Individual Differences in Frequency and Topography of Slow and Fast Sleep Spindles

Phase-Amplitude Coupling of NREM Sleep Oscillations Shows Between-Night Stability and is Related to Overnight Memory Gains

There is growing evidence in humans linking the temporal coupling between spindles and slow oscillations during NREM sleep with the overnight stabilization of memories encoded from daytime experiences in humans. However, whether the type and strength of learning influence that relationship is still unknown. Here we tested whether the amount or type of verbal word-pair learning prior to sleep affects subsequent phase-amplitude coupling (PAC) between spindles and slow oscillations (SO). We measured the strength and preferred timing of such coupling in the EEG of 41 healthy human participants over a post-learning and control night to compare intra-individual changes with inter-individual differences. We leveraged learning paradigms of varying word-pair (WP) load: 40 WP learned to a minimum criterion of 60% correct (n = 11); 40 WP presented twice (n = 15); 120 WP presented twice (n = 15). There were no significant differences in the preferred phase or strength between the control and post-learning nights, in all learning conditions. We observed an overnight consolidation effect (improved performance at delayed recall) for the criterion learning condition only, and only in this condition was the overnight change in memory performance significantly positively correlated with the phase of SO-spindle coupling. These results suggest that the coupling of brain oscillations during human NREM sleep is stable traits that are not modulated by the amount of pre-sleep learning, yet are implicated in the sleep-dependent consolidation of memory-especially when overnight gains in memory are observed.

A spectrum of altered non-rapid eye movement sleep in schizophrenia

Multiple facets of sleep neurophysiology, including electroencephalography (EEG) metrics such as non-rapid eye movement (NREM) spindles and slow oscillations, are altered in individuals with schizophrenia (SCZ). However, beyond group-level analyses, the extent to which NREM deficits vary among patients is unclear, as are their relationships to other sources of heterogeneity including clinical factors, aging, cognitive profiles, and medication regimens. Using newly collected high-density sleep EEG data on 103 individuals with SCZ and 68 controls, we first sought to replicate our previously reported group-level differences between patients and controls (original N = 130) during the N2 stage. Then in the combined sample (N = 301 including 175 patients), we characterized patient-to-patient variability. We replicated all group-level mean differences and confirmed the high accuracy of our predictive model (area under the receiver operating characteristic curve [AUC] = 0.93 for diagnosis). Compared to controls, patients showed significantly increased between-individual variability across many (26%) sleep metrics. Although multiple clinical and cognitive factors were associated with NREM metrics, collectively they did not account for much of the general increase in patient-to-patient variability. The medication regimen was a greater contributor to variability. Some sleep metrics including fast spindle density showed exaggerated age-related effects in SCZ, and patients exhibited older predicted biological ages based on the sleep EEG; further, among patients, certain medications exacerbated these effects, in particular olanzapine. Collectively, our results point to a spectrum of N2 sleep deficits among SCZ patients that can be measured objectively and at scale, with relevance to both the etiological heterogeneity of SCZ as well as potential iatrogenic effects of antipsychotic medication.

The influence of transcranial alternating current stimulation on EEG spectral power during subsequent sleep: A randomized crossover study

OBJECTIVE

To evaluate the instant impact of transcranial alternating current stimulation (tACS) on sleep brain oscillations.

METHODS

Thirty-six healthy subjects were randomly assigned to receive tACS and sham stimulation in a crossover design separated by a one-week washout period. After stimulation, a 2-h nap polysomnography (PSG) was performed to obtain Electroencephalogram (EEG) data and objective sleep variables, and self-reported subjective sleep parameters were collected at the end of the nap. EEG spectral analyses were conducted on the EEG data to obtain the absolute and relative power for each sleep stage during the nap. The associations between power values and objective and subjective measurements were analyzed using Spearman or Pearson correlation coefficients.

RESULTS

The tACS group presented higher power in slow wave activity (SWA) and delta frequency bands and lower alpha, sigma and beta power values compared to the sham group during the N2 and N3 sleep stages. SWA and delta power were positively associated with sleep duration and sleep efficiency relevant parameters; while alpha, sigma and beta power were positively associated with prolonged sleep latency and wakefulness related variables. PSG, self-reported and sleep diary measured objective and subjective sleep parameters were comparable between the tACS and the sham groups.

CONCLUSION

Our results support that tACS could promote sleep depth in microstructure of sleep EEG, manifesting as an increase in EEG spectral power in low frequency bands and a decrease in high frequency bands. The registration number of this study is ChiCTR2200063729.

Slow oscillation-sleep spindle coupling is associated with fear extinction retention in trauma-exposed individuals

Posttraumatic stress disorder (PTSD) can be characterized as a disorder of fear learning and memory, in which there is a failure to retain memory for the extinction of conditioned fear. Sleep has been implicated in successful extinction retention. The coupling of sleep spindles to slow oscillations (SOs) during non-rapid eye movement sleep has been shown to broadly underpin sleep's beneficial effect on memory consolidation. However, the role of this oscillatory coupling in the retention of extinction memories is unknown. In a large sample of 124 trauma-exposed individuals, we investigated SO-spindle coupling in relation to fear extinction memory. We found that participants with a PTSD diagnosis, relative to trauma-exposed controls, showed significantly altered SO-spindle timing, such that PTSD participants exhibited spindle coupling further away from the peak of the SO. Across participants, the amount of coupling significantly predicted extinction retention, with coupled spindles uniquely predicting successful extinction retention compared to uncoupled spindles. These results suggest that SO-spindle coupling is critical for successful retention of extinguished fear, and that SO-spindle coupling dynamics are altered in PTSD. These alterations in the mechanics of sleep may have substantial clinical implications, meriting further investigation.

Individualized temporal patterns drive human sleep spindle timing

Sleep spindles are cortical electrical oscillations considered critical for memory consolidation and sleep stability. The timing and pattern of sleep spindles are likely to be important in driving synaptic plasticity during sleep as well as preventing disruption of sleep by sensory and internal stimuli. However, the relative importance of factors such as sleep depth, cortical up/down-state, and temporal clustering in governing sleep spindle dynamics remains poorly understood. Here, we analyze sleep data from 1,025 participants, statistically modeling the simultaneous influences of multiple factors on moment-to-moment spindle production using a point process-generalized linear model framework. Results reveal fingerprint-like timing patterns, characterized by a refractory period followed by a period of increased spindle activity, which are highly individualized yet consistent night-to-night, with increased variability with age. Strikingly, short-term (<15 s) temporal patterns of past spindle history are the main determinant of spindle timing, accounting for over 70% of the statistical deviance-surpassing the contribution of factors such as cortical up/down-state (slow oscillation phase), sleep depth, and long-term history (15 to 90 s, including ~50 s infraslow activity). Short-term history has a statistically significant influence in over 98% of the population, suggesting it is a near-universal feature of spindle activity. Short-term history and slow oscillation phase exert independent effects on spindle timing. Our results establish a robust statistical framework to examine abnormalities in sleep spindle timing observed in neurological disorders and aging, as well as the relationship between individualized sleep spindle timing, cognition, and sleep stability.

Sleep oscillations and their relations with sleep-dependent memory consolidation in early course psychosis and first-degree relatives

Sleep spindles mediate sleep-dependent memory consolidation, particularly when coupled to neocortical slow oscillations (SOs). Schizophrenia is characterized by a deficit in sleep spindles that correlates with reduced overnight memory consolidation. Here, we examined sleep spindle activity, SO-spindle coupling, and both motor procedural and verbal declarative memory consolidation in early course, minimally medicated psychosis patients and non-psychotic first-degree relatives. Using a four-night experimental procedure, we observed significant deficits in spindle density and amplitude in patients relative to controls that were driven by individuals with schizophrenia. Schizophrenia patients also showed reduced sleep-dependent consolidation of motor procedural memory, which correlated with lower spindle density. Contrary to expectations, there were no group differences in the consolidation of declarative memory on a word pairs task. Nor did the relatives of patients differ in spindle activity or memory consolidation compared with controls, however increased consistency in the timing of SO-spindle coupling were seen in both patients and relatives. Our results extend prior work by demonstrating correlated deficits in sleep spindles and sleep-dependent motor procedural memory consolidation in early course, minimally medicated patients with schizophrenia, but not in first-degree relatives. This is consistent with other work in suggesting that impaired sleep-dependent memory consolidation has some specificity for schizophrenia and is a core feature rather than reflecting the effects of medication or chronicity.

