SLEEP

ObjectiveTo examine whether hypoxic burden is distinctly associated with key drivers of glymphatic activity, independent of sleep fragmentation. BackgroundOSA is a robust risk factor for multiple neurodegenerative conditions, including Alzheimers disease, with glymphatic impairment representing a potential mechanistic pathway. However, it remains unknown whether distinct pathological features of OSA, including hypoxic burden and sleep fragmentation, are differentially associated with the two key physiological drivers of glymphatic activity: (1) coordination between brain pulsations and CSF flow and (2) brain pulsation strength. MethodTwenty-eight individuals with newly identified OSA and eight healthy individuals without OSA completed either in-lab polysomnography or WatchPAT, providing estimates of hypoxic burden, quantified as time spent below 90% oxygen saturation (T90), and sleep fragmentation, quantified as non-hypoxic respiratory effort-related arousals (RERAs). Participants also completed 7T resting-state fMRI to quantify the coordination between brain pulsations and CSF flow using gBOLD-CSF coupling (i.e., cross-correlation between gray matter blood oxygen level dependent signal pulsations and CSF inflow) and brain pulsation strength using gBOLD amplitude. Hierarchical regression and Pearson correlations were used to examine associations between sleep measures and fMRI-derived metrics. ResultsGreater T90 was associated with weaker gBOLD-CSF coupling, independent of age, sex, race, and RERAs (Table 2; {beta}=0.07, p=0.008). T90 also significantly improved model-explained variance in gBOLD-CSF coupling (Table 2; {Delta}R2=0.20, p=0.008). Contrary to expectations, greater T90 was associated with higher gBOLD amplitude across the temporal lobe and multiple frontal and parietal regions. Within regions showing T90-linked elevations in gBOLD amplitude, higher gBOLD amplitude was not associated with stronger region-specific gBOLD-CSF coupling. This contrasted with regions not associated with T90, where higher gBOLD amplitude was associated with stronger gBOLD-CSF coupling (difference in {beta}=0.0006, p<0.001). RERAs were not associated with gBOLD-CSF coupling and gBOLD amplitude throughout the cerebral cortex. O_TBL View this table: org.highwire.dtl.DTLVardef@107050eorg.highwire.dtl.DTLVardef@1dcf868org.highwire.dtl.DTLVardef@3899baorg.highwire.dtl.DTLVardef@1f4a867org.highwire.dtl.DTLVardef@15c281f_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 2.C_FLOATNO O_TABLECAPTIONAssociation of T90 with the coupling strength between gray matter pulsations and CSF flow derived from a nested, hierarchical modeling approach Acronyms. RERA=respiratory effort-related arousal index; T90=time of sleep spent under 90% oxygen saturation C_TABLECAPTION C_TBL ConclusionsIn OSA, hypoxic burden, rather than respiratory effort-related sleep fragmentation, may be the primary pathological feature associated with impaired brain pulsation and CSF dynamics, both of which are key drivers of glymphatic activity. These alterations may be most prominent in the temporal lobe, potentially reflecting its elevated metabolic demand and vulnerability to hypoxemia.

