NREM Sleep EEG Research Articles

High-density EEG recordings in the European jackdaw (Coloeus monedula): sleep deprivation increases NREM sleep time and EEG power while reducing hemispheric asymmetry

High-density EEG recordings in the European jackdaw (Coloeus monedula): sleep deprivation increases NREM sleep time and EEG power while reducing hemispheric asymmetry

Cortical miR-709 links glutamatergic signaling to NREM sleep EEG slow waves in an activity-dependent manner.

MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression that have been implicated in a plethora of neuronal processes. Nevertheless, their role in regulating brain activity in the context of sleep has so far received little attention. To test their involvement, we deleted mature miRNAs in post-mitotic neurons at two developmental ages, i.e., in early adulthood using conditional Dicer knockout (cKO) mice and in adult mice using an inducible conditional Dicer cKO (icKO) line. In both models, electroencephalographic (EEG) activity was affected and the response to sleep deprivation (SD) altered; while the rapid-eye-movement sleep (REMS) rebound was compromised in both, the increase in EEG delta (1 to 4 Hz) power during non-REMS (NREMS) was smaller in cKO mice and larger in icKO mice compared to controls. We subsequently investigated the effects of SD on the forebrain miRNA transcriptome and found that the expression of 48 miRNAs was affected, and in particular that of the activity-dependent miR-709. In vivo inhibition of miR-709 in the brain increased EEG power during NREMS in the slow-delta (0.75 to 1.75 Hz) range, particularly after periods of prolonged wakefulness. Transcriptome analysis of primary cortical neurons in vitro revealed that miR-709 regulates genes involved in glutamatergic neurotransmission. A subset of these genes was also affected in the cortices of sleep-deprived, miR-709-inhibited mice. Our data implicate miRNAs in the regulation of EEG activity and indicate that miR-709 links neuronal activity during wakefulness to brain synchrony during sleep through the regulation of glutamatergic signaling.

Correlation between NREM Sleep EEG characteristics and Mild Cognitive Impairment in patients with Parkinson’s disease

Correlation between NREM Sleep EEG characteristics and Mild Cognitive Impairment in patients with Parkinson’s disease

Associations of Baseline Sleep Microarchitecture with Cognitive Function After 8 Years in Middle-Aged and Older Men from a Community-Based Cohort Study.

Prospective studies examining associations between baseline sleep microarchitecture and future cognitive function recruited from small samples with predominantly short follow-up. This study examined sleep microarchitecture predictors of cognitive function (visual attention, processing speed, and executive function) after 8 years in community-dwelling men. Florey Adelaide Male Ageing Study participants (n=477) underwent home-based polysomnography (2010-2011), with 157 completing baseline (2007-2010) and follow-up (2018-2019) cognitive assessments (trail-making tests A [TMT-A] and B [TMT-B] and the standardized mini-mental state examination [SMMSE]). Whole-night F4-M1 sleep EEG recordings were processed following artifact exclusion, and quantitative EEG characteristics were obtained using validated algorithms. Associations between baseline sleep microarchitecture and future cognitive function (visual attention, processing speed, and executive function) were examined using linear regression models adjusted for baseline obstructive sleep apnoea, other risk factors, and cognition. The final sample included men aged (mean [SD]) 58.9 (8.9) years at baseline, overweight (BMI 28.5 [4.2] kg/m2), and well educated (75.2% ≥Bachelor, Certificate, or Trade), with majorly normal baseline cognition. Median (IQR) follow-up was 8.3 (7.9, 8.6) years. In adjusted analyses, NREM and REM sleep EEG spectral power was not associated with TMT-A, TMT-B, or SMMSE performance (all p>0.05). A significant association of higher N3 sleep fast spindle density with worse TMT-B performance (B=1.06, 95% CI [0.13, 2.00], p=0.026) did not persist following adjustment for baseline TMT-B performance. In this sample of community-dwelling men, sleep microarchitecture was not independently associated with visual attention, processing speed, or executive function after 8 years.