Association between alterations in sleep spindles and cognitive decline in persons with Parkinson's disease

BACKGROUND

Sleep macro and microstructural features have a relevant role for cognition. Although alterations in sleep macrostructure have been reported in persons with neurodegenerative disorders, including Parkinson's disease (PD), it is unknown whether there is a relationship between alterations in microstructure (sleep spindles) and global cognitive deficits in this disease.

OBJECTIVE

To explore the association between the macro and microstructure of sleep (sleep spindles) and the general cognitive state in persons with PD.

METHODS

Thirty-three patients with idiopathic PD underwent a one-night polysomnography (PSG) and a global cognitive assessment using the Montreal Cognitive Assessment (MoCA) test. PSG-based macrostructural sleep values and quantification and spectral estimation of sleep spindles were obtained.

RESULTS

We found increases in total sleep time, latency to rapid eye movement (REM) sleep, and percentage of N1 stage, as well as a decrease in percentage of REM sleep and sleep efficiency compared to values reported in healthy adults. Compared to expected values, a decrease in the number of sleep spindles was found at frontal regions. Participants with cognitive impairment showed an even lower count of sleep spindles, as well as an increase in the amplitude of underlying sigma (12-16 Hz) waves (fast spindles). When exploring MoCA subdomains, we found a consistent relationship between the number and amplitude of sleep spindles and attention capacity.

CONCLUSIONS

Decreased number and increased amplitude of sleep spindles are linked to cognitive impairment in persons with PD, especially in attention capacity. Therefore, sleep spindles characteristics could serve as prognostic indicators of cognitive deterioration in PD.

Corticothalamic Responsive Neurostimulation for Focal Epilepsy: A Single-Center Experience

PURPOSE

Owing to its extensive, reciprocal connectivity with the cortex and other subcortical structures, the thalamus is considered an important target for neuromodulation in drug-resistant focal epilepsy. Using corticothalamic stimulation, it is possible to modulate both the thalamus and the cortical seizure onset zone. Limited published clinical experience describes corticothalamic stimulation with depth leads targeting one of the anterior (ANT), centromedian (centromedian nucleus), or pulvinar (PUL) thalamic nuclei. However, it is not clear which of these nuclei is the "best" therapeutic target.

METHODS

This study comprised a single-center experience with corticothalamic responsive neurostimulation using the RNS System to target these three thalamic nuclei. Presented here are the methods for target selection and device programming as well as clinical outcomes and a comparison of ictal and nonictal electrophysiological features.

RESULTS

In this small retrospective study ( N = 19), responsive corticothalamic neurostimulation was an effective therapy for 79% of patients (≥50% reduction in disabling seizure frequency), regardless of whether the thalamic lead was implanted in the ANT ( N = 2), PUL ( N = 6), or centromedian nucleus ( N = 11). Twenty-six percent of patients reported a reduction in disabling seizure frequency ≥90%. Both high frequency (≥100 Hz) and low (≤20 Hz) frequency were used to stimulate the thalamus depending on the patient's response and ability to tolerate higher charge densities. In all patients, a longer burst duration (2000-5000 ms) was ultimately implemented on the thalamic leads. Across patients, peaks in the intracranial EEG were observed at theta, beta, gamma, and sleep spindle frequencies. Changes in frequency content and distribution were observed over time in all three nuclei.

CONCLUSIONS

These results indicate that both high frequency and low frequency corticothalamic responsive neurostimulation can potentially be an effective adjunctive therapy in drug-resistant focal epilepsy. These data can also contribute to a broader understanding of thalamic electrophysiology in the context of focal epilepsy.

Overnight changes in performance fatigability and their relationship to modulated deep sleep oscillations via auditory stimulation

Deep sleep oscillations are proposed to be central in restoring brain function and to affect different aspects of motor performance such as facilitating the consolidation of motor sequences resulting in faster and more accurate sequence tapping. Yet, whether deep sleep modulates performance fatigability during fatiguing tasks remains unexplored. We investigated overnight changes in tapping speed and resistance against performance fatigability via a finger tapping task. During fast tapping, fatigability manifests as a reduction in speed (or "motor slowing") which affects all tapping tasks, including motor sequences used to study motor memory formation. We further tested whether overnight changes in performance fatigability are influenced by enhancing deep sleep oscillations using auditory stimulation. We found an overnight increase in tapping speed alongside a reduction in performance fatigability and perceived workload. Auditory stimulation led to a global enhancement of slow waves and both slow and fast spindles during the stimulation window and a local increase in slow spindles in motor areas across the night. However, overnight performance improvements were not significantly modulated by auditory stimulation and changes in tapping speed or performance fatigability were not predicted by individual changes in deep sleep oscillations. Our findings demonstrate overnight changes in fatigability but revealed no evidence suggesting that this effect is causally linked to temporary augmentation of slow waves or sleep spindles. Our results are important for future studies using tapping tasks to test the relationship between sleep and motor memory consolidation, as overnight changes in objectively measured and subjectively perceived fatigue likely impact behavioural outcomes.

Structure of Spectral Composition and Synchronization in Human Sleep on the Whole Scalp: A Pilot Study

We used numerical methods to define the normative structure of the different stages of sleep and wake (W) in a pilot study of 19 participants without pathology (18-64 years old) using a double-banana bipolar montage. Artefact-free 120-240 s epoch lengths were visually identified and divided into 1 s windows with a 10% overlap. Differential channels were grouped into frontal, parieto-occipital, and temporal lobes. For every channel, the power spectrum (PS) was calculated via fast Fourier transform and used to compute the areas for the delta (0-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-30 Hz) bands, which were log-transformed. Furthermore, Pearson's correlation coefficient and coherence by bands were computed. Differences in logPS and synchronization from the whole scalp were observed between the sexes for specific stages. However, these differences vanished when specific lobes were considered. Considering the location and stages, the logPS and synchronization vary highly and specifically in a complex manner. Furthermore, the average spectra for every channel and stage were very well defined, with phase-specific features (e.g., the sigma band during N2 and N3, or the occipital alpha component during wakefulness), although the slow alpha component (8.0-8.5 Hz) persisted during NREM and REM sleep. The average spectra were symmetric between hemispheres. The properties of K-complexes and the sigma band (mainly due to sleep spindles-SSs) were deeply analyzed during the NREM N2 stage. The properties of the sigma band are directly related to the density of SSs. The average frequency of SSs in the frontal lobe was lower than that in the occipital lobe. In approximately 30% of the participants, SSs showed bimodal components in the anterior regions. qEEG can be easily and reliably used to study sleep in healthy participants and patients.

Age-related changes in sleep spindle characteristics in individuals over 75 years of age: a retrospective and comparative study

BACKGROUND

Sleep and its architecture are affected and changing through the whole lifespan. We know main modifications of the macro-architecture with a shorter sleep, occurring earlier and being more fragmented. We have been studying sleep micro-architecture through its pathological modification in sleep, psychiatric or neurocognitive disorders whereas we are still unable to say if the sleep micro-architecture of an old and very old person is rather normal, under physiological changes, or a concern for a future disorder to appear. We wanted to evaluate age-related changes in sleep spindle characteristics in individuals over 75 years of age compared with younger individuals.

METHODS

This was an exploratory study based on retrospective and comparative laboratory-based polysomnography data registered in the normal care routine for people over 75 years of age compared to people aged 65-74 years. We were studying their sleep spindle characteristics (localization, density, frequency, amplitude, and duration) in the N2 and N3 sleep stages. ANOVA and ANCOVA using age, sex and OSA were applied.

RESULTS

We included 36 participants aged > 75 years and 57 participants aged between 65 and 74 years. An OSA diagnosis was most common in both groups. Older adults receive more medication to modify their sleep. Spindle localization becomes more central after 75 years of age. Changes in the other sleep spindle characteristics between the N2 and N3 sleep stages and between the slow and fast spindles were conformed to literature data, but age was a relevant modifier only for density and duration.

CONCLUSION

We observed the same sleep spindle characteristics in both age groups except for localization. We built our study on a short sample, and participants were not free of all sleep disorders. We could establish normative values through further studies with larger samples of people without any sleep disorders to understand the modifications in normal aging and pathological conditions and to reveal the predictive biomarker function of sleep spindles.

