Sigma Power Research Articles

Sleep-spindles as a marker of attention and intelligence in dogs

The sleep spindle-generating thalamo-cortical circuitry supports attention capacity in awake humans and animals, but using sleep spindles to predict differences in attention has not been tried in either. Of the more commonly examined cognitive correlates of spindle occurrence and amplitude, post-sleep recall, and general intelligence, only post-sleep recall had been studied in dogs, rats and mice. Here, we examined a sample of companion dogs (N = 58) for whom polysomnographic recordings and several cognitive tests were performed on two occasions each, with a three-month break in-between. Five of the tests were used to extract a factor analogous to human g (general mental ability). A sixth test in the battery measured sustained attention. Both attention and g-factor scores were predicted by higher slow spindle occurrence and absolute sigma power detected in polysomnographic recordings over the central electrode. These effects persisted across measurement occasions. Higher intrinsic spindle frequency was, in turn, linked to lower g-factor scores but displayed no relationship with attention scores. The overlap in localization and direction for the effects of slow spindle density (spindles/minute) and sigma power supports that they tap into the same underlying cognition-relevant aspects of spindling. Given earlier large sample and meta-analysis validations of sigma power as a reliable predictor of cognitive performance in humans, we thus conclude that the currently handled method for quantifying spindle density in dogs indeed measures cognition-relevant spindle activity by virtue of its agreement with the sigma power alternative.

Spectral Dynamics Prior to Motor Events Differ Between NREM Sleep Parasomnias and Healthy Sleepers.

The umbrella term "Disorders of Arousal" (DoA), encompassing sleepwalking, confusional arousals, and sleep terrors, refers to parasomnias manifesting during non-rapid eye movement (NREM) sleep, commonly thought to arise from an aberrant arousal process. While previous studies have detailed EEG changes linked to DoA episodes, it remains uncertain how these alterations differ from a physiological arousal process. This study directly compared brain activity between DoA episodes and arousals associated with physiological movements (motor arousal) in individuals with DoA and healthy sleepers. Fifty-three adult patients with DoA (25 males, 32.2±15.5years) and 33 control subjects (14 males, 31.4±11.4years) underwent one or more home-EEG recordings. A semiparametric regression model was employed to elucidate the complex relationship between EEG activity across channels, within and across different groups, including motor arousals in DoA (n=169), parasomnia episodes in DoA (n=361), and motor arousals in healthy sleepers (n=137). Parasomnia episodes and motor arousals in both groups were preceded by a diffuse increase in slow-wave activity (SWA) and beta power, and a widespread decrease in sigma power. However, motor arousals in DoA displayed lower beta and central sigma than in healthy sleepers. Within DoA patients, episodes were preceded by lower beta, frontal sigma, and higher SWA than motor arousals. Our findings suggest that the arousal process is altered in DOA patients, and that specific EEG patterns are required for DOA episodes to emerge. These insights will help guide future research into the underlying circuits and objective markers of DOA.

Heart Rate Variability During Rapid Eye Movement Sleep is Associated with Reduced Negative Memory Bias.

Emotional memories change over time, but the mechanisms supporting this change are not well understood. Sleep has been identified as one mechanism that supports memory consolidation, with sleep selectively benefitting negative emotional consolidation at the expense of neutral memories, with specific oscillatory events linked to this process. In contrast, the consolidation of neutral and positive memories, compared to negative memories, has been associated with increased vagally-mediated vagal heart rate variability (HRV) during wakefulness. However, how HRV during sleep contributes to emotional memory consolidation remains unexplored. We investigated how sleep oscillations and vagal contributions during sleep contribute to the consolidation of neutral and negative memories. Using a double-blind, placebo-controlled, within-subject, cross-over design, we examined the impact of pharmacological vagal suppression using zolpidem on overnight emotional memory consolidation. Thirty-two participants encoded neutral and negative pictures in the morning, followed by picture recognition tests before and after a night of sleep. Zolpidem or placebo was administered in the evening before overnight sleep, and participants were monitored with electroencephalography and electrocardiography. In the placebo condition, greater overnight improvement for neutral pictures was associated with higher vagal HRV in both Non-Rapid Eye Movement Slow Wave Sleep (NREM SWS) and REM. Additionally, the emotional memory tradeoff (i.e., difference between consolidation of neutral versus negative memories) was associated with higher vagal HRV during REM, but in this case, neutral memories were remembered better than negative memories, indicating a potential role for REM vagal HRV in promoting a positive memory bias overnight. Zolpidem, on the other hand, reduced vagal HRV during SWS, increased NREM sigma power, and eliminated the positive memory bias. Lastly, we used a stepwise linear mixed effects regression to determine how NREM sigma power and vagal HRV during REM independently explained the variance in the emotional memory tradeoff effect. We found that the addition of vagal HRV in combination with sleep significantly improved the model's fit. Overall, our results suggest that sleep brain oscillations and vagal signals synergistically interact in the overnight consolidation of emotional memories, with REM vagal HRV critically contributing to the positive memory bias.