Retracted: NREM Sleep EEG Characteristics Correlate to the Mild Cognitive Impairment in Patients with Parkinsonism

Retracted: NREM Sleep EEG Characteristics Correlate to the Mild Cognitive Impairment in Patients with Parkinsonism

Season is related to the slow wave and sigma activity of infants and toddlers

Objective/BackgroundSlow wave activity (SWA) and sigma frequency activity (SFA) are hallmarks of NREM sleep EEG and important indicators of neural plasticity, development of the central nervous system, and cognition. However, little is known about the factors that modulate these sleep EEG activities, especially in small children. Patients/methodsWe analyzed the power spectral densities of SWA (1–4 Hz) and SFA range (10–15 Hz) from six EEG derivations of 56 infants (8 months) and 60 toddlers (24 months) during their all-night sleep and during the first and the last half of night sleep. The spectral values were compared between the four seasons. ResultsIn the spring group of infants, compared with the darker seasons, SFA was lower in the centro-occipital EEG derivations during both halves of the night. The SWA findings of the infants were restricted to the last half of the night (SWA2) and frontally, where SWA2 was higher during winter than spring. The toddlers presented less frontal SWA2 during winter compared with autumn. Both age groups showed a reduction in both SWA and SFA towards the last half of the night. ConclusionsThe sleep EEG spectral power densities are more often associated with seasons in infants’ SFA range. The results might stem from seasonally changing light exposure, but the exact mechanism warrants further study. Moreover, contrary to the adult-like increment of SFA, the SFA at both ages was lower at the last part of the night sleep. This suggests different regulation of spindle activity in infants and toddlers.

The Fingerprint-Like Pattern of Nocturnal Brain Activity Demonstrated in Young Individuals is Also Present in Senior Adulthood.

PurposeThe quantitative sleep EEG has been considered as electroencephalographic “fingerprint”, ie, it is stable within but differs between individuals. So far, however, almost all studies addressing this aspect have been conducted in young men. It was therefore of interest to know whether the sleep EEG fingerprint concept holds true in older samples of both sexes.Patients and MethodsData from three different subsamples of 30 healthy individuals each were reused for the present secondary analysis (young men (YM) = 25.6 ± 2.4 years, elderly men (EM) = 69.1 ± 5.5 years, elderly women (EW) = 67.8 ± 5.7 years). Individuals slept ten times in the sleep laboratory, resulting in a total of 900 study nights. However, to avoid misinterpretation due to intervention-related changes in sleep EEG power spectra, only the 3 sham nights without any intervention were included, reducing the datasets to 270. To determine stability of NREM sleep EEG power spectra between sham night pairs, within- and between-subject Manhattan distance measures were computed separately by sample.ResultsRegardless of subsample and sham night pair, lowest distance measures, ie, largest similarity, were observed for within-subject power spectra comparisons (range of mean distance measures for EW from 3.82 to 4.06, for EM from 3.55 to 3.63, and for YM from 3.04 to 3.62). Moreover, intraindividual similarity did not differ substantially between samples. Between-subject power spectra distance measures were considerably larger (range of mean distance measures for EW from 12.95 to 13.15, for EM from 12.21 to 12.57, and for YM from 10.33 to 10.78) and varied significantly between young and elderly individuals.ConclusionThe present results support the view that the sleep EEG power spectrum is an individual trait-like characteristic that remains unique up until old age. This finding may help to increase the sensitivity in measuring intervention effects.