ObjectivesChronic insomnia (INS) is particularly prevalent in older adults and females. Sex-and age-related differences in neurophysiological markers of sleep quality (sleep spindles and slow-wave activity [SWA]) may underlie differential vulnerability to INS. This study investigated the effects of sex and insomnia on spindle and SWA beyond aging, to better understand the mechanistic differences contributing to the higher prevalence of INS in females. MethodsAfter a habituation night, one night of sleep assessed with polysomnography was analyzed in 222 adults (aged 18-82) including 119 INS (71% female) and 103 healthy sleepers (HS; 61% female). Spindle density, slow oscillation (SO) density, relative sigma power and SWA were derived during NREM sleep. Age, group, sex, and group-by-sex interactions were examined, with age as a covariate. ResultsAge, insomnia, and sex each contributed uniquely to NREM oscillatory activity. INS primarily reduced spindle and SO density, while sex accounted for differences in SWA. While SWA was higher in females overall, sex differences were not significant within the INS or HS groups. Female INS reported highest rates of insomnia severity as well as lower sigma power than males in the INS group. Spindle and SO density deficits were also present in female INS relative to female HS, as well as male INS relative to male HS. ConclusionsThe combination of reduced sigma power in females with insomnia relative to their male counterparts, as well as less spindle and SO density compared to female healthy sleepers may contribute to greater insomnia severity in females. Statement of SignificanceInsomnia is a growing public health concern that is more commonly reported in females, yet the neural mechanisms underlying this sex difference remain poorly understood. Our findings suggest that specific markers of sleep quality are disproportionately disrupted in females with insomnia, potentially contributing to greater vulnerability and symptom severity. These results provide new insight into how sex influences the neurophysiology of insomnia disorder and identify oscillatory markers that could serve as targets for personalized interventions. Future research should investigate whether these alterations represent persistent dysfunction or reversible changes, which could advance understanding of the biological basis of insomnia and inform strategies to improve sleep health in at-risk populations.

BackgroundSleep-onset insomnia (SOI) is characterized by difficulty initiating sleep and is frequently associated with psycho-affective disorders. Despite its high prevalence and clinical impact, pathophysiological biomarkers and clear nosological frameworks remain lacking. Conventional polysomnographic (PSG) measures provide limited insight into the continuous dynamics of vigilance during the transition from wakefulness to sleep and across the night. MethodsWe retrospectively analyzed PSG recordings from 2 952 individuals using fine-grained EEG markers of vigilance, including theta/alpha ratio dynamics, micro-sleep episodes, and probability-of-wakefulness metrics. Individuals with and without SOI were compared, and SOI subgroups with and without depressive or anxiety symptoms were further examined. ResultsIndividuals with SOI exhibited a persistent state of elevated EEG-defined vigilance extending from wakefulness through the sleep onset period (SOP) and across all sleep stages, including N2, N3, and REM sleep. This hypervigilance was associated with vigilance instability during the SOP and a delayed accumulation of deep sleep over the night. Importantly, hypervigilance was more pronounced in isolated SOI than in SOI comorbid with psycho-affective symptoms, particularly depressive symptoms, and remained largely undetected by conventional PSG macrostructure measures. ConclusionsThese findings support a reconceptualization of SOI as a disorder of sustained vigilance dysregulation and reveal heterogeneity in hypervigilance across insomnia phenotypes. This dissociation from psycho-affective symptoms challenges current nosological frameworks at the interface of sleep and psychiatric disorders. By capturing microstructural alterations in vigilance invisible to standard scoring, continuous EEG-based markers provide mechanistic insight into insomnia heterogeneity and may enable biologically informed phenotyping across psychiatric conditions.

ObjectiveK-complexes (KCs) are large-amplitude EEG events that represent N2 sleep stage and have been linked to sensory gating, sleep protection, and memory consolidation. Their detection remains limited by inter-rater variability in visual scoring and by the reliance of detectors on features that discard temporal information. We propose a two-stage detector that combines a rule-based candidate localization algorithm with a Support Vector Machine (SVM) classifier operating directly on the raw 2-seconds waveform, and we evaluate it against an adjudicated expert consensus of two different datasets. MethodsPolysomnographic recordings from 10 healthy adults (Dataset 1) were independently annotated by two human scorers; discordant events were adjudicated by a senior expert, yielding 240 consensus KCs. The automatic classifier was evaluated using subject-level 10-fold Group K-Fold cross-validation and compared directly against the two human scorers under identical conditions. Cross-dataset generalization was further assessed on the public DREAMS database (Dataset 2) under both external and internal training criteria. ResultsThe SVM classifier achieved the highest F1-score (79.4%) and accuracy (78.8%) among all scorers, with balanced recall (81.7%) and specificity (75.8%). Of the 58 false positives, 42 originated from events both experts had rejected yet displayed canonical KC morphology and received high classifier confidence (P(KC)>0.7 in 45.2% of cases). This pattern was replicated on Dataset 2. ConclusionA waveform-based classifier matches expert performance and systematically flags morphologically valid KCs that fall outside conventional visual-scoring criteria. SignificanceThese findings question the existence of an unambiguous ground truth for KC detection and support a data-driven redefinition of the event boundary, with implications for sleep staging and memory-consolidation research.