Oscillatory and nonoscillatory sleep electroencephalographic biomarkers of the epileptic network.

In addition to the oscillatory brain activity, the nonoscillatory (scale-free) components of the background electroencephalogram (EEG) may provide further information about the complexity of the underlying neuronal network. As epilepsy is considered a network disease, such scale-free metrics might help to delineate the epileptic network. Here, we performed an analysis of the sleep oscillatory (spindle, slow wave, and rhythmic spectral power) and nonoscillatory (H exponent) intracranial EEG using multiple interictal features to estimate whether and how they deviate from normalcy in 38 adults with drug-resistant epilepsy. To quantify intracranial EEG abnormalities within and outside the seizure onset areas, patients' values were adjusted based on normative maps derived from the open-access Montreal Neurological Institute open iEEG Atlas. In a subset of 29 patients who underwent resective surgery, we estimated the predictive value of these features to identify the epileptogenic zone in those with a good postsurgical outcome. We found that distinct sleep oscillatory and nonoscillatory metrics behave differently across the epileptic network, with the strongest differences observed for (1) a reduction in spindle activity (spindle rates and rhythmic sigma power in the 10-16 Hz band), (2) a higher rhythmic gamma power (30-80 Hz), and (3) a higher H exponent (steeper 1/f slope). As expected, epileptic spikes were also highest in the seizure onset areas. Furthermore, in surgical patients, the H exponent achieved the highest performance (balanced accuracy of .76) for classifying resected versus nonresected channels in good outcome patients. This work suggests that nonoscillatory components of the intracranial EEG signal could serve as promising interictal sleep candidates of epileptogenicity in patients with drug-resistant epilepsy. Our findings further advance the understanding of epilepsy as a disease, whereby absence or loss of sleep physiology may provide information complementary to pathological epileptic processes.

The timing of sleep spindles is modulated by the respiratory cycle in humans

ObjectiveCoupling of sleep spindles with cortical slow waves and hippocampus sharp-waves ripples is crucial for sleep-related memory consolidation. Recent literature evidenced that nasal respiration modulates neural activity in large-scale brain networks. In rodents, this respiratory drive strongly varies according to vigilance states. Whether sleep oscillations are also respiration-modulated in humans remains open. In this work, we investigated the influence of breathing on sleep spindles during non-rapid-eye-movement sleep in humans. MethodsFull night polysomnography of twenty healthy participants were analysed. Spindles and slow waves were automatically detected during N2 and N3 stages. Spindle-related sigma power as well as spindle and slow wave events were analysed according to the respiratory phase. ResultsWe found a significant coupling between both slow and fast spindles and the respiration cycle, with enhanced sigma activity and occurrence probability of spindles during the middle part of the expiration phase. A different coupling was observed for slow waves negative peaks which were rather distributed around the two respiration phase transitions. ConclusionOur findings suggest that breathing cycle influences the dynamics of brain activity during non-rapid-eye-movement sleep. SignificanceThis coupling may enable sleep spindles to synchronize with other sleep oscillations and facilitate information transfer between distributed brain networks.

Possible mechanisms to improve sleep spindles via closed loop stimulation during slow wave sleep: A computational study.