P143 Sleep-dependent declarative memory consolidation and NREM sleep EEG oscillations in older adults with obstructive sleep apnea

Abstract Objectives To compare overnight declarative memory consolidation and NREM sleep EEG oscillations in older adults with OSA to an age-matched control group, and to assess the quantitative sleep EEG features as correlates of memory consolidation. Methods 46 participants (24 without OSA and 22 patients with OSA) were recruited. Participants completed a word-paired associates declarative memory task before and after an 8-hour sleep opportunity with full polysomnography. Power spectral analysis was performed on all-night EEG recorded at frontal and central electrode sites. We calculated slow wave activity (slow oscillations absolute power 0.25–1 Hz; and delta EEG power (0.5–4.5 Hz) in NREM sleep. Slow spindle density (11–13 Hz, events p/min) and fast spindle density (13–16 Hz, events p/min) in stage N2 was derived using an automated spindle detection algorithm. Results Patients with OSA showed no significant differences in overnight memory recall and recognition compared to individuals without OSA. The OSA group showed reduced slow spindle density at the central region and fast spindle density at the frontal region relative to controls. No differences were observed in SWA. Within group correlations showed slow and fast spindle density were correlated to percent recognition in the control group. Conclusion Older adults with OSA had deficits in slow and fast sleep spindles compared to controls. OSA patients showed preserved sleep-dependent declarative memory consolidation despite sleep fragmentation and intermittent hypoxemia. Sleep spindles were positively correlated with overnight memory consolidation in controls but not OSA patients. Targeted interventions to boost spindles may enhance memory consolidation in older adults.

Spike-Wave Index Assessment and Electro-Clinical Correlation in Patients with Encephalopathy Associated with Epileptic State During Slow Sleep (ESES / CSWS); Single-Center Experience

PurposeThis study aimed to describe the electroclinical spectrum and neurocognitive outcome in children with epileptic encephalopathy with status epilepticus during sleep (ESES) according to the EEG patterns. MethodsRecords of 48 (19 males, 29 females) patients with ESES/CSWS syndrome were retrospectively evaluated for data on sleep and awake EEGs, psychometric tests, and brain MRI. Patients with a spike-wave index (SWI) of at least 50 % in the NREM sleep EEG were included in the study. Electrophysiologic findings were separated into two groups based on SWI: SWI>85-100 % (typical ESES) and SWI < 85 % (atypical ESES). The neurocognitive prognosis was also evaluated in two groups; favorable and unfavorable. ResultsThe median age at the onset of ESES was 6 years and 5 months and ranged from 3 to 13 years. The median duration of follow-up after the ESES diagnosis was 57 months (range 24–150 months). Etiology was evaluated in three groups: symptomatic/structural, idiopathic, and unknown (cryptogenic). Twenty-seven (56.25 %) patients had atypical ESES patterns and 21 patients (43.75 %) had typical ESES patterns. Twenty-eight patients (58.3 %) had cognitive deterioration. Long term neurocognitive outcome was unfavorable in half of the patients. Symptomatic/structural etiology was more common in patients with unfavorable (p < 0.001) outcomes. The median age at the diagnosis of ESES (p < 0.001) was significantly earlier in the patients with unfavorable neurocognitive outcomes. The longer duration of ESES(p < 0.001), and the longer time between the onset of epilepsy and ESES (p = 0.039) was significantly associated with unfavorable outcomes. We found that patients with typical ESES had a higher risk for poor neurocognitive outcomes than patients with atypical ESES (OR: 31.096 [1.565–617.696]). ConclusionThe long-term outcome of ESES is exceedingly variable. An unfavorable neurocognitive outcome seems to be related to ESES with a long-duration and early-onset epileptic activity, SWI ≥ 85 %, and etiology.