Abstract Background Prediction of long-term neurodevelopmental outcomes remains challenging after perinatal asphyxia. Here, we studied whether computational metrics of brain function derived from neonatal EEG are associated with long-term neurodevelopment in infants with perinatal asphyxia. Methods Total of 36 term-born infants with perinatal asphyxia with or without hypoxic-ischemic encephalopathy were studied with neonatal multichannel electroencephalography (EEG). We computed local EEG amplitudes and phase-amplitude coupling (PAC), as well as large-scale functional cortical networks estimated using amplitude-amplitude correlations (AAC) and phase-phase correlations (PPC). These EEG-derived markers were tested for associations with neurodevelopmental outcomes at two years, assessed using the Griffiths Scales of Child Development, 3rd edition (GMDS-III). Results EEG amplitudes showed positive associations with GMDS-III Foundations of Learning and General Development scores across most electrodes during quiet sleep, with the strongest effects observed at frontal and central regions (r = 0.44-0.66). PAC showed negative associations with the same scores mainly over parietal and temporal regions (r = -0.45 to -0.55). Cortical AAC networks demonstrated the most robust and widespread negative associations in all frequency bands during quiet sleep (r = -0.47 to -0.54), with 70-72% of connections significant in high delta frequency. In turn, PPC networks showed frequency-selective and more spatially constrained negative associations during quiet sleep (r = -0.48 to -0.53), involving 5-12% of the network. Conclusions Both local and network-based metrics in the newborn brain show significant association with neurodevelopmental outcome at 2 years after perinatal asphyxia.

INTRODUCTIONLocus coeruleus and glymphatic dysfunction are linked both to Alzheimers disease (AD) and, recently, to infraslow oscillation in sleep spindle (sigma) activity (ISO). Here we hypothesise ISO integrity is a critical link between sleep and AD. METHODSWe analyzed non-rapid eye movement sleep EEG from AD and controls, extracting ISO peak amplitude, intrinsic frequency, and bandwidth from the sigma-power time course. We assessed group differences and correlations with plasma biomarkers (A{beta}42/40, pTau181 and 217, NfL, GFAP). RESULTSISO peak amplitude was significantly reduced in AD, while intrinsic frequency and bandwidth were preserved. ISO peak amplitude positively correlated with A{beta}42/40 ratio, and ISO bandwidth correlated with GFAP and NfL levels, and with lower verbal memory retention. DISCUSSIONSuch selective weakening of ISO in AD is consistent with LC dysfunction and impaired glymphatic cycling. ISO may be a novel mechanism and electrophysiological marker linking sleep microarchitecture to AD pathology.