Sleep spindles are one of the prominent EEG oscillatory rhythms of non-rapid eye movement sleep. In the memory consolidation, these oscillations have an important role in the processes of long-term potentiation and synaptic plasticity. Moreover, the activity (spindle density and/or sigma power) of spindles has a linear association with learning performance in different paradigms. According to the experimental observations, the sleep spindle activity can be improved by closed loop acoustic stimulations (CLAS) which eventually improve memory performance. To examine the effects of CLAS on spindles, we propose a biophysical thalamocortical model for slow oscillations (SOs) and sleep spindles. In addition, closed loop stimulation protocols are applied on a thalamic network. Our model results show that the power of spindles is increased when stimulation cues are applied at the commencing of an SO Down-to-Up-state transition, but that activity gradually decreases when cues are applied with an increased time delay from this SO phase. Conversely, stimulation is not effective when cues are applied during the transition of an Up-to-Down-state. Furthermore, our model suggests that a strong inhibitory input from the reticular (RE) layer to the thalamocortical (TC) layer in the thalamic network shifts leads to an emergence of spindle activity at the Up-to-Down-state transition (rather than at Down-to-Up-state transition), and the spindle frequency is also reduced (8-11 Hz) by thalamic inhibition.

Neuronal PAS domain 1 identifies a major subpopulation of wakefulness-promoting GABAergic neurons in the basal forebrain

Here, we describe a group of basal forebrain (BF) neurons expressing neuronal Per-Arnt-Sim (PAS) domain 1 (Npas1), a developmental transcription factor linked to neuropsychiatric disorders. Immunohistochemical staining in Npas1-cre-2A-TdTomato mice revealed BF Npas1+ neurons are distinct from well-studied parvalbumin or cholinergic neurons. Npas1 staining in GAD67-GFP knock-in mice confirmed that the vast majority of Npas1+ neurons are GABAergic, with minimal colocalization with glutamatergic neurons in vGlut1-cre-tdTomato or vGlut2-cre-tdTomato mice. The density of Npas1+ neurons was high, five to six times that of neighboring cholinergic, parvalbumin, or glutamatergic neurons. Anterograde tracing identified prominent projections of BF Npas1+ neurons to brain regions involved in sleep-wake control, motivated behaviors, and olfaction such as the lateral hypothalamus, lateral habenula, nucleus accumbens shell, ventral tegmental area, and olfactory bulb. Chemogenetic activation of BF Npas1+ neurons in the light period increased the amount of wakefulness and the latency to sleep for 2 to 3 h, due to an increase in long wake bouts and short NREM sleep bouts. NREM slow-wave and sigma power, as well as sleep spindle density, amplitude, and duration, were reduced, reminiscent of findings in several neuropsychiatric disorders. Together with previous findings implicating BF Npas1+ neurons in stress responsiveness, the anatomical projections of BF Npas1+ neurons and the effect of activating them suggest a possible role for BF Npas1+ neurons in motivationally driven wakefulness and stress-induced insomnia. Identification of this major subpopulation of BF GABAergic neurons will facilitate studies of their role in sleep disorders, dementia, and other neuropsychiatric conditions involving BF.

Dampened circadian amplitude of EEG power in women after menopause.

Postmenopausal women are at high risk of developing sleep-wake disturbances. We previously reported dampened circadian rhythms of melatonin, alertness and sleep in postmenopausal compared with young women. The present study aims to further explore electroencephalography power spectral changes in the sleep of postmenopausal women. Eight healthy postmenopausal women were compared with 12 healthy, naturally ovulating, young women in their mid-follicular phase. Participants followed a regular 8-hr sleep schedule for ≥ 2 weeks prior to laboratory entry. The laboratory visit included an 8-hr baseline sleep period followed by an ultradian sleep-wake cycle procedure, consisting of alternating 1-hr wake periods and nap opportunities. Electroencephalography power spectral analysis was performed on non-rapid eye movement sleep obtained over a 48-hr period. The baseline nocturnal sleep of postmenopausal women comprised lower power within delta and sigma, and higher power within alpha bands compared with that of younger women. During nighttime naps of the ultradian sleep-wake cycle procedure, lower power within delta and sigma, and higher power within beta bands were observed in postmenopausal women. During the ultradian sleep-wake cycle procedure, postmenopausal women presented lower power of delta, theta and sigma (14-15 Hz), undetectable rhythms of delta and theta, and a dampened or undetectable rhythm of sigma (12-15 Hz) power compared with younger women. Our results support the hypothesis of a dampened circadian variation of sleep microstructure in healthy-sleeping postmenopausal women. Circadian changes with aging are potential mechanisms for increased susceptibility to develop sleep disturbances; however, further research is needed to clarify their clinical implications and contribution to insomnia.