The laminar profile of sleep spindles in humans

Sleep spindles are functionally important NREM sleep EEG oscillations which are generated in thalamocortical, corticothalamic and possibly cortico-cortical circuits. Previous hypotheses suggested that slow and fast spindles or spindles with various spatial extent may be generated in different circuits with various cortical laminar innervation patterns. We used NREM sleep EEG data recorded from four human epileptic patients undergoing presurgical electrophysiological monitoring with subdural electrocorticographic grids (ECoG) and implanted laminar microelectrodes penetrating the cortex (IME). The position of IMEs within cortical layers was confirmed using postsurgical histological reconstructions. Many spindles detected on the IME occurred only in one layer and were absent from the ECoG, but with increasing amplitude simultaneous detection in other layers and on the ECoG became more likely. ECoG spindles were in contrast usually accompanied by IME spindles. Neither IME nor ECoG spindle cortical profiles were strongly associated with sleep spindle frequency or globality. Multiple-unit and single-unit activity during spindles, however, was heterogeneous across spindle types, but also across layers and patients. Our results indicate that extremely local spindles may occur in any cortical layer, but co-occurrence at other locations becomes likelier with increasing amplitude and the relatively large spindles detected on ECoG channels have a stereotypical laminar profile. We found no compelling evidence that different spindle types are associated with different laminar profiles, suggesting that they are generated in cortical and thalamic circuits with similar cortical innervation patterns. Local neuronal activity is a stronger candidate mechanism for driving functional differences between spindles subtypes.

Non-REM sleep instability in children with restless sleep disorder

Study objectivesRestless sleep disorder (RSD) is a newly recognized condition characterized by motor movements involving large muscle groups with frequent repositioning or bed sheets disruption. We analyzed cyclic alternating pattern (CAP) in these children, a marker of sleep instability that might be associated with the motor episodes of RSD and may play a role in their daytime symptoms. MethodsPolysomnographic recordings from thirty-eight children who fulfilled RSD diagnostic criteria (23 boys and 15 girls), 23 children with restless legs syndrome (RLS, 18 boys and 5 girls) and 19 controls (10 boys and 9 girls) were included. For CAP analysis, a previously developed, highly precise automated system, based on a deep learning recurrent neural network, was used. ResultsAge and gender were not statistically different between groups. RSD patients showed a lower percentage of A3 CAP subtypes than controls (median 9.8 vs. 18.2, p = 0.0089), accompanied by shorter duration of the B phase of the CAP cycle (median 28.2 vs. 29.8 in controls, 30.2 in RLS, p = 0.005) and shorter CAP cycle duration than both controls and RLS subjects (median 33.8 vs. 35.0 in controls, 35.8 in RLS, p = 0.002). Finally, RSD children also showed a longer duration of CAP cycle sequences, when compared to controls (median 172.7 vs. 141.9, p = 0.0063). ConclusionsIn conclusion, our study indicates that NREM sleep EEG shows an increased instability in RSD; these findings add to the current knowledge on the mechanisms of this newly recognized sleep disorder and suggest that sleep instability might be a favoring mechanism for the emergence of the motor episodes characterizing RSD.

0789 Decreased Sigma Band Power During NREM Sleep in REM Sleep Behavior Disorder

Abstract Introduction REM sleep Behavior Disorder (RBD) is characterized by dream enacting behaviors and a loss of atonia during REM sleep. Early detection of RBD is important because it is considered premonitory symptoms neurodegenerative disorders. In this study, we investigated the slow and fast sigma band power of patients with RBD using frequency analysis. Methods Twenty patients who were diagnosed as RBD according to the ICSD-3 criteria and 20 age-matched controls who underwent polysomnography (PSG) for other sleep disorders (insomnia, snoring) and showed normal to mild obstructive sleep apnea (OSA). NREM sleep EEG data was extracted and N1 sleep data was excluded to minimize arousal artifact. Fast Fourier transform-based spectral power analysis was used to compute the power spectral densities of the EEG in the MATLAB environment. The sigma bands were divided into 2 discrete bands: slow sigma (11 to 13 Hz) and- fast sigma (13 to 15 Hz). Mann-Whitney U test by SPSS was used. Results RBD patients (61.9 ± 7.1 years old; 12 men) had a significantly lower sigma band power than the control group (61.5 ± 1.1 years old; 11 men) in central region (p = 0.028). Particularly, the slow sigma band power showed a bigger difference in all regions except O1 (F3 = 0.017, F4 = 0.027, C3 = 0.004, C4 = 0.009, O2 = 0.017). Conclusion Sigma power was lower in the RBD patients than in the control. It suggests that RBD has impaired cortical activity. Thus, decreased spindle activity during NREM sleep may be a potential biomarker of RBD. Support