Isolated rapid eye movement sleep behavior disorder is a strong clinical marker of future alpha-synucleinopathy, but earlier stages of this risk pathway remain insufficiently characterized. Rapid eye movement sleep without atonia is the polysomnographic substrate of this disorder and may also be detected in individuals without clinical dream-enactment behavior. Whether isolated rapid eye movement sleep without atonia is a benign finding or an early risk state for future rapid eye movement sleep behavior disorder and neurodegeneration remains unknown. DREAMER is a multicenter, prospective, observational cohort protocol designed to identify adults without clinical rapid eye movement sleep behavior disorder who show isolated rapid eye movement sleep without atonia during full-night laboratory video-polysomnography. Four Italian sleep centers will use harmonized eligibility criteria, standardized clinical and sleep assessment, quantitative REM Atonia Index scoring, secure web-based data capture, and planned longitudinal follow-up. Adults aged 40 years or older undergoing video-polysomnography will be screened. Participants with prior rapid eye movement sleep behavior disorder or technically inadequate REM sleep/chin electromyographic data will be excluded. Isolated rapid eye movement sleep without atonia will be defined in participants without clinical rapid eye movement sleep behavior disorder using a REM Atonia Index threshold of <0.85. The target recruitment is more than 500 participants over 18 months, with an expected enriched subgroup of approximately 85 individuals with isolated rapid eye movement sleep without atonia. Ancillary neurophysiological assessments and blood sampling for future biomarker studies will be obtained when feasible. DREAMER is intended to create a harmonized, trial-ready cohort for evaluating isolated rapid eye movement sleep without atonia as a potential early risk marker for incident rapid eye movement sleep behavior disorder and subsequent neurodegenerative outcomes. The study is registered at ClinicalTrials.gov as DREAMER, ClinicalTrials.gov Identifier NCT06140511.

The brain continuously integrates information from the external environment (exteroception) and the internal bodily milieu (interoception). How the balance between these two processing streams shifts across vigilance states with differing levels of environmental responsiveness, however, remains poorly understood. Here, we examined neural responses to external auditory and internal cardiac signals across wakefulness and REM sleep microstates - tonic and phasic REM - which are characterized by progressively reduced responsiveness to external stimulation. High-density EEG was recorded in healthy participants (n=25). Auditory evoked potentials (AEPs) and heartbeat evoked potentials (HEPs) served as indices of exteroception and interoception, respectively, and were compared across vigilance states. AEPs progressively decreased from wakefulness to tonic REM and were most attenuated during phasic REM. In contrast, HEPs were preserved across REM microstates and were enhanced relative to wakefulness, indicating sustained - and even amplified - processing of cardiac signals during REM sleep. To quantify the relative weighting of external and internal signals, we introduce an exteroceptive-interoceptive index, defined as the ratio of auditory to cardiac neural responses. This index decreased systematically across vigilance states, revealing a graded shift from externally oriented processing during wakefulness to internally oriented processing during phasic REM, with tonic REM occupying an intermediate position. Together, these findings demonstrate that while responsiveness to external stimuli diminishes during phasic REM, the brain continues to prioritize physiologically relevant internal signals. The exteroceptive-interoceptive balance may thus provide a novel, mechanistically grounded marker of altered consciousness, particularly informative in contexts where behavioural responsiveness cannot be assessed. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/712081v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@1e46a9borg.highwire.dtl.DTLVardef@112f050org.highwire.dtl.DTLVardef@5f5249org.highwire.dtl.DTLVardef@135cc4_HPS_FORMAT_FIGEXP M_FIG C_FIG

Motor memory retention is impaired in Parkinsons disease (PD), affecting long-term rehabilitation outcomes. It appears that NREM sleep could be beneficial for consolidation processes in PD, and could be leveraged with non-invasive sleep interventions. This study examined the effect of auditory targeted memory reactivation (TMR) during NREM sleep on the retention of a motor sequence learning finger tapping task in 20 PD and 20 healthy older adults (HOA). TMR was applied during a 2-hour nap and its effect on motor retention was post-nap, after 24-hours and with a dual-task. The impact of TMR on sleep electrophysiology was also evaluated. Results showed no effect of TMR on motor retention or dual-tasking, with no difference between the groups. However, the TMR intervention did increase slow-wave density and decreased spindle density in both groups, and slow-wave amplitude during the presentation of the auditory cues was positively associated with performance in HOA. In conclusion, TMR applied during a 2 hour nap did not enhance motor retention, but the changes in sleep physiological features could be linked to a possible underlying effect on memory processing that warrants further investigation.