Objective sleep quality predicts subjective sleep ratings

In both clinical and observational studies, sleep quality is usually assessed by subjective self-report. The literature is mixed about how accurately these self-reports track objectively (e.g. via polysomnography) assessed sleep quality, with frequent reports of little to no association. However, previous research on this question focused on between-subject designs, which may be confounded by trait-level variables. In the current study, we used the novel Budapest Sleep, Experiences and Traits Study (BSETS) dataset to investigate if within-subject differences in subjectively reported sleep quality are related to sleep macrostructure and quantitative EEG variables assessed using a mobile EEG headband. We found clear evidence that self-reported sleep quality in the morning is influenced by within-subject variations in sleep onset latency, wake after sleep onset, total sleep time, and sleep efficiency. These effects were replicated if detailed sleep composition metrics (percentage and latency of specific vigilance states) or two alternative measures of subjective sleep quality were used instead. We found no effect of the number of awakenings or relative EEG delta and sigma power. Between-subject effects (relationships between individual mean values of sleep metrics and subjective sleep quality) were also found, highlighting that analyses focusing only on these may be erroneous. Our findings show that while previous investigations of this issue may have been confounded by between-subject effects, objective sleep quality is indeed reflected in subjective sleep ratings.

Sleep Physiology and Neurocognition Among Adolescents With Attention-Deficit/Hyperactivity Disorder

Few studies have characterized the nature of sleep problems among adolescents with attention-deficit/hyperactivity disorder (ADHD) using polysomnography (PSG). Additionally, although adolescents with ADHD and adolescents with sleep disturbances display similar neurocognitive deficits, the role of sleep in contributing to neurocognitive impairment in adolescent ADHD is unknown. This study investigated differences in PSG-measured sleep among adolescents with ADHD compared with non-psychiatric controls and associations with neurocognition. Medication-free adolescents aged 13 to 17 (N = 62, n= 31 with ADHD; mean age= 15.3 years; 50% female) completed a diagnostic evaluation, 3 nights of ambulatory PSG, the Cambridge Neuropsychological Test Automated Battery, and subjective reports of sleep and executive functioning. Linear regressions covarying for age, sex, and pubertal status examined group differences in sleep indices, and partial Pearson correlations assessed relations between sleep and neurocognition. Although adolescents with ADHD did not exhibit differences in PSG-measured sleep duration, awakenings, or latency (ps > .05) compared with non-psychiatric controls, they displayed lower slow wave sleep percentage (β=-.40) and non-rapid eye movement (NREM) electroencephalogram (EEG) delta power (β=-.29). They also exhibited greater stage 2 percentage (β= .41), NREM EEG sigma power (β= .41), and elevated self-reported sleep disturbances (ps< .05). Lower NREM EEG delta power, increased high-frequency power, and slower decline in NREM EEG delta power overnight were associated with poorer neurocognition among adolescents with ADHD. Adolescents with ADHD reported more sleep disturbances than non-psychiatric controls and exhibited differences in sleep stage distribution and NREM sleep EEG frequency. Sleep-EEG spectral indices were associated with impaired neurocognition, suggesting that physiological sleep processes may underlie neurocognitive deficits in ADHD. Future studies may clarify whether sleep plays a causal role in neurocognitive impairments in adolescent ADHD and whether interventions normalizing sleep improve neurocognition. Sleep Dysfunction and Neurocognitive Outcomes in Adolescent ADHD; https://clinicaltrials.gov/; NCT02897362. We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. We actively worked to promote sex and gender balance in our author group. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list.