0943 Increased Non-REM Sleep Instability in Children with Restless Sleep Disorder

Abstract Introduction Restless sleep disorder (RSD) is a newly recognized condition characterized by motor movements involving large muscle groups with frequent repositioning or bed sheets disruption. We analyzed cyclic alternating pattern (CAP) in these children, a marker of sleep instability that might be associated with the motor episodes of RSD and may play a role in their daytime symptoms. Methods Polysomnographic recordings from thirty-eight children who fulfilled RSD diagnostic criteria (23 boys and 15 girls), 23 children with restless legs syndrome (RLS, 18 boys and 5 girls) and 19 controls (10 boys and 9 girls) were included. For CAP analysis, a previously developed, highly precise automated system, based on a deep learning recurrent neural network, was used. Results Age and gender were not statistically different between groups. RSD patients showed a lower percentage of A3 CAP subtypes than controls (median 9.8 vs. 18.2, p=0.0089), accompanied by shorter duration of the B phase of the CAP cycle (median 28.2 vs. 29.8 in controls, 30.2 in RLS, p=0.005) and shorter CAP cycle duration than both controls and RLS subjects (median 33.8 vs. 35.0 in controls, 35.8 in RLS, p=0.002). Finally, RSD children also showed a longer duration of CAP cycle sequences, when compared to controls (median 172.7 vs. 141.9, p=0.0063). Conclusion In conclusion, our study indicates that NREM sleep EEG shows an increased instability in RSD; these findings add to the current knowledge on the mechanisms of this newly recognized sleep disorder and suggest that sleep instability might be a favoring mechanism for the emergence of the motor episodes characterizing RSD. Support Partial support by a grant of the Italian Ministry of Health RC n. 2751598 (R.F.)

Differential modulation of NREM sleep regulation and EEG topography by chronic sleep restriction in mice

Compensatory elevation in NREM sleep EEG delta power has been typically observed following prolonged wakefulness and widely used as a sleep homeostasis indicator. However, recent evidence in human and rodent chronic sleep restriction (CSR) studies suggests that NREM delta power is not progressively increased despite of accumulated sleep loss over days. In addition, there has been little progress in understanding how sleep EEG in different brain regions responds to CSR. Using novel high-density EEG electrode arrays in the mouse model of CSR where mice underwent 18-h sleep deprivation per day for 5 consecutive days, we performed an extensive analysis of topographical NREM sleep EEG responses to the CSR condition, including period-amplitude analysis of individual slow waves. As previously reported in our analysis of REM sleep responses, we found different patterns of changes: (i) progressive decrease in NREM sleep duration and consolidation, (ii) persistent enhancement in NREM delta power especially in the frontal and parietal regions, and (iii) progressive increases in individual slow wave slope and frontal fast oscillation power. These results suggest that multiple sleep-wake regulatory systems exist in a brain region-specific manner, which can be modulated independently, especially in the CSR condition.

Oscillatory EEG Activity During REM Sleep in Elderly People Predicts Subsequent Dream Recall After Awakenings.