Study ObjectivesSleep spindles are implicated in memory consolidation. Yet direct evidence linking spindle dynamics to declarative memory outcomes remains limited. We thus tested whether targeted memory reactivation (TMR) time-locked to sleep spindles enhances declarative memory, and whether the temporal organization of stimulated spindles-trains versus isolated events-is selectively associated with distinct memory outcomes. MethodsTwenty-eight healthy young adults learned image locations from two categories (animals, clothing) in a grid, each paired with a distinct auditory cue. During overnight NREM sleep, one cue was replayed time-locked to spindles detected in real-time using a closed-loop system (TMR condition); the other served as the non-reactivated control (No-TMR condition). Category-cue assignment was counterbalanced. Post-sleep recall, recognition accuracy, and movement time were assessed. ResultsRecall accuracy was significantly higher in the TMR than the No-TMR condition (93.96% vs. 90.61%, p = .024), whereas recognition accuracy (p = .139) and movement time (p = .651) did not differ. Stimulation intensity within spindle trains correlated with the TMR effect on recall (Spearman {rho} = .531, p = .004), whereas the proportion of isolated spindle stimulations correlated with the TMR effect on recognition ({rho} = .563, p = .002). Cross-associations were not significant. ConclusionsSpindle-locked TMR enhances recall-based declarative memory retention. The selective association between spindle temporal clustering and memory outcomes suggests that train-embedded and isolated spindles support different aspects of memory consolidation, highlighting spindle temporal context as a functionally relevant dimension of sleep-dependent memory processing.

The transition from wake to stable sleep is characterized by multiple neural, physiological, and behavioral changes. How these changes may differ in individuals with difficulties falling asleep such as children with neurodevelopmental conditions is poorly understood. Here, we studied sleep initiation in >2000 nights recorded from 186 children who participated in the Simons Sleep Project (SSP). Data included simultaneous, synchronized recordings of actigraphy, electroencephalography (EEG), photoplethysmography (PPG), and skin temperature. We extracted multiple neural, physiological, and behavioral measures that are known to increase/decrease during the sleep initiation period including EEG delta (1-4Hz) power, movement counts, heart rate (HR), and skin temperature. Transitions from 20 minutes before sleep onset to 40 minutes after sleep onset were modeled with a sigmoid function enabling the quantification of transition timing, speed, and magnitude per measure. Individuals with longer sleep onset latencies (SOL) exhibited smaller increases in EEG delta power and skin temperature as well as smaller decreases in HR and activity counts. These findings indicate that difficulties falling asleep are associated with multiple forms of cortical, physiological, and behavioral hyperarousal that can be measured at home with wearable devices. Importantly, transition magnitudes were key to explaining differences in SOL across participants (26% explained variance) in contrast to transition speed or timing within the sleep initiation period (<13% explained variance). Longer SOL and weaker transitions were particularly prominent in children diagnosed with autism and/or attention deficit hyperactivity disorder (ADHD).

Introduction: Actigraphy sleep-wake classification methods increasingly seek to leverage raw acceleration data and machine-learning-based classification, but performance evaluation in pediatrics is limited. We trained machine-learning models using pediatric data and compared their sleep-wake classification performance with existing algorithms for children. Methods: Sixty-five children (46% female, ages 5.3 to 17.7 years) completed in-lab overnight polysomnography and wore a GENEActiv device on their non-dominant wrist. The acceleration data were converted into 30-second epochs and aligned with physician-scored sleep-wake data from electroencephalography. Seven machine-learning models were trained using leave-one-subject-out cross-validation. Epoch-by-epoch analyses generated performance metrics (e.g., balanced accuracy [BA]) and discrepancy analyses provided overall sleep duration bias estimates. The combination of highest performance and least bias was used to rank using Euclidean distance scores - where a lower score represents closer to perfect performance and zero bias. For benchmarking, we included GGIR sleep scoring algorithms and an adult trained random forest classifier. Results: Overall, 560.1 hours of polysomnography and actigraphy data were collected (74.4% of epochs were scored as sleep). The pediatric-trained local-global long-short term memory (LSTM) classifier had the most optimal epoch-by-epoch performance (e.g., BA=0.85, sensitivity=0.88, specificity=0.83, ROC-AUC=0.95, and Cohen kappa=0.67). These metrics exceeded that of an adult-trained random forest classifier and GGIR-based algorithms. Discrepancy analyses revealed that overall sleep duration was underestimated by an average of 25 minutes using the LSTM classifier with no proportional bias. Conclusion: We trained seven pediatric sleep-wake classifiers that had strong ability to detect sleep and wake, with the LSTM classifier being most optimal.