An examination of sleep spindle metrics in the Sleep Heart Health Study: superiority of automated spindle detection over total sigma power in assessing age-related spindle decline

BackgroundSleep spindle activity is commonly estimated by measuring sigma power during stage 2 non-rapid eye movement (NREM2) sleep. However, spindles account for little of the total NREM2 interval and therefore sigma power over the entire interval may be misleading. This study compares derived spindle measures from direct automated spindle detection with those from gross power spectral analyses for the purposes of clinical trial design.MethodsWe estimated spindle activity in a set of 8,440 overnight electroencephalogram (EEG) recordings from 5,793 patients from the Sleep Heart Health Study using both sigma power and direct automated spindle detection. Performance of the two methods was evaluated by determining the sample size required to detect decline in age-related spindle coherence with each method in a simulated clinical trial.ResultsIn a simulated clinical trial, sigma power required a sample size of 115 to achieve 95% power to identify age-related changes in sigma coherence, while automated spindle detection required a sample size of only 60.ConclusionsMeasurements of spindle activity utilizing automated spindle detection outperformed conventional sigma power analysis by a wide margin, suggesting that many studies would benefit from incorporation of automated spindle detection. These results further suggest that some previous studies which have failed to detect changes in sigma power or coherence may have failed simply because they were underpowered.

Multivariate prediction of cognitive performance from the sleep electroencephalogram

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

Sleep spindles across youth affected by schizophrenia or anti-N-methyl-D-aspartate-receptor encephalitis.

Sleep disturbances are intertwined with the progression and pathophysiology of psychotic symptoms in schizophrenia. Reductions in sleep spindles, a major electrophysiological oscillation during non-rapid eye movement sleep, have been identified in patients with schizophrenia as a potential biomarker representing the impaired integrity of the thalamocortical network. Altered glutamatergic neurotransmission within this network via a hypofunction of the N-methyl-D-aspartate receptor (NMDAR) is one of the hypotheses at the heart of schizophrenia. This pathomechanism and the symptomatology are shared by anti-NMDAR encephalitis (NMDARE), where antibodies specific to the NMDAR induce a reduction of functional NMDAR. However, sleep spindle parameters have yet to be investigated in NMDARE and a comparison of these rare patients with young individuals with schizophrenia and healthy controls (HC) is lacking. This study aims to assess and compare sleep spindles across young patients affected by Childhood-Onset Schizophrenia (COS), Early-Onset Schizophrenia, (EOS), or NMDARE and HC. Further, the potential relationship between sleep spindle parameters in COS and EOS and the duration of the disease is examined. Sleep EEG data of patients with COS (N = 17), EOS (N = 11), NMDARE (N = 8) aged 7-21 years old, and age- and sex-matched HC (N = 36) were assessed in 17 (COS, EOS) or 5 (NMDARE) electrodes. Sleep spindle parameters (sleep spindle density, maximum amplitude, and sigma power) were analyzed. Central sleep spindle density, maximum amplitude, and sigma power were reduced when comparing all patients with psychosis to all HC. Between patient group comparisons showed no differences in central spindle density but lower central maximum amplitude and sigma power in patients with COS compared to patients with EOS or NMDARE. Assessing the topography of spindle density, it was significantly reduced over 15/17 electrodes in COS, 3/17 in EOS, and 0/5 in NMDARE compared to HC. In the pooled sample of COS and EOS, a longer duration of illness was associated with lower central sigma power. Patients with COS demonstrated more pronounced impairments of sleep spindles compared to patients with EOS and NMDARE. In this sample, there is no strong evidence that changes in NMDAR activity are related to spindle deficits.