Oscillatory-Quality of sleep spindles links brain state with sleep regulation and function

Here, we characterized the dynamics of sleep spindles, focusing on their damping, which we estimated using a metric called oscillatory-Quality (o-Quality), derived by fitting an autoregressive model to electrophysiological signals, recorded from the cortex in mice. The o-Quality of sleep spindles correlates weakly with their amplitude, shows marked laminar differences and regional topography across cortical regions, reflects the level of synchrony within and between cortical networks, is strongly modulated by sleep-wake history, reflects the degree of sensory disconnection, and correlates with the strength of coupling between spindles and slow waves. As most spindle events are highly localized and not detectable with conventional low-density recording approaches, o-Quality thus emerges as a valuable metric that allows us to infer the spread and dynamics of spindle activity across the brain and directly links their spatiotemporal dynamics with local and global regulation of brain states, sleep regulation, and function.

Sleep Consolidation Potentiates Sensorimotor Adaptation

Contrary to its well-established role in declarative learning, the impact of sleep on motor memory consolidation remains a subject of debate. Current literature suggests that while motor skill learning benefits from sleep, consolidation of sensorimotor adaptation (SMA) depends solely on the passage of time. This has led to the proposal that SMA may be an exception to other types of memories. Here, we addressed this ongoing controversy in humans through three comprehensive experiments using the visuomotor adaptation paradigm (N = 290, 150 females). In Experiment 1, we investigated the impact of sleep on memory retention when the temporal gap between training and sleep was not controlled. In line with the previous literature, we found that memory consolidates with the passage of time. In Experiment 2, we used an anterograde interference protocol to determine the time window during which SMA memory is most fragile and, thus, potentially most sensitive to sleep intervention. Our results show that memory is most vulnerable during the initial hour post-training. Building on this insight, in Experiment 3, we investigated the impact of sleep when it coincided with the critical first hour of memory consolidation. This manipulation unveiled a benefit of sleep (30% memory enhancement) alongside an increase in spindle density and spindle-SO coupling during NREM sleep, two well-established neural markers of sleep consolidation. Our findings reconcile seemingly conflicting perspectives on the active role of sleep in motor learning and point to common mechanisms at the basis of memory formation.

SPINDILOMETER: a model describing sleep spindles on EEG signals for polysomnography

This paper aims to present a model called SPINDILOMETER, which we propose to be integrated into polysomnography (PSG) devices for researchers focused on electrophysiological signals in PSG, physicians, and technicians practicing sleep in clinics, by examining the methods of the sleep electroencephalogram (EEG) signal analysis in recent years. For this purpose, an assist diagnostic model for PSG has been developed that measures the number and density of sleep spindles by analyzing EEG signals in PSG. EEG signals of 72 volunteers, 51 males and 21 females (age; 51.7 ± 3.42 years and body mass index; 37.6 ± 4.21) diagnosed with sleep-disordered breathing by PSG were analyzed by machine learning methods. The number and density of sleep spindles were compared between the classical method (EEG monitoring with the naked eye in PSG) ('method with naked eye') and the model (SPINDILOMETER). A strong positive correlation was found between 'method with naked eye' and SPINDILOMETER results (correlation coefficient: 0.987), and this correlation was statistically significant (p = 0.000). Confusion matrix (accuracy (94.61%), sensitivity (94.61%), specificity (96.60%)), and ROC analysis (AUC: 0.95) were performed to prove the adequacy of SPINDILOMETER (p = 0.000). In conclusion SPINDILOMETER can be included in PSG analysis performed in sleep laboratories. At the same time, this model provides diagnostic convenience to the physician in understanding the neurological events associated with sleep spindles and sheds light on research for thalamocortical regions in the fields of neurophysiology and electrophysiology.

Sleep oscillations related to memory consolidation during aromatases inhibitors for breast cancer

Aromatase inhibitors (AIs) are associated with sleep difficulties in breast cancer (BC) patients. Sleep is known to favor memory consolidation through the occurrence of specific oscillations, i.e., slow waves (SW) and sleep spindles, allowing a dialogue between prefrontal cortex and the hippocampus. Interestingly, neuroimaging studies in BC patients have consistently shown structural and functional modifications in these two brain regions. With the aim to evaluate sleep oscillations related to memory consolidation during AIs, we collected polysomnography data in BC patients treated (AI+, n = 17) or not (AI-, n = 17) with AIs compared to healthy controls (HC, n = 21). None of the patients had received chemotherapy and radiotherapy was finished since at least 6 months, that limit the confounding effects of other treatments than AIs. Fast and slow spindles were detected during sleep stage 2 at centro-parietal and frontal electrodes respectively. SW were detected at frontal electrodes during stage 3. Here, we show lower frontal SW densities in AI + patients compared to HC. These results concord with previous reports about frontal cortical alterations in cancer following AIs administration. Moreover, AI + patients tended to have lower spindle density at C4 electrode. Regression analyses showed that, in both patient groups, spindle density at C4 electrode explained a large variance of memory performances. Slow spindle characteristics did not differ between groups and sleep oscillations characteristics of AI- patients did not differ significantly from those of both AI + patients and HC. Overall, our results add to the compelling evidence of the systemic effects of AIs previously reported in animals, with deleterious effects on cortical activity during sleep and associated memory consolidation in the current study. There is thus a need to further investigate sleep modifications during AIs administration. Longitudinal studies are needed to confirm these findings and investigation in other cancers on this topic should be conducted.

Sex differences in the association of sleep spindle density and cognitive performance among community-dwelling middle-aged and older adults with obstructive sleep apnea

Recent studies have found associations between obstructive sleep apnea and cognitive decline. The underlying mechanisms are still unclear. Here, we investigate the associations between changes in micro-architecture, specifically sleep spindles, and cognitive function in community-dwelling middle-aged and older adults, some with obstructive sleep apnea, with a focus on sex differences. A total of 125 voluntary participants (mean age 66.0 ± 6.4 years, 64 females) from a larger cohort (participants of the Brain in Motion Studies I and II) underwent 1 night of in-home polysomnography and a neuropsychological battery (sleep and cognitive testing were conducted within 2 weeks of each other). A semi-automatic computerized algorithm was used to score polysomnography data and detect spindle characteristics in non-rapid eye movement Stages 2 and 3 in both frontal and central electrodes. Based on their apnea-hypopnea index, participants were divided into those with no obstructive sleep apnea (apnea-hypopnea index < 5 per hr, n = 21), mild obstructive sleep apnea (5 ≥ apnea-hypopnea index < 15, n = 47), moderate obstructive sleep apnea (15 ≥ apnea-hypopnea index < 30, n = 34) and severe obstructive sleep apnea (apnea-hypopnea index ≥ 30, n = 23). There were no significant differences in spindle characteristics between the four obstructive sleep apnea severity groups. Spindle density and percentage of fast spindles were positively associated with some verbal fluency measures on the cognitive testing. Sex might be linked with these associations. Biological sex could play a role in the associations between spindle characteristics and some verbal fluency measures. Obstructive sleep apnea severity was not found to be a contributing factor in this non-clinical community-dwelling cohort.

A personalized semi-automatic sleep spindle detection (PSASD) framework

BACKGROUND

Sleep spindles are distinct electroencephalogram (EEG) patterns of brain activity that have been posited to play a critical role in development, learning, and neurological disorders. Manual scoring for sleep spindles is labor-intensive and tedious but could supplement automated algorithms to resolve challenges posed with either approaches alone.

NEW METHODS

A Personalized Semi-Automatic Sleep Spindle Detection (PSASD) framework was developed to combine the strength of automated detection algorithms and visual expertise of human scorers. The underlying model in the PSASD framework assumes a generative model for EEG sleep spindles as oscillatory components, optimized to EEG amplitude, with remaining signals distributed into transient and low-frequency components.

RESULTS

A single graphical user interface (GUI) allows both manual scoring of sleep spindles (model training data) and verification of automatically detected spindles. A grid search approach allows optimization of parameters to balance tradeoffs between precision and recall measures.

COMPARISON WITH EXISTING METHODS

PSASD outperformed DETOKS in F1-score by 19% and 4% on the DREAMS and P-DROWS-E datasets, respectively. It also outperformed YASA in F1-score by 25% in the P-DROWS-E dataset. Further benchmarking analysis showed that PSASD outperformed four additional widely used sleep spindle detectors in F1-score in the P-DROWS-E dataset. Titration analysis revealed that four 30-second epochs are sufficient to fine-tune the model parameters of PSASD. Associations of frequency, duration, and amplitude of detected sleep spindles matched those previously reported with automated approaches.