Several findings underlined that the electrophysiological (EEG) background of the last segment of sleep before awakenings may predict the presence/absence of dream recall (DR) in young subjects. However, little is known about the EEG correlates of DR in elderly people. Only an investigation found differences between recall and non-recall conditions during NREM sleep EEG in older adults, while—surprisingly—no EEG predictor of DR was found for what concerns REM sleep. Considering REM sleep as a privileged scenario to produce mental sleep activity related to cognitive processes, our study aimed to investigate whether specific EEG topography and frequency changes during REM sleep in elderly people may predict a subsequent recall of mental sleep activity. Twenty-one healthy older volunteers (mean age 69.2 ± 6.07 SD) and 20 young adults (mean age 23.4 ± 2.76 SD) were recorded for one night from 19 scalp derivations. Dreams were collected upon morning awakenings from REM sleep. EEG signals of the last 5 min were analyzed by the Better OSCillation algorithm to detect the peaks of oscillatory activity in both groups. Statistical comparisons revealed that older as well as young individuals recall their dream experience when the last segment of REM sleep is characterized by frontal theta oscillations. No Recall (Recall vs. Non-Recall) × Age (Young vs. Older) interaction was found. This result replicated the previous evidence in healthy young subjects, as shown in within- and between-subjects design. The findings are completely original for older individuals, demonstrating that theta oscillations are crucial for the retrieval of dreaming also in this population. Furthermore, our results did not confirm a greater presence of the theta activity in healthy aging. Conversely, we found a greater amount of rhythmic theta and alpha activity in young than older participants. It is worth noting that the theta oscillations detected are related to cognitive functioning. We emphasize the notion that the oscillatory theta activity should be distinguished from the non-rhythmic theta activity identified in relation to other phenomena such as (a) sleepiness and hypoarousal conditions during the waking state and (b) cortical slowing, considered as an EEG alteration in clinical samples.

Topographic deficits in sleep spindle density and duration point to frontal thalamo-cortical dysfunctions in first-episode psychosis

Sleep spindles are NREM sleep EEG oscillations, which are initiated within the thalamus and are regulated by thalamo-cortical circuits. Previous work from our and other research groups has shown marked spindle deficits in patients with schizophrenia (SCZ). However, the presence of spindle impairments at illness onset, including which parameters are most affected, their topographic characteristics, and their relationships with clinical symptoms have yet to be characterized. In this study we performed sleep high density (hd)-EEG recordings in twenty-seven first-episode psychosis (FEP) patients and twenty-three healthy controls (HC). Several spindle parameters—amplitude, duration, and density—were calculated and compared across groups. FEP patients showed reduced spindle duration and density, but not in spindle amplitude relative to HC. These spindles reductions were localized in a frontal area and predicted the severity of FEP patients’ negative symptoms. Altogether, these findings indicate that spindle deficits are present at the beginning of psychosis, contribute to clinical symptomatology, and point to frontal thalamo-cortical dysfunctions, thus providing a potential treatment target for early interventions in SCZ and related psychotic disorders.

NREM sleep EEG slow waves in autistic and typically developing children: Morphological characteristics and scalp distribution.

Autism is a developmental disorder with a neurobiological aetiology. Studies of the autistic brain identified atypical developmental trajectories that may lead to an impaired capacity to modulate electroencephalogram activity during sleep. We assessed the topography and characteristics of non-rapid eye movement sleep electroencephalogram slow waves in 26 boys aged between 6 and 13 years old: 13 with an autism spectrum disorder and 13 typically developing. None of the participants was medicated, intellectually disabled, reported poor sleep, or suffered from medical co-morbidities. Results are derived from a second consecutive night of polysomnography in a sleep laboratory. Slow waves (0.3-4.0 Hz; >75 µV) were automatically detected on artefact-free sections of non-rapid eye movement sleep along the anteroposterior axis in frontal, central, parietal and occipital derivations. Slow wave density (number per minute), amplitude (µV), slope (µV s-1 ) and duration (s) were computed for the first four non-rapid eye movement periods. Slow wave characteristics comparisons between groups, derivations and non-rapid eye movement periods were assessed with three-way mixed ANOVAs. Slow wave density, amplitude, slope and duration were higher in anterior compared with most posterior derivations in both groups. Children with autism spectrum disorder showed lower differences in slow waves between recording sites along the anteroposterior axis than typically developing children. These group differences in the topography of slow wave characteristics were stable across the night. We propose that slow waves during non-rapid eye movement sleep could be an electrophysiological marker of the deviant cortical maturation in autism linked to an atypical functioning of thalamo-cortical networks.