0588 DNS and Sleep-Dependent Memory Consolidation in Pediatric Narcolepsy Type 1

Abstract Introduction Disrupted nighttime sleep (DNS) is common in narcolepsy type 1 (NT1), yet its impact on cognitive function is unknown. Given known associations between sleep-dependent memory consolidation and N2 sleep spindles, we hypothesized that NT1 impairs memory consolidation, due to fragmented N2 sleep and altered N2 sleep spindles in the NT1 group. Methods In this case-control study, we trained n=23 NT1 participants [mean age 15.8 years (3.2)] and n=28 healthy control (HC) patients [13.6 years (3.7)] to criterion on a spatial declarative memory task before a nocturnal in-lab polysomnogram and then gave them a cued recall test upon awakening in the morning. NT1 participants could take SSRI/SNRI medication for cataplexy but were weaned off wake-promoting medications and excluded if on an oxybate. We extracted wake and sleep stage bout numbers from sleep and N2 spindle characteristics from the polysomnogram and conducted linear regression with memory consolidation results across groups. Results Adjusting for age, NT1 participants had longer sleep duration than HC, more N1%, lower N3%, higher Wake/N1 Index, as well as more bouts per hour of Wake, N1, N2, REM than controls (p’s &amp;lt; 0.04). Compared to HC, NT1 subjects had similar N2 spindle density, amplitude, and sigma power, but shorter duration of N2 spindles (p=0.009). More NT1 participants could not meet performance criterion on the initial learning task and required an easier memory task vs. HC (p=0.02) despite being older than HC. NT1 participants showed a trend for impaired memory consolidation vs. HC across a night of sleep after adjusting for age, gender, and total sleep time (p=0.07). Across groups, shorter N2 spindle duration (p=0.02) but not increased N2 bout number was associated with worse sleep-dependent memory consolidation. Conclusion Compared to controls, NT1 participants showed encoding difficulties but only a trend difference in memory consolidation despite greater sleep fragmentation. NT1 participants had briefer N2 sleep spindles and overall, these shorter N2 spindles were associated with greater memory consolidation deficits. Future sleep therapeutic studies are needed to determine if sleep-dependent memory consolidation can be improved to address daytime cognitive problems in NT1 patients. Support (if any) Jazz Pharmaceuticals and National Institutes of Health grant 5K23NS104267-2

0751 Early Childhood Sleep Associated with Adolescent Sleep Physiology among Youth with ADHD

Abstract Introduction Sleep complaints are prevalent and impairing symptoms among adolescents with ADHD. Our recent work has shown that key aspects of sleep physiology differentiate adolescents with ADHD from healthy controls (HC), including reduced slow-wave sleep percentage (SWS%) and relative delta power (rDelta) and increased stage 2 percentage (N2%) and relative sigma power (rSigma) after accounting for sleep duration. ADHD-related sleep problems may emerge as early as toddlerhood, yet little is known about the trajectory of sleep disturbances over time in ADHD. The current study examines relationships between early childhood sleep problems and adolescent sleep physiology in ADHD and HC. Methods Sixty-two medication-free adolescents (31 with ADHD, mean age=15.3, 50% female) completed a diagnostic interview (Mini International Neuropsychiatric Interview) and 3 nights of at-home polysomnography. Spectral analysis was conducted on a single O1-C3 channel. Caregivers reported on participants’ sleep problems during toddlerhood and preschool (Child Behavior Questionnaire; CBQ). Linear regressions controlling for age, sex, and pubertal status examined relationships between early childhood sleep problems and aspects of sleep physiology implicated in adolescent ADHD (SWS%, rDelta, N2%, rSigma) and whether associations differed between groups. Results Adolescents with ADHD had greater caregiver-reported early childhood sleep problems compared to HC (t(60)=3.71, p&amp;lt;.001). In the full sample, greater caregiver-reported sleep problems in early childhood were associated with reduced SWS% (β=-.28, p=.04) and rDelta (β=-.27, p=.04), and increased rSigma (β=.33, p=.02), in adolescence. An early childhood sleep by group interaction was observed for rDelta (β=1.09, p=.04), such that the association was significantly stronger for adolescents with ADHD than HC. Conclusion The current study found that sleep problems in early development were associated with disruptions in sleep physiology in adolescents, including relatively less time spent in SWS, reduced delta power, and increased sigma power. Results suggest that ADHD-related sleep problems may begin early in life and persist into adolescence. Screening for and treating sleep problems during early development may be important for supporting sleep health among adolescents with ADHD, and future studies should assess this possibility. Future studies employing longitudinal designs may clarify the contribution of sleep disturbances to the onset and persistence of ADHD symptoms across development. Support (if any) K23MH108704; R34MH128440