CONCLUSIONS

Overall, PSASD improves detection of sleep spindles in EEG data acquired from both younger healthy and older adult patient populations.

Targeted Memory Reactivation during Nonrapid Eye Movement Sleep Enhances Neutral, But Not Negative, Components of Memory

Emotionally salient components of memory are preferentially remembered at the expense of accompanying neutral information. This emotional memory trade-off is enhanced over time, and possibly sleep, through a process of memory consolidation. Sleep is believed to benefit memory through a process of reactivation during nonrapid eye movement sleep (NREM). Here, targeted memory reactivation (TMR) was used to manipulate the reactivation of negative and neutral memories during NREM sleep. Thirty-one male and female participants encoded composite scenes containing either a negative or neutral object superimposed on an always neutral background. During NREM sleep, sounds associated with the scene object were replayed, and memory for object and background components was tested the following morning. We found that TMR during NREM sleep improved memory for neutral, but not negative scene objects. This effect was associated with sleep spindle activity, with a larger spindle response following TMR cues predicting TMR effectiveness for neutral items only. These findings therefore do not suggest a role of NREM memory reactivation in enhancing the emotional memory trade-off across a 12 h period but do align with growing evidence of spindle-mediated memory reactivation in service of neutral declarative memory.

Interrelations and functional roles of key oscillatory activities during daytime sleep in older adults

Certain neurophysiological characteristics of sleep, in particular slow oscillations (SOs), sleep spindles, and their temporal coupling, have been well characterised and associated with human memory abilities. Delta waves, which are somewhat higher in frequency and lower in amplitude compared to SOs, and their interaction with spindles have only recently been found to play a critical role in memory processing of rodents, through a competitive interaction between SO-spindle and delta-spindle coupling. However, human studies that comprehensively address delta wave interactions with spindles and SOs, as well as their functional role for memory are still lacking. Electroencephalographic data were acquired across three naps of 33 healthy older human participants (17 female) to investigate delta-spindle coupling and the interplay between delta- and SO-related activity. Additionally, we determined intra-individual stability of coupling measures and their potential link to the ability to form novel memories in a verbal memory task. Our results revealed weaker delta-spindle compared to SO-spindle coupling. Contrary to our initial hypothesis, we found no evidence for an opposing dependency between SO- and delta-related activities during non-rapid eye movement sleep. Moreover, the ratio between SO- and delta-nested spindles rather than SO-spindle and delta-spindle coupling measures by themselves predicted the ability to form novel memories best. In conclusion, our results do not confirm previous findings in rodents on competitive interactions between delta activity and SO-spindle coupling in older adults. However, they support the hypothesis that SO, delta wave, and spindle activity should be jointly considered when aiming to link sleep physiology and memory formation.

Suvorexant alters dynamics of the sleep-electroencephalography-power spectrum and depressive-symptom trajectories during inpatient opioid withdrawal

STUDY OBJECTIVES

Opioid withdrawal is an aversive experience that often exacerbates depressive symptoms and poor sleep. The aims of the present study were to examine the effects of suvorexant on oscillatory sleep-electroencephalography (EEG) band power during medically managed opioid withdrawal, and to examine their association with withdrawal severity and depressive symptoms.

METHODS

Participants with opioid use disorder (N = 38: age-range:21-63, 87% male, 45% white) underwent an 11-day buprenorphine taper, in which they were randomly assigned to suvorexant (20 mg [n = 14] or 40 mg [n = 12]), or placebo [n = 12], while ambulatory sleep-EEG data was collected. Linear mixed-effect models were used to explore: (1) main and interactive effects of drug group, and time on sleep-EEG band power, and (2) associations between sleep-EEG band power change, depressive symptoms, and withdrawal severity.

RESULTS

Oscillatory spectral power tended to be greater in the suvorexant groups. Over the course of the study, decreases in delta power were observed in all study groups (β = -189.082, d = -0.522, p = <0.005), increases in beta power (20 mg: β = 2.579, d = 0.413, p = 0.009 | 40 mg β = 5.265, d = 0.847, p < 0.001) alpha power (20 mg: β = 158.304, d = 0.397, p = 0.009 | 40 mg: β = 250.212, d = 0.601, p = 0.001) and sigma power (20 mg: β = 48.97, d = 0.410, p < 0.001 | 40 mg: β = 71.54, d = 0.568, p < 0.001) were observed in the two suvorexant groups. During the four-night taper, decreases in delta power were associated with decreases in depressive symptoms (20 mg: β = 190.90, d = 0.308, p = 0.99 | 40 mg: β = 433.33, d = 0.889 p = <0.001), and withdrawal severity (20 mg: β = 215.55, d = 0.034, p = 0.006 | 40 mg: β = 192.64, d = -0.854, p = <0.001), in both suvorexant groups and increases in sigma power were associated with decreases in withdrawal severity (20 mg: β = -357.84, d = -0.659, p = 0.004 | 40 mg: β = -906.35, d = -1.053, p = <0.001). Post-taper decreases in delta (20 mg: β = 740.58, d = 0.964 p = <0.001 | 40 mg: β = 662.23, d = 0.882, p = <0.001) and sigma power (20 mg only: β = 335.54, d = 0.560, p = 0.023) were associated with reduced depressive symptoms in the placebo group.

CONCLUSIONS

Results highlight a complex and nuanced relationship between sleep-EEG power and symptoms of depression and withdrawal. Changes in delta power may represent a mechanism influencing depressive symptoms and withdrawal.

Coupled sleep rhythms for memory consolidation

How do passing moments turn into lasting memories? Sheltered from external tasks and distractions, sleep constitutes an optimal state for the brain to reprocess and consolidate previous experiences. Recent work suggests that consolidation is governed by the intricate interaction of slow oscillations (SOs), spindles, and ripples - electrophysiological sleep rhythms that orchestrate neuronal processing and communication within and across memory circuits. This review describes how sequential SO-spindle-ripple coupling provides a temporally and spatially fine-tuned mechanism to selectively strengthen target memories across hippocampal and cortical networks. Coupled sleep rhythms might be harnessed not only to enhance overnight memory retention, but also to combat memory decline associated with healthy ageing and neurodegenerative diseases.

Age-associated sleep spindle characteristics in Duchenne muscular dystrophy

Brain oscillations of non-rapid eye movement sleep, including slow oscillations (SO, 0.5-1.5 Hz) and spindles (10-16 Hz), mirror underlying brain maturation across development and are associated with cognition. Hence, age-associated emergence and changes in the electrophysiological properties of these rhythms can lend insight into cortical development, specifically in comparisons between pediatric populations and typically developing peers. We previously evaluated age-associated changes in SOs in male patients with Duchenne muscular dystrophy (DMD), finding a significant age-related decline between 4 and 18 years. While primarily a muscle disorder, male patients with DMD can also have sleep, cognitive, and cortical abnormalities, thought to be driven by altered dystrophin expression in the brain. In this follow-up study, we characterized the age-associated changes in sleep spindles. We found that age-dependent spindle characteristics in patients with DMD, including density, frequency, amplitude, and duration, were consistent with age-associated trends reported in the literature for typically developing controls. Combined with our prior finding of age-associated decline in SOs, our results suggest that SOs, but not spindles, are a candidate intervention target to enhance sleep in patients with DMD.

Hippocampal ripples coincide with "up-state" and spindles in retrosplenial cortex

During NREM sleep, hippocampal sharp-wave ripple (SWR) events are thought to stabilize memory traces for long-term storage in downstream neocortical structures. Within the neocortex, a set of distributed networks organized around retrosplenial cortex (RS-network) interact preferentially with the hippocampus purportedly to consolidate those traces. Transient bouts of slow oscillations and sleep spindles in this RS-network are often observed around SWRs, suggesting that these two activities are related and that their interplay possibly contributes to memory consolidation. To investigate how SWRs interact with the RS-network and spindles, we combined cortical wide-field voltage imaging, Electrocorticography, and hippocampal LFP recordings in anesthetized and sleeping mice. Here, we show that, during SWR, "up-states" and spindles reliably co-occur in a cortical subnetwork centered around the retrosplenial cortex. Furthermore, retrosplenial transient activations and spindles predict slow gamma oscillations in CA1 during SWRs. Together, our results suggest that retrosplenial-hippocampal interaction may be a critical pathway of information exchange between the cortex and hippocampus.