The precise coordination of slow oscillations (SO) and sleep spindles during non-rapid eye movement (NREM) sleep supports memory consolidation and may serve as a sensitive marker of cognitive aging. However, longitudinal changes in their oscillatory dynamics in midlife and older age remain poorly understood. Using polysomnography with high-density EEG at two timepoints over [~]2.5 years, we examined changes in local NREM slow wave (SW), sleep spindle (occurring in the 11-16 Hz sigma range), and SO-sigma coupling strength in cognitively unimpaired middle-aged to older adults at risk for Alzheimers disease. Fronto-central SO-sigma power coupling strength significantly declined over time, independent of changes in multiple measures of SW and sleep spindle expression. Local declines in multiple sleep spindle measures were also observed. Greater baseline levels of cerebrospinal fluid (CSF) neurogranin, a postsynaptic protein abundantly expressed in the dendritic spines of the hippocampus and cerebral cortex and implicated in calcium-dependent synaptic plasticity, predicted the magnitude of longitudinal decline in SO-fast sigma coupling strength, which in turn predicted episodic memory performance changes. These findings suggest that longitudinal changes in local sleep oscillatory dynamics are related to decreased synaptic integrity and may serve as an early indicator of memory decline in older adults at risk for Alzheimers disease.

BackgroundNarcolepsy is a debilitating sleep disorder caused by hypocretin deficiency. Aside from its role to induce wakefulness, hypocretin is linked to modulated appetite and metabolism, often resulting in weight gain. Study objectivesWe aimed to unravel the comprehensive epidemiological connection between narcolepsy and major cardiometabolic outcomes. MethodsWe analyzed cardiovascular and metabolic disease distribution in the FinnGen study. Using longitudinal electronic health records, we assessed associations between narcolepsy, cardiac/metabolic markers, and prescriptions for relevant drugs. ResultsOur findings demonstrate significant associations between narcolepsy and metabolic traits (OR [95% CI] = 2.65 [1.81, 3.89]) as well as stroke (OR = 2.36 [1.38, 4.04]). Narcolepsy patients exhibit a less favourable metabolic profile, including higher glucose levels (OR = 1.1143 [1.0599, 1.1715]) and dyslipidaemia. This is supported by increased prescriptions of insulin (OR = 2.269 [1.46, 3.53]), simvastatin (OR = 2.292 [1.59, 3.31]), and metformin (OR = 2.327 [1.66, 3.25]), reflecting high metabolic disturbances. Furthermore, positive associations with antihypertensive and antiplatelet medications were observed, consistent with elevated cardiovascular risk. ConclusionTaken together, our findings highlight the cardiometabolic burden in narcolepsy. This study enhances understanding of the metabolic and cardiovascular consequences of narcolepsy and offers timely guidance for effective disease control. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/26351468v2_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@19f5783org.highwire.dtl.DTLVardef@2a648corg.highwire.dtl.DTLVardef@12f2b9eorg.highwire.dtl.DTLVardef@1d8baaf_HPS_FORMAT_FIGEXP M_FIG C_FIG