0409 Is insomnia with objective short sleep duration related to insufficient sleep drive or physiological hyperarousal?

Abstract Introduction IInsomnia with objective short sleep duration (OSSD) was found to be associated with higher risks of cardiometabolic disorders, and was therefore proposed to be a phenotype associated with higher physiological hyperarousal. Previous studies further reported that insomnia with OSSD had higher autonomic arousal as measured by heart rate variability (HRV) during sleep. Since sleep duration could be determined by the interplay of arousal and sleep drive and HRV during sleep could be influenced by sleep staging and quality, the present study examined the level of arousal and sleep drive prior to sleep with EEG power and HRV to further understand the phenotyping of insomnia. Methods Ninety-four insomnia patients participated in the study and went through one night of 8-hour PSG recording. They were divided, with a cut-off of PSG total sleep time of 6 hours, into two groups: an OSSD group (N=26; mean age=37.0 ±10.3; M:F=7:19; TST=286.21±87.21 min) and an objective normal sleep duration (ONSD) group (N=68, mean age=32.95 ±10.05, M:F=12: 56, TST=414.4±28.9 min). Resting-state EEG and EKG were recorded for a 6-min period, 3-min eye-opened (EO) with fixation focus and 3 mins eye-closed (EC), prior to bedtime. Results T-tests showed no significant difference in HRV measures (SDNN, RMSD, LF, HF, LF/HF) between the two groups, but shorter R-R interval for OSSD group than ONSD group. Mann-Whitney tests for EEG power showed significantly lower theta power at F3, F4, C3, C4, and O2, and higher sigma power at F3, C3, C4, O1, and O2 during EC, as well as lower theta power at C3 and higher sigma power at O2 during EO for OSSD group in comparison to ONSD group. Conclusion The results partially support that insomnia with OSSD is associated with physiological hyperarousal as indicated by faster heart rate and higher high frequency EEG power prior to sleep. However, the lower EEG theta power prior to sleep suggest that lower homeostatic sleep drive may also play a role for the insomnia with short objective sleep duration. Support (if any) Supported by Taiwan National Science and Technology Council

Longitudinal trajectories of spectral power during sleep in middle-aged and older adults.

Age-related changes in sleep appear to contribute to cognitive aging and dementia. However, most of the current understanding of sleep across the lifespan is based on cross-sectional evidence. Using data from the Sleep Heart Health Study, we investigated longitudinal changes in sleep micro-architecture, focusing on whether such age-related changes are experienced uniformly across individuals. Participants were 2,202 adults (ageBaseline=62.40±10.38, 55.36% female, 87.92% White) who completed home polysomnography assessment at two study visits, which were 5.23years apart (range: 4-7years). We analyzed NREM and REM spectral power density for each 0.5Hz frequency bin, including slow oscillation (0.5-1Hz), delta (1-4Hz), theta (4-8Hz), alpha (8-12Hz), sigma (12-15Hz), and beta-1 (15-20Hz) bands. Longitudinal comparisons showed a 5-year decline in NREM delta (p<.001) and NREM sigma power density (p<.001) as well as a 5-year increase in theta power density during NREM (p=.001) and power density for all frequency bands during REM sleep (ps<0.05). In contrast to the notion that sleep declines linearly with advancing age, longitudinal trajectories varied considerably across individuals. Within individuals, the 5-year changes in NREM and REM power density were strongly correlated (slow oscillation: r=0.46; delta: r=0.67; theta r=0.78; alpha r=0.66; sigma: r=0.71; beta-1: r=0.73; ps<0.001). The convergence in the longitudinal trajectories of NREM and REM activity may reflect age-related neural de-differentiation and/or compensation processes. Future research should investigate the neurocognitive implications of longitudinal changes in sleep micro-architecture and test whether interventions for improving key sleep micro-architecture features (such as NREM delta and sigma activity) also benefit cognition over time.