The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study

Closed-loop auditory stimulation (CLAS) is a brain modulation technique in which sounds are timed to enhance or disrupt endogenous neurophysiological events. CLAS of slow oscillation up-states in sleep is becoming a popular tool to study and enhance sleep's functions, as it increases slow oscillations, evokes sleep spindles and enhances memory consolidation of certain tasks. However, few studies have examined the specific neurophysiological mechanisms involved in CLAS, in part because of practical limitations to available tools. To evaluate evidence for possible models of how sound stimulation during brain up-states alters brain activity, we simultaneously recorded electro- and magnetoencephalography in human participants who received auditory stimulation across sleep stages. We conducted a series of analyses that test different models of pathways through which CLAS of slow oscillations may affect widespread neural activity that have been suggested in literature, using spatial information, timing and phase relationships in the source-localized magnetoencephalography data. The results suggest that auditory information reaches ventral frontal lobe areas via non-lemniscal pathways. From there, a slow oscillation is created and propagated. We demonstrate that while the state of excitability of tissue in auditory cortex and frontal ventral regions shows some synchrony with the electroencephalography (EEG)-recorded up-states that are commonly used for CLAS, it is the state of ventral frontal regions that is most critical for slow oscillation generation. Our findings advance models of how CLAS leads to enhancement of slow oscillations, sleep spindles and associated cognitive benefits and offer insight into how the effectiveness of brain stimulation techniques can be improved.

Slow oscillation-spindle cross-frequency coupling predicts overnight declarative memory consolidation in older adults

Cross-frequency coupling (CFC) between brain oscillations during non-rapid-eye-movement (NREM) sleep (e.g. slow oscillations [SO] and spindles) may be a neural mechanism of overnight memory consolidation. Declines in CFC across the lifespan might accompany coinciding memory problems with ageing. However, there are few reports of CFC changes during sleep after learning in older adults, controlling for baseline effects. Our objective was to examine NREM CFC in healthy older adults, with an emphasis on spindle activity and SOs from frontal electroencephalogram (EEG), during a learning night after a declarative learning task, as compared to a baseline night without learning. Twenty-five older adults (M [SD] age = 69.12 [5.53] years; 64% female) completed a two-night study, with a pre- and post-sleep word-pair associates task completed on the second night. SO-spindle coupling strength and a measure of coupling phase distance from the SO up-state were both examined for between-night differences and associations with memory consolidation. Coupling strength and phase distance from the up-state peak were both stable between nights. Change in coupling strength between nights was not associated with memory consolidation, but a shift in coupling phase towards (vs. away from) the up-state peak after learning predicted better memory consolidation. Also, an exploratory interaction model suggested that associations between coupling phase closer to the up-state peak and memory consolidation may be moderated by higher (vs. lower) coupling strength. This study supports a role for NREM CFC in sleep-related memory consolidation in older adults.

Semi-Automatic Analysis of Specific Electroencephalographic Patterns during NREM2 Sleep in a Pediatric Population after SARS-CoV-2 Infection

The post-COVID-19 condition is defined by the World Health Organization as the persistence of symptoms or development of new symptoms three months after the initial SARS-CoV-2 infection, lasting for at least two months without a clear explanation. Neuropsychiatric disorders associated with this condition include asthenia, memory and concentration problems, and sleep disturbances. Our study aims to investigate sleep patterns following SARS-CoV-2 infection using EEG findings and a sleep quality questionnaire completed by parents (Sleep Disturbance Scale for Children-SDSC). Notably, our investigation is based on a convenience sample. The patients in our sample, aged 1 to 14 years, are not currently taking any medications; rather, they are undergoing follow-up assessments at the Child Neuropsychiatry department of the University Hospital of Messina for neurodevelopmental evaluations. Specifically, we are analyzing amplitude and power spectrum data in the first five minutes of NREM2 sleep, calculated from EEG recordings obtained via bipolar leads within three months after the onset of the disease. These results will be compared with controls performed on the same subjects in the six months preceding the infection. The focus of the study was sleep spindles, which are generated by the thalamocortical systems and play a role in sleep modulation, memory, and learning. Preliminary analysis suggests a predominant increase in the slow component of the spindles in the right-frontal lead.

Two-Stage Atomic Decomposition of Multichannel EEG and the Previously Undetectable Sleep Spindles

We propose a two-step procedure for atomic decomposition of multichannel EEGs, based upon multivariate matching pursuit and dipolar inverse solution, from which atoms representing relevant EEG structures are selected according to prior knowledge. We detect sleep spindles in 147 polysomnographic recordings from the Montreal Archive of Sleep Studies. Detection is compared with human scorers and two state-of-the-art algorithms, which find only about a third of the structures conforming to the definition of sleep spindles and detected by the proposed method. We provide arguments supporting the thesis that the previously undetectable sleep spindles share the same properties as those marked by human experts and previously applied methods, and were previously omitted only because of unfavorable local signal-to-noise ratios, obscuring their visibility to both human experts and algorithms replicating their markings. All detected EEG structures are automatically parametrized by their time and frequency centers, width duration, phase, and spatial location of an equivalent dipolar source within the brain. It allowed us, for the first time, to estimate the spatial gradient of sleep spindles frequencies, which not only confirmed quantitatively the well-known prevalence of higher frequencies in posterior regions, but also revealed a significant gradient in the sagittal plane. The software used in this study is freely available.

Automatic sleep spindles identification and classification with multitapers and convolution

Sleep spindles are isolated transient surges of oscillatory neural activity present during sleep stages 2 and 3 in the nonrapid eye movement (NREM). They can indicate the mechanisms of memory consolidation and plasticity in the brain. Spindles can be identified across cortical areas and classified as either slow or fast. There are spindle transients across different frequencies and power, yet most of their functions remain a mystery. Using several electroencephalogram (EEG) databases, this study presents a new method, called the "spindles across multiple channels" (SAMC) method, for identifying and categorizing sleep spindles in EEGs during the NREM sleep. The SAMC method uses a multitapers and convolution (MT&C) approach to extract the spectral estimation of different frequencies present in sleep EEGs and graphically identify spindles across multiple channels. The characteristics of spindles, such as duration, power, and event areas, are also extracted by the SAMC method. Comparison with other state-of-the-art spindle identification methods demonstrated the superiority of the proposed method with an agreement rate, average positive predictive value, and sensitivity of over 90% for spindle classification across the three databases used in this paper. The computing cost was found to be, on average, 0.004 seconds per epoch. The proposed method can potentially improve the understanding of the behavior of spindles across the scalp and accurately identify and categories sleep spindles.

A spectrum of altered non-rapid eye movement sleep in schizophrenia

Background

Multiple facets of sleep neurophysiology, including electroencephalography (EEG) metrics such as non-rapid eye movement (NREM) spindles and slow oscillations (SO), are altered in individuals with schizophrenia (SCZ). However, beyond group-level analyses which treat all patients as a unitary set, the extent to which NREM deficits vary among patients is unclear, as are their relationships to other sources of heterogeneity including clinical factors, illness duration and ageing, cognitive profiles and medication regimens. Using newly collected high density sleep EEG data on 103 individuals with SCZ and 68 controls, we first sought to replicate our previously reported (Kozhemiako et. al, 2022) group-level mean differences between patients and controls (original N=130). Then in the combined sample (N=301 including 175 patients), we characterized patient-to-patient variability in NREM neurophysiology.

Results

We replicated all group-level mean differences and confirmed the high accuracy of our predictive model (Area Under the ROC Curve, AUC = 0.93 for diagnosis). Compared to controls, patients showed significantly increased between-individual variability across many (26%) sleep metrics, with patterns only partially recapitulating those for group-level mean differences. Although multiple clinical and cognitive factors were associated with NREM metrics including spindle density, collectively they did not account for much of the general increase in patient-to-patient variability. Medication regimen was a greater (albeit still partial) contributor to variability, although original group mean differences persisted after controlling for medications. Some sleep metrics including fast spindle density showed exaggerated age-related effects in SCZ, and patients exhibited older predicted biological ages based on an independent model of ageing and the sleep EEG.

Conclusion

We demonstrated robust and replicable alterations in sleep neurophysiology in individuals with SCZ and highlighted distinct patterns of effects contrasting between-group means versus within-group variances. We further documented and controlled for a major effect of medication use, and pointed to greater age-related change in NREM sleep in patients. That increased NREM heterogeneity was not explained by standard clinical or cognitive patient assessments suggests the sleep EEG provides novel, nonredundant information to support the goals of personalized medicine. Collectively, our results point to a spectrum of NREM sleep deficits among SCZ patients that can be measured objectively and at scale, and that may offer a unique window on the etiological and genetic diversity that underlies SCZ risk, treatment response and prognosis.

