 2013). However, studies in pediatric samples are limited overall and haven’t examined spindles in relation to objective measures of emotion regulation. Methods We examined relationships between spindle activity during NREM stage 2 (N2) and next-day subjective and objective emotional responses among N=26 healthy children, 7-11 years old. Children completed a full-night of at-home PSG monitoring (10hr sleep opportunity) followed by two in-lab tasks. In task 1, children rated arousal/reactivity in response to negative images from the International Affective Pictures System (IAPS). In task 2, respiratory sinus arrhythmia (RSA) was measured while children were directed to suppress all facial expressions of emotion (i.e., regulate emotional responses to negative content) while watching negatively-valenced movie clips. All analyses controlled for total sleep time on PSG night and RSA analyses controlled for a resting baseline period. Results Greater C3 spindle count (r = .51, p &amp;lt; .05) and density (r = .53, p &amp;lt; .05) were significantly associated with less child-reported arousal towards negative images. Greater F3 peak spindle frequency was positively associated with higher RSA during negative movies (r = .54, p &amp;lt; .05), suggesting better regulatory control of emotional responses to correspond with greater spindle peak frequency. Conclusion Together with previous data, our findings suggest that sleep spindle activity may partially reflect children’s capacity to regulate emotional responses in relation to stressful situations, thereby potentially reducing risk of mental health problems. Support (If Any)

0197 Increased Brain Kynurenic Acid Elicits Sex-Dependent Abnormalities in NREM Sleep Spindle Dynamics

Abstract Introduction Sleep spindles are thalamocortical oscillations which occur during non-rapid eye movement (NREM) sleep. NREM sleep spindle aberrations are a consistent clinical sleep deficiency associated with psychotic disorders and exacerbation of cognitive symptoms. Kynurenic acid (KYNA), a tryptophan metabolite synthesized from kynurenine via kynurenine aminotransferases (KATs) and modulator of glutamatergic and cholinergic neurotransmission, is elevated in the brain of patients with psychotic disorders, including schizophrenia and bipolar disorder. Currently, we sought to understand the neurodevelopmental and transient impacts of brain KYNA elevation on sleep spindle dynamics. Methods In Experiment #1, sleep spindles were evaluated in adult offspring, postnatal day (PD) 56 from embryonic kynurenine (EKyn) treated rat dams (Rentschler et al., 2021 Sz Bull) (N=7-9 per group). EKyn KYNA male, but not female, offspring have elevated KYNA during the light phase (Wright et al., 2021 Frontiers in Psychiatry). In Experiment #2, sleep spindles were evaluated in adult rats injected with kynurenine (100 mg/kg; i.p.) to acutely elevate brain KYNA levels at zeitgeber time 0 (N=8-12 per group). Polysomnography was recorded via EEG/EMG telemetry. Sleep spindles were evaluated using a custom-made manual scoring system during the first 4 hr of the light cycle. Results Male EKyn, but not female, exhibited a decrease in spindle density compared to ECon (2-wayANOVA: ***P&amp;lt;0.001). FFT spectral power for peak spindle frequency (10-15 Hz) was reduced for all EKyn offspring (3-way ANOVA; frequency x treatment interaction: ****P&amp;lt;0.0001; treatment: *P&amp;lt;0.05). Kynurenine challenge reduced spindle density for both sexes (2-way ANOVA: ***P&amp;lt;0.001; M: **P&amp;lt;0.01; F: *P&amp;lt;0.05). Frequency x treatment interaction for males (2-way ANOVA: ***P&amp;lt;0.001) was observed with lower FFT spectral power for 10-10.5 Hz (*P&amp;lt;0.05) and greater power for 14-14.5 Hz (*P&amp;lt;0.05). Conclusion We determined conspicuous sex differences in spindle dynamics in the EKyn paradigm that may be related to brain KYNA levels; only males exhibited a decrease in spindle density, however all EKyn offspring had reduced FFT spectral power. Kynurenine challenge reduced spindle density in both sexes, however only males had changes in FFT spectral power. Future work will consider the efficacy of KYNA synthesis inhibition to prevent NREM sleep spindle abnormalities induced by KYNA elevation. Support (If Any) Funding Source: National Institute of Health Grants: NIH RO1 NS102209 &amp; P50 MH103222.

Topographical relocation of adolescent sleep spindles reveals a new maturational pattern in the human brain

Current theories of human neural development emphasize the posterior-to-anterior pattern of brain maturation. However, this scenario leaves out significant brain areas not directly involved with sensory input and behavioral control. Suggesting the relevance of cortical activity unrelated to sensory stimulation, such as sleep, we investigated adolescent transformations in the topography of sleep spindles. Sleep spindles are known to be involved in neural plasticity and in adults have a bimodal topography: slow spindles are frontally dominant, while fast spindles have a parietal/precuneal origin. The late functional segregation of the precuneus from the frontoparietal network during adolescence suggests that spindle topography might approach the adult state relatively late in development, and it may not be a result of the posterior-to-anterior maturational pattern. We analyzed the topographical distribution of spindle parameters in HD-EEG polysomnographic sleep recordings of adolescents and found that slow spindle duration maxima traveled from central to anterior brain regions, while fast spindle density, amplitude and frequency peaks traveled from central to more posterior brain regions. These results provide evidence for the gradual posteriorization of the anatomical localization of fast sleep spindles during adolescence and indicate the existence of an anterior-to-posterior pattern of human brain maturation.