Updating memories of unwanted emotions during human sleep

Post-learning sleep contributes to memory consolidation. Yet it remains contentious whether sleep affords opportunities to modify or update emotional memories, particularly when people would prefer to forget those memories. Here, we attempted to update memories during sleep, using spoken positive words paired with cues to recent memories of aversive events. Affective updating using positive words during human non-rapid eye movement (NREM) sleep, compared with using neutral words instead, reduced negative affective judgments in post-sleep tests, suggesting that the recalled events were perceived as less aversive. Electroencephalogram (EEG) analyses showed that positive words modulated theta and spindle/sigma activity; specifically, to the extent that theta power was larger for the positive words than for the memory cues that followed, participants judged the memory cues less negatively. Moreover, to the extent that sigma power was larger for the positive words than for the memory cues that followed, participants forgot more episodic details about aversive events. Notably, when the onset of individual positive words coincided with the up-phase of slow oscillations (a state characterized by increased cortical excitability during NREM sleep), affective updating was more successful. In sum, we altered the affective content of memories via the strategic pairing of positive words and memory cues during sleep, linked with EEG theta power increases and theslow oscillation up-phase. These findings suggest novel possibilities for modifying unwanted memories during sleep, which would not require people to consciously confront memories that they prefer to avoid.

Association Between Sleep Microstructure and Incident Hypertension in a Population-Based Sample: The HypnoLaus Study.

Background Poor sleep quality is associated with increased incident hypertension. However, few studies have investigated the impact of objective sleep structure parameters on hypertension. This study investigated the association between sleep macrostructural and microstructural parameters and incident hypertension in a middle- to older-aged sample. Methods and Results Participants from the HypnoLaus population-based cohort without hypertension at baseline were included. Participants had at-home polysomnography at baseline, allowing assessment of sleep macrostructure (nonrapid eye movement sleep stages 1, 2, and 3; rapid eye movement sleep stages; and total sleep time) and microstructure including power spectral density of electroencephalogram in nonrapid eye movement sleep and spindles characteristics (density, duration, frequency, amplitude) in nonrapid eye movement sleep stage 2. Associations between sleep macrostructure and microstructure parameters at baseline and incident clinical hypertension over a mean follow-up of 5.2years were assessed with multiple-adjusted logistic regression. A total of 1172 participants (42% men; age 55±10years) were included. Of these, 198 (17%) developed hypertension. After adjustment for confounders, no sleep macrostructure features were associated with incident hypertension. However, low absolute delta and sigma power were significantly associated with incident hypertension where participants in the lowest quartile of delta and sigma had a 1.69-fold (95% CI, 1.00-2.89) and 1.72-fold (95% CI, 1.05-2.82) increased risk of incident hypertension, respectively, versus those in the highest quartile. Lower spindle density (odds ratio, 0.87; 95% CI, 0.76-0.99) and amplitude (odds ratio, 0.98; 95% CI, 0.95-1.00) were also associated with higher incident hypertension. Conclusions Sleep microstructure is associated with incident hypertension. Slow-wave activity and sleep spindles, 2 hallmarks of objective sleep continuity and quality, were inversely and consistently associated with incident hypertension. This supports the protective role of sleep continuity in the development of hypertension.

Sigma oscillations protect or reinstate motor memory depending on their temporal coordination with slow waves.

Targeted memory reactivation (TMR) during post-learning sleep is known to enhance motor memory consolidation but the underlying neurophysiological processes remain unclear. Here, we confirm the beneficial effect of auditory TMR on motor performance. At the neural level, TMR enhanced slow wave (SW) characteristics. Additionally, greater TMR-related phase-amplitude coupling between slow (0.5-2 Hz) and sigma (12-16 Hz) oscillations after the SW peak was related to higher TMR effect on performance. Importantly, sounds that were not associated to learning strengthened SW-sigma coupling at the SW trough. Moreover, the increase in sigma power nested in the trough of the potential evoked by the unassociated sounds was related to the TMR benefit. Altogether, our data suggest that, depending on their precise temporal coordination during post learning sleep, slow and sigma oscillations play a crucial role in either memory reinstatement or protection against irrelevant information; two processes that critically contribute to motor memory consolidation.