Sleep spindle maturity promotes slow oscillation-spindle coupling across child and adolescent development

The synchronization of canonical fast sleep spindle activity (12.5-16 Hz, adult-like) precisely during the slow oscillation (0.5-1 Hz) up peak is considered an essential feature of adult non-rapid eye movement sleep. However, there is little knowledge on how this well-known coalescence between slow oscillations and sleep spindles develops. Leveraging individualized detection of single events, we first provide a detailed cross-sectional characterization of age-specific patterns of slow and fast sleep spindles, slow oscillations, and their coupling in children and adolescents aged 5-6, 8-11, and 14-18 years, and an adult sample of 20- to 26-year-olds. Critically, based on this, we then investigated how spindle and slow oscillation maturity substantiate age-related differences in their precise orchestration. While the predominant type of fast spindles was development-specific in that it was still nested in a frequency range below the canonical fast spindle range for the majority of children, the well-known slow oscillation-spindle coupling pattern was evident for sleep spindles in the adult-like canonical fast spindle range in all four age groups-but notably less precise in children. To corroborate these findings, we linked personalized measures of fast spindle maturity, which indicate the similarity between the prevailing development-specific and adult-like canonical fast spindles, and slow oscillation maturity, which reflects the extent to which slow oscillations show frontal dominance, with individual slow oscillation-spindle coupling patterns. Importantly, we found that fast spindle maturity was uniquely associated with enhanced slow oscillation-spindle coupling strength and temporal precision across the four age groups. Taken together, our results suggest that the increasing ability to generate adult-like canonical fast sleep spindles actuates precise slow oscillation-spindle coupling patterns from childhood through adolescence and into young adulthood.

Memory ability and retention performance relate differentially to sleep depth and spindle type

Temporal interactions between non-rapid eye movement (NREM) sleep rhythms especially the coupling between cortical slow oscillations (SO, ∼1 Hz) and thalamic spindles (∼12 Hz) have been proposed to contribute to multi-regional interactions crucial for memory processing and cognitive ability. We investigated relationships between NREM sleep depth, sleep spindles and SO-spindle coupling regarding memory ability and memory consolidation in healthy humans. Findings underscore the functional relevance of spindle dynamics (slow versus fast), SO-phase, and most importantly NREM sleep depth for cognitive processing. Cross-frequency coupling analyses demonstrated stronger precise temporal coordination of slow spindles to SO down-state in N2 for subjects with higher general memory ability. A GLM model underscored this relationship, and furthermore that fast spindle properties were predictive of overnight memory consolidation. Our results suggest cognitive fingerprints dependent on conjoint fine-tuned SO-spindle temporal coupling, spindle properties, and brain sleep state.

NREM sleep oscillations and their relations with sleep-dependent memory consolidation in early course psychosis and first-degree relatives

Sleep spindles are believed to mediate sleep-dependent memory consolidation, particularly when coupled to neocortical slow oscillations. Schizophrenia is characterized by a deficit in sleep spindles that correlates with reduced overnight memory consolidation. Here, we examined sleep spindle activity, slow oscillation-spindle coupling, and both motor procedural and verbal declarative memory consolidation in early course, minimally medicated psychosis patients and non-psychotic first-degree relatives. Using a four-night experimental procedure, we observed significant deficits in spindle density and amplitude in patients relative to controls that were driven by individuals with schizophrenia. Schizophrenia patients also showed reduced sleep-dependent consolidation of motor procedural memory, which correlated with spindle density. Contrary to expectations, there were no group differences in the consolidation of declarative memory on a word pairs task. Nor did the relatives of patients differ in spindle activity or memory consolidation compared with controls, however increased consistency in the timing of SO-spindle coupling were seen in both patient and relatives. Our results extend prior work by demonstrating correlated deficits in sleep spindles and sleep-dependent motor procedural memory consolidation in early course, minimally medicated patients with schizophrenia, but not in first-degree relatives. This is consistent with other work in suggesting that impaired sleep-dependent memory consolidation has some specificity for schizophrenia and is a core feature rather than reflecting the effects of medication or chronicity.

Protocol of the Budapest sleep, experiences, and traits study: An accessible resource for understanding associations between daily experiences, individual differences, and objectively measured sleep

Sleep is both a neurophysiological state and a biologically necessary behavior that performs a variety of indispensable roles for human health, development, and cognitive functioning. Despite this, comparatively little is known about the relationships between daily experiences and sleep features. Importantly, these relationships are bidirectional in nature, may be differently associated with subjectively and objectively assessed sleep, and may also be modulated by individual differences To address this challenge, we created the Budapest Sleep, Experiences, and Traits Study (BSETS), a multidisciplinary observational sleep study utilizing novel remote EEG devices. BSETS was designed to establish a dataset for future use in investigating the relationships between sleep features and daily experiences. In this paper we describe the protocol of the currently ongoing BSETS, which examines a community-dwelling sample of over 250 healthy participants who are studied in a naturalistic setting using a large questionnaire assessing psychological, demographic, and anthropometric information, as well as evening/morning diaries of sleep and daily experiences, and mobile EEG recordings over a period of 7 days. This dataset will become an accessible resource to the wider scientific community and can be utilized to investigate the complex multidirectional relationships between objectively and subjectively measured sleep, daily experiences, and individual differences, bestowing it with significant value for sleep researchers as well as practitioners working in clinical settings with patients suffering from disordered sleep.

Beta spectral power during sleep is associated with impaired recall of extinguished fear

The failure to retain memory for extinguished fear plays a major role in the maintenance of posttraumatic stress disorder (PTSD), with successful extinction recall necessary for symptom reduction. Disturbed sleep, a hallmark symptom of PTSD, impairs fear extinction recall. However, our understanding of the electrophysiological mechanisms underpinning sleep's role in extinction retention remains underdetermined. We examined the relationship between the microarchitecture of sleep and extinction recall in healthy humans (n = 71, both male and females included) and a pilot study in individuals with PTSD (n = 12). Participants underwent a fear conditioning and extinction protocol over 2 days, with sleep recording occurring between conditioning and extinction. Twenty-four hours after extinction learning, participants underwent extinction recall. Power spectral density (PSD) was computed for pre- and post-extinction learning sleep. Increased beta-band PSD (~17-26 Hz) during pre-extinction learning sleep was associated with worse extinction recall in healthy participants (r = 0.41, p = .004). Beta PSD was highly stable across three nights of sleep (intraclass correlation coefficients > 0.92). Results suggest beta-band PSD is specifically implicated in difficulties recalling extinguished fear.

Spindle-dependent memory consolidation in healthy adults: A meta-analysis

Accumulating evidence suggests a central role for sleep spindles in the consolidation of new memories. However, no meta-analysis of the association between sleep spindles and memory performance has been conducted so far. Here, we report meta-analytical evidence for spindle-memory associations and investigate how multiple factors, including memory type, spindle type, spindle characteristics, and EEG topography affect this relationship. The literature search yielded 53 studies reporting 1427 effect sizes, resulting in a small to moderate effect for the average association. We further found that spindle-memory associations were significantly stronger for procedural memory than for declarative memory. Neither spindle types nor EEG scalp topography had an impact on the strength of the spindle-memory relation, but we observed a distinct functional role of global and fast sleep spindles, especially for procedural memory. We also found a moderation effect of spindle characteristics, with power showing the largest effect sizes. Collectively, our findings suggest that sleep spindles are involved in learning, thereby representing a general physiological mechanism for memory consolidation.

Sleep Spindles Favor Emotion Regulation Over Memory Consolidation of Stressors in Posttraumatic Stress Disorder

BACKGROUND

Posttraumatic stress disorder (PTSD) is a trauma-induced condition, characterized by intrusive memories and trauma-associated anxiety. Non-rapid eye movement (NREM) sleep spindles might play a crucial role in learning and consolidating declarative stressor information. However, sleep and possibly sleep spindles are also known to regulate anxiety, suggestive of a dual role for sleep spindles in the processing of stressors. Specifically, in individuals with high PTSD symptom burden, spindles might fail to regulate anxiety levels after exposure and instead might maladaptively consolidate stressor information.