Sleep spindles are rhythmic electroencephalographic signatures of non-rapid-eye-movement sleep. Their dysregulation has been implicated in several neuropsychiatric illnesses. Spindles have a characteristic waxing and waning shape, but the cellular and circuit mechanisms controlling their shape are not well understood. Recent but sparse research has implied that sleep spindle shape becomes abnormal in post-traumatic stress disorder (PTSD). PTSD patients have dysfunctional GABAA receptors in midline thalamic regions, areas involved in the orchestration of sleep spindles. We modelled this GABAA dysfunction within thalamocortical (TC) neurons using localized CRISPR-Cas9 technology to test the hypothesis that GABA dysfunction would dysregulate sleep spindle shape and cause symptoms of PTSD, in mouse model behavioral evaluations. We found sleep spindles were shorter and abnormally shaped, having lost their characteristic waxing and waning shape, in mice with GABAA receptor knock-down in TC neurons (TC-1KD). TC-1KD mice failed to recover from learned fearful reactions following an aversive stimulus. We tested this with a contextual fear conditioning paradigm using electric foot shocks. A control group with intact GABAA receptors successfully habituated to the fear conditioned location in subsequent visits to that context without foot shocks. In contrast, TC-1KD mice never habituated, suggesting abnormally extended fearful memories. The number of inhibitory post synaptic currents in TC neurons were significantly decreased in vitro, confirming an effective knock-down. Our results imply that abnormally shaped sleep spindles may serve as a biomarker of GABAA receptor dysfunction in TC neurons which may be involved in abnormal fear processing in PTSD. We postulate GABAA receptor dysfunction in TC neurons may be underlying pathophysiology of PTSD and our findings here may inspire the development of screens, diagnostics and objective characteristics of stress related disorders, including PTSD.

Objectives: Self-applied, low-density EEG offers opportunities to examine sleep in the home environment, yet its feasibility during behavioural sleep interventions remains unexplored. This pilot study aimed to evaluate the feasibility and acceptability of a self-applied, low-density EEG device during sleep restriction therapy (SRT) and explore effects on sleep and affect. Methods: Seventeen adults with insomnia and depressive symptoms completed a 2-week baseline and 4 weeks of SRT. The primary outcome was the proportion of expected EEG recordings completed and scoreable. Secondary outcomes included clinical measures, sleep continuity (sleep diary, actigraphy), sleep architecture (low-density EEG for 9 nights), power spectral density, and affect. Data were analysed with linear mixed models. Cohen's d and 95% confidence intervals were reported. Results: Feasibility was demonstrated (92% of expected EEG nights completed). SRT was associated with reductions in insomnia severity, depressive symptoms, negative affect, and increases in positive affect. Robust improvements were observed across treatment in sleep continuity (SOL, WASO, SE) from diary, which were paralleled by actigraphy. EEG revealed reduced TIB, TST, N1, N2, REM sleep, and REM latency during week one. Reductions in EEG-derived TIB and N1 sleep were maintained at night 28. There were no reliable differences for spectral or spindle measures. Conclusions: These findings suggest that self-applied, low-density EEG during SRT is feasible, acceptable, and may capture sleep changes during treatment. They highlight the potential for multi-night monitoring of sleep interventions at home and elucidating mechanisms underlying therapeutic change.