Acute effects of meditation training on the waking and sleeping brain: Is it all about homeostasis?

Our recent finding of a meditation-related increase in low-frequency NREM sleep EEG oscillatory activities peaking in the theta-alpha range (4-12Hz) was not predicted. From a consolidated body of research on sleep homeostasis, we would expect a change peaking in slow wave activity (1-4Hz) following an intense meditation session. Here we compared these changes in sleep with the post-meditation changes in waking rest scalp power to further characterize their functional significance. High-density EEG recordings were acquired from 27 long-term meditators (LTM) on three separate days at baseline and following two 8-hr sessions of either mindfulness or compassion-and-loving-kindness meditation. Thirty-one meditation-naïve participants (MNP) were recorded at the same time points. As a common effect of meditation practice, we found increases in low and fast waking EEG oscillations for LTM only, peaking at eight and 15Hz respectively, over prefrontal, and left centro-parietal electrodes. Paralleling our previous findings in sleep, there was no significant difference between meditation styles in LTM as well as no difference between matched sessions in MNP. Meditation-related changes in wakefulness and NREM sleep were correlated across space and frequency. A significant correlation was found in the EEG low frequencies (<12Hz). Since the peak of coupling was observed in the theta-alpha oscillatory range, sleep homeostatic response to meditation practice is not sufficient to explain our findings. Another likely phenomenon into play is a reverberation of meditation-related processes during subsequent sleep. Future studies should ascertain the interplay between these processes in promoting the beneficial effects of meditation practice.

Sigma frequency dependent motor learning in Williams syndrome

There are two basic stages of fine motor learning: performance gain might occur during practice (online learning), and improvement might take place without any further practice (offline learning). Offline learning, also called consolidation, has a sleep-dependent stage in terms of both speed and accuracy of the learned movement. Sleep spindle or sigma band characteristics affect motor learning in typically developing individuals. Here we ask whether the earlier found, altered sigma activity in a neurodevelopmental disorder (Williams syndrome, WS) predicts motor learning. TD and WS participants practiced in a sequential finger tapping (FT) task for two days. Although WS participants started out at a lower performance level, TD and WS participants had a comparable amount of online and offline learning in terms of the accuracy of movement. Spectral analysis of WS sleep EEG recordings revealed that motor accuracy improvement is intricately related to WS-specific NREM sleep EEG features in the 8–16 Hz range profiles: higher 11–13.5 Hz z-transformed power is associated with higher offline FT accuracy improvement; and higher oscillatory peak frequencies are associated with lower offline accuracy improvements. These findings indicate a fundamental relationship between sleep spindle (or sigma band) activity and motor learning in WS.

Increased overall cortical connectivity with syndrome specific local decreases suggested by atypical sleep-EEG synchronization in Williams syndrome

Williams syndrome (7q11.23 microdeletion) is characterized by specific alterations in neurocognitive architecture and functioning, as well as disordered sleep. Here we analyze the region, sleep state and frequency-specific EEG synchronization of whole night sleep recordings of 21 Williams syndrome and 21 typically developing age- and gender-matched subjects by calculating weighted phase lag indexes. We found broadband increases in inter- and intrahemispheric neural connectivity for both NREM and REM sleep EEG of Williams syndrome subjects. These effects consisted of increased theta, high sigma, and beta/low gamma synchronization, whereas alpha synchronization was characterized by a peculiar Williams syndrome-specific decrease during NREM states (intra- and interhemispheric centro-temporal) and REM phases of sleep (occipital intra-area synchronization). We also found a decrease in short range, occipital connectivity of NREM sleep EEG theta activity. The striking increased overall synchronization of sleep EEG in Williams syndrome subjects is consistent with the recently reported increase in synaptic and dendritic density in stem-cell based Williams syndrome models, whereas decreased alpha and occipital connectivity might reflect and underpin the altered microarchitecture of primary visual cortex and disordered visuospatial functioning of Williams syndrome subjects.