METHODS

To disentangle the role of spindles in declarative memory versus anxiety regulation after stressor exposure and to examine the role of PTSD in these processes, we measured nap sleep after a cohort of 45 trauma-exposed participants were exposed to laboratory stress. Participants (high vs. low PTSD symptoms) completed 2 visits: a stress visit involving exposure to negatively valent images before nap and a control visit. In both visits, sleep was monitored via electroencephalography. A stressor recall session occurred after the nap in the stress visit.

RESULTS

Stage 2 NREM (NREM2) spindle rates were higher in stress versus control sleep, indicative of stress-induced changes in spindles. In participants with high PTSD symptoms, NREM2 spindle rates in stress sleep predicted poorer recall accuracy of stressor images relative to participants with low PTSD symptoms, while correlating with greater reduction in stressor-induced anxiety levels after sleep.

CONCLUSIONS

Contrary to our expectations, although spindles are known to play a role in declarative memory processes, our findings highlight an important role for spindles in sleep-dependent anxiety regulation in PTSD.

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

Background

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.

Methods

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.

Results

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.

Conclusions

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.

L-DOPA increases slow-wave sleep duration and selectively modulates memory persistence in older adults

Introduction

Millions of people worldwide take medications such as L-DOPA that increase dopamine to treat Parkinson's disease. Yet, we do not fully understand how L-DOPA affects sleep and memory. Our earlier research in Parkinson's disease revealed that the timing of L-DOPA relative to sleep affects dopamine's impact on long-term memory. Dopamine projections between the midbrain and hippocampus potentially support memory processes during slow wave sleep. In this study, we aimed to test the hypothesis that L-DOPA enhances memory consolidation by modulating NREM sleep.

Methods

We conducted a double-blind, randomised, placebo-controlled crossover trial with healthy older adults (65-79 years, n = 35). Participants first learned a word list and were then administered long-acting L-DOPA (or placebo) before a full night of sleep. Before sleeping, a proportion of the words were re-exposed using a recognition test to strengthen memory. L-DOPA was active during sleep and the practice-recognition test, but not during initial learning.

Results

The single dose of L-DOPA increased total slow-wave sleep duration by approximately 11% compared to placebo, while also increasing spindle amplitudes around slow oscillation peaks and around 1-4 Hz NREM spectral power. However, behaviourally, L-DOPA worsened memory of words presented only once compared to re-exposed words. The coupling of spindles to slow oscillation peaks correlated with these differential effects on weaker and stronger memories. To gauge whether L-DOPA affects encoding or retrieval of information in addition to consolidation, we conducted a second experiment targeting L-DOPA only to initial encoding or retrieval and found no behavioural effects.

Discussion

Our results demonstrate that L-DOPA augments slow wave sleep in elderly, perhaps tuning coordinated network activity and impacting the selection of information for long-term storage. The pharmaceutical modification of slow-wave sleep and long-term memory may have clinical implications.

Clinical trial registration

Eudract number: 2015-002027-26; https://doi.org/10.1186/ISRCTN90897064, ISRCTN90897064.

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 model reproduce 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.

Sleep spindles, stress and PTSD: The state of the science and future directions

Sleep spindles are a signature feature of non-REM (NREM) sleep, with demonstrated relationships to sleep maintenance and learning and memory. Because PTSD is characterized by disturbances in sleep maintenance and in stress learning and memory, there is now a growing interest in examining the role of sleep spindles in the neurobiology of PTSD. This review provides an overview of methods for measuring and detecting sleep spindles as they pertain to human PTSD and stress research, presents a critical review of early findings examining sleep spindles in PTSD and stress neurobiology, and proposes several directions for future research. In doing so, this review underscores the extensive heterogeneity in sleep spindle measurement and detection methods, the wide range of spindle features that may be and have been examined, the many persisting unknowns about the clinical and functional relevance of those features, and the problems considering PTSD as a homogeneous group in between-group comparisons. This review also highlights the progress that has been made in this field and underscores the strong rationale for ongoing work in this area.

Amygdala and hippocampus dialogue with neocortex during human sleep and wakefulness

ABSTRACT

Previous studies have described synchronic electroencephalographic (EEG) patterns of the background activity that is characteristic of several vigilance states.

STUDY OBJECTIVES

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Transient oscillation dynamics during sleep provide a robust basis for electroencephalographic phenotyping and biomarker identification

Transient oscillatory events in the sleep electroencephalogram represent short-term coordinated network activity. Of particular importance, sleep spindles are transient oscillatory events associated with memory consolidation, which are altered in aging and in several psychiatric and neurodegenerative disorders. Spindle identification, however, currently contains implicit assumptions derived from what waveforms were historically easiest to discern by eye, and has recently been shown to select only a high-amplitude subset of transient events. Moreover, spindle activity is typically averaged across a sleep stage, collapsing continuous dynamics into discrete states. What information can be gained by expanding our view of transient oscillatory events and their dynamics? In this paper, we develop a novel approach to electroencephalographic phenotyping, characterizing a generalized class of transient time-frequency events across a wide frequency range using continuous dynamics. We demonstrate that the complex temporal evolution of transient events during sleep is highly stereotyped when viewed as a function of slow oscillation power (an objective, continuous metric of depth-of-sleep) and phase (a correlate of cortical up/down states). This two-fold power-phase representation has large intersubject variability-even within healthy controls-yet strong night-to-night stability for individuals, suggesting a robust basis for phenotyping. As a clinical application, we then analyze patients with schizophrenia, confirming established spindle (12-15 Hz) deficits as well as identifying novel differences in transient non-rapid eye movement events in low-alpha (7-10 Hz) and theta (4-6 Hz) ranges. Overall, these results offer an expanded view of transient activity, describing a broad class of events with properties varying continuously across spatial, temporal, and phase-coupling dimensions.

Investigating the effects of sleep and sleep loss on the different stages of episodic emotional memory: A narrative review and guide to the future

For two decades, sleep has been touted as one of the primary drivers for the encoding, consolidation, retention, and retrieval of episodic emotional memory. Recently, however, sleep's role in emotional memory processing has received renewed scrutiny as meta-analyses and reviews have indicated that sleep may only contribute a small effect that hinges on the content or context of the learning and retrieval episodes. On the one hand, the strong perception of sleep's importance in maintaining memory for emotional events may have been exacerbated by publication bias phenomena, such as the "winner's curse" and "file drawer problem." On the other hand, it is plausible that there are sets of circumstances that lead to consistent and reliable effects of sleep on emotional memory; these circumstances may depend on factors such as the placement and quality of sleep relative to the emotional experience, the content and context of the emotional experience, and the probes and strategies used to assess memory at retrieval. Here, we review the literature on how sleep (and sleep loss) influences each stage of emotional episodic memory. Specifically, we have separated previous work based on the placement of sleep and sleep loss in relation to the different stages of emotional memory processing: (1) prior to encoding, (2) immediately following encoding during early consolidation, (3) during extended consolidation, separated from initial learning, (4) just prior to retrieval, and (5) post-retrieval as memories may be restructured and reconsolidated. The goals of this review are three-fold: (1) examine phases of emotional memory that sleep may influence to a greater or lesser degree, (2) explicitly identify problematic overlaps in traditional sleep-wake study designs that are preventing the ability to better disentangle the potential role of sleep in the different stages of emotional memory processing, and (3) highlight areas for future research by identifying the stages of emotional memory processing in which the effect of sleep and sleep loss remains under-investigated. Here, we begin the task of better understanding the contexts and factors that influence the relationship between sleep and emotional memory processing and aim to be a valuable resource to facilitate hypothesis generation and promote important future research.

High-density EEG sleep correlates of cognitive and affective impairment at 12-month follow-up after COVID-19

Objective

To disentangle the pathophysiology of cognitive/affective impairment in Coronavirus Disease-2019 (COVID-19), we studied long-term cognitive and affective sequelae and sleep high-density electroencephalography (EEG) at 12-month follow-up in people with a previous hospital admission for acute COVID-19.

Methods

People discharged from an intensive care unit (ICU) and a sub-intensive ward (nonICU) between March and May 2020 were contacted between March and June 2021. Participants underwent cognitive, psychological, and sleep assessment. High-density EEG recording was acquired during a nap. Slow and fast spindles density/amplitude/frequency and source reconstruction in brain gray matter were extracted. The relationship between psychological and cognitive findings was explored with Pearson correlation.

Results

We enrolled 33 participants ( 17 nonICU) and 12 controls. We observed a lower Physical Quality of Life index, higher post-traumatic stress disorder (PTSD) score, and a worse executive function performance in nonICU participants. Higher PTSD and Beck Depression Inventory scores correlated with lower executive performance. The same group showed a reorganization of spindle cortical generators.

Conclusions

Our results show executive and psycho-affective deficits and spindle alterations in COVID-19 survivors – especially in nonICU participants – after 12 months from discharge.

Significance

These findings may be suggestive of a crucial contribution of stress experienced during hospital admission on long-term cognitive functioning.

A Novel Approach to Estimating the Cortical Sources of Sleep Spindles Using Simultaneous EEG/MEG

Sleep spindles, defining oscillations of stage II non-rapid eye movement sleep (N2), mediate sleep-dependent memory consolidation. Spindles are disrupted in several neurodevelopmental, neuropsychiatric, and neurodegenerative disorders characterized by cognitive impairment. Increasing spindles can improve memory suggesting spindles as a promising physiological target for the development of cognitive enhancing therapies. This effort would benefit from more comprehensive and spatially precise methods to characterize spindles. Spindles, as detected with electroencephalography (EEG), are often widespread across electrodes. Available evidence, however, suggests that they act locally to enhance cortical plasticity in the service of memory consolidation. Here, we present a novel method to enhance the spatial specificity of cortical source estimates of spindles using combined EEG and magnetoencephalography (MEG) data constrained to the cortex based on structural MRI. To illustrate this method, we used simultaneous EEG and MEG recordings from 25 healthy adults during a daytime nap. We first validated source space spindle detection using only EEG data by demonstrating strong temporal correspondence with sensor space EEG spindle detection (gold standard). We then demonstrated that spindle source estimates using EEG alone, MEG alone and combined EEG/MEG are stable across nap sessions. EEG detected more source space spindles than MEG and each modality detected non-overlapping spindles that had distinct cortical source distributions. Source space EEG was more sensitive to spindles in medial frontal and lateral prefrontal cortex, while MEG was more sensitive to spindles in somatosensory and motor cortices. By combining EEG and MEG data this method leverages the differential spatial sensitivities of the two modalities to obtain a more comprehensive and spatially specific source estimation of spindles than possible with either modality alone.

Human Spindle Variability

In humans, sleep spindles are 10- to 16-Hz oscillations lasting approximately 0.5-2 s. Spindles, along with cortical slow oscillations, may facilitate memory consolidation by enabling synaptic plasticity. Early recordings of spindles at the scalp found anterior channels had overall slower frequency than central-posterior channels. This robust, topographical finding led to dichotomizing spindles as "slow" versus "fast," modeled as two distinct spindle generators in frontal versus posterior cortex. Using a large dataset of intracranial stereoelectroencephalographic (sEEG) recordings from 20 patients (13 female, 7 male) and 365 bipolar recordings, we show that the difference in spindle frequency between frontal and parietal channels is comparable to the variability in spindle frequency within the course of individual spindles, across different spindles recorded by a given site, and across sites within a given region. Thus, fast and slow spindles only capture average differences that obscure a much larger underlying overlap in frequency. Furthermore, differences in mean frequency are only one of several ways that spindles differ. For example, compared with parietal, frontal spindles are smaller, tend to occur after parietal when both are engaged, and show a larger decrease in frequency within-spindles. However, frontal and parietal spindles are similar in being longer, less variable, and more widespread than occipital, temporal, and Rolandic spindles. These characteristics are accentuated in spindles which are highly phase-locked to posterior hippocampal spindles. We propose that rather than a strict parietal-fast/frontal-slow dichotomy, spindles differ continuously and quasi-independently in multiple dimensions, with variability due about equally to within-spindle, within-region, and between-region factors.SIGNIFICANCE STATEMENT Sleep spindles are 10- to 16-Hz neural oscillations generated by cortico-thalamic circuits that promote memory consolidation. Spindles are often dichotomized into slow-anterior and fast-posterior categories for cognitive and clinical studies. Here, we show that the anterior-posterior difference in spindle frequency is comparable to that observed between different cycles of individual spindles, between spindles from a given site, or from different sites within a region. Further, we show that spindles vary on other dimensions such as duration, amplitude, spread, primacy and consistency, and that these multiple dimensions vary continuously and largely independently across cortical regions. These findings suggest that multiple continuous variables rather than a strict frequency dichotomy may be more useful biomarkers for memory consolidation or psychiatric disorders.

Non-rapid eye movement sleep and wake neurophysiology in schizophrenia

Motivated by the potential of objective neurophysiological markers to index thalamocortical function in patients with severe psychiatric illnesses, we comprehensively characterized key non-rapid eye movement (NREM) sleep parameters across multiple domains, their interdependencies, and their relationship to waking event-related potentials and symptom severity. In 72 schizophrenia (SCZ) patients and 58 controls, we confirmed a marked reduction in sleep spindle density in SCZ and extended these findings to show that fast and slow spindle properties were largely uncorrelated. We also describe a novel measure of slow oscillation and spindle interaction that was attenuated in SCZ. The main sleep findings were replicated in a demographically distinct sample, and a joint model, based on multiple NREM components, statistically predicted disease status in the replication cohort. Although also altered in patients, auditory event-related potentials elicited during wake were unrelated to NREM metrics. Consistent with a growing literature implicating thalamocortical dysfunction in SCZ, our characterization identifies independent NREM and wake EEG biomarkers that may index distinct aspects of SCZ pathophysiology and point to multiple neural mechanisms underlying disease heterogeneity. This study lays the groundwork for evaluating these neurophysiological markers, individually or in combination, to guide efforts at treatment and prevention as well as identifying individuals most likely to benefit from specific interventions.

Cross-Frequency Slow Oscillation–Spindle Coupling in a Biophysically Realistic Thalamocortical Neural Mass Model

Sleep manifests itself by the spontaneous emergence of characteristic oscillatory rhythms, which often time-lock and are implicated in memory formation. Here, we analyze a neural mass model of the thalamocortical loop in which the cortical node can generate slow oscillations (approximately 1 Hz) while its thalamic component can generate fast sleep spindles of σ-band activity (12–15 Hz). We study the dynamics for different coupling strengths between the thalamic and cortical nodes, for different conductance values of the thalamic node's potassium leak and hyperpolarization-activated cation-nonselective currents, and for different parameter regimes of the cortical node. The latter are listed as follows: (1) a low activity (DOWN) state with noise-induced, transient excursions into a high activity (UP) state, (2) an adaptation induced slow oscillation limit cycle with alternating UP and DOWN states, and (3) a high activity (UP) state with noise-induced, transient excursions into the low activity (DOWN) state. During UP states, thalamic spindling is abolished or reduced. During DOWN states, the thalamic node generates sleep spindles, which in turn can cause DOWN to UP transitions in the cortical node. Consequently, this leads to spindle-induced UP state transitions in parameter regime (1), thalamic spindles induced in some but not all DOWN states in regime (2), and thalamic spindles following UP to DOWN transitions in regime (3). The spindle-induced σ-band activity in the cortical node, however, is typically the strongest during the UP state, which follows a DOWN state “window of opportunity” for spindling. When the cortical node is parametrized in regime (3), the model well explains the interactions between slow oscillations and sleep spindles observed experimentally during Non-Rapid Eye Movement sleep. The model is computationally efficient and can be integrated into large-scale modeling frameworks to study spatial aspects like sleep wave propagation.

Sleep spindles track cortical learning patterns for memory consolidation

Memory consolidation-the transformation of labile memory traces into stable long-term representations-is facilitated by post-learning sleep. Computational and biophysical models suggest that sleep spindles may play a key mechanistic role for consolidation, igniting structural changes at cortical sites involved in prior learning. Here, we tested the resulting prediction that spindles are most pronounced over learning-related cortical areas and that the extent of this learning-spindle overlap predicts behavioral measures of memory consolidation. Using high-density scalp electroencephalography (EEG) and polysomnography (PSG) in healthy volunteers, we first identified cortical areas engaged during a temporospatial associative memory task (power decreases in the alpha/beta frequency range, 6-20 Hz). Critically, we found that participant-specific topographies (i.e., spatial distributions) of post-learning sleep spindle amplitude correlated with participant-specific learning topographies. Importantly, the extent to which spindles tracked learning patterns further predicted memory consolidation across participants. Our results provide empirical evidence for a role of post-learning sleep spindles in tracking learning networks, thereby facilitating memory consolidation.