BackgroundGrowing evidence suggests that sleep plays an important role in PTSD outcomes, potentially due to its influence on emotional memory consolidation, though these mechanisms remain unknown. This study sought to test the hypotheses that sleep neurophysiology, PTSD status, and sex moderates the degree to which the late positive potential (LPP) mediates memory accuracy for affective visual stimuli. MethodsN = 39 participants (18 female) viewed 75 negative and 75 neutral IAPS images while EEG was recorded. After viewing the images, participants took a two-hour long nap which was followed by a memory assessment. Memory accuracy was measured using d = Z(hit rate) - Z(false alarm rate), where hit rate refers to the proportion of images seen during the memory assessment that are correctly identified as being previously seen, false alarm rate refers to the proportion of images seen during the memory assessment that are incorrectly identified as being previously seen, and Z() is the inverse cumulative distribution function of the standard normal distribution function. ResultsThe early (300 - 1000 ms) and late (1000 - 1500 ms) LPP mediated enhanced discrimination accuracy for emotional compared to neural stimuli (d) (ps < 0.001). The association between the late LPP and d was moderated by sleep such that the association was stronger when participants spent proportionately more time in N3 and REM (p = 0.02). The differences in reactivity between emotional and neutral images for both the early and late LPP were attenuated in PTSD+ individuals vs. controls (ps < 0.001). Despite mediation results showing greater d for emotional compared to neutral stimuli, women showed overall worse memory accuracy for negative compared to neutral stimuli (p < 0.001) whereas men showed no difference (p = 0.64). ConclusionsN3 and REM sleep play a critical role for memory of stimuli that produce large and sustained neural responses. PTSD is marked by a diminished ability to distinguish between negative and neutral information. More research is critical to understand sex effects on emotional memory.

IntroductionSleep-dependent memory consolidation differs by sex and maybe disrupted by Alzheimers disease (AD) risk. Whether sex moderates associations between apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) status, non-rapid eye movement (NREM) sleep, and memory remains unclear. MethodsEighty cognitively unimpaired older adults completed a word-pair memory task with encoding and immediate testing occurring prior to overnight polysomnography with high-density electroencephalography (hdEEG) and delayed recall occurring after sleep. Sleep-memory associations were examined as a function of sex and APOE {varepsilon}4 status. ResultsIn this sample, a sexxAPOE {varepsilon}4 interaction was associated with overnight memory retention, with female carriers exhibiting less overnight forgetting than female non-carriers and male {varepsilon}4 carriers. NREM sleep differed by sex and APOE {varepsilon}4 status and was associated with memory retention in{varepsilon} 4 carriers. DiscussionThese findings indicate sex-specific, sleep-dependent memory mechanisms associated with genetic AD risk, highlighting sleep as a potential early target for intervention, pending replication in larger samples.

Background: Peri-lead edema (PLE) occurs in up to 15% of Deep Brain Stimulation (DBS) cases, can cause morbidity, and its etiology remains unknown. We hypothesized that PLE represents a secondary brain injury modulated by hypoxemia, and that patients with obstructive sleep apnea (OSA) are at elevated risk. Methods: We conducted a retrospective case-control study of 121 Parkinson's disease (PD) patients undergoing DBS at a single center (2019-2024). PLE severity was quantified by CT volumetric segmentation and Hounsfield unit (HU) measures. Perioperative SpO2 and PaO2 were recorded. Polysomnography (PSG) was available in 26 patients; and the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) was administered retrospectively. Results: Symptomatic PLE occurred in 12 patients (9.9%), with onset at 3.5 (2-9) days postoperatively. PLE patients had higher body mass index (p = 0.022) and higher OSA prevalence (75% vs. 30%; p = 0.002). Perioperative SpO2 was lower in the PLE group in both the operating room and post-anesthesia care unit (PACU; p < 0.05); PaO2 was lower in the PACU (p = 0.037). In the PSG subgroup, REM Sleep Behavior Disorder (RBD) incidence was lower in PLE patients (20% vs. 60%; unadjusted p = 0.048), and PLE severity correlated significantly with sleep-related hypoxemia and respiratory indices. RBDSQ scores were positively associated with edema density (normalized HU: rho = 0.86, p = 0.024). Conclusions: OSA and perioperative hypoxemia are associated with symptomatic PLE following DBS, while RBD appears protective. Preoperative sleep evaluation and optimized perioperative airway management warrant prospective investigation as PLE prevention strategies.

Sleep abnormalities and dysfunction of gamma band (30-80 Hz) activity generated by parvalbumin (PV) interneurons are early characteristics of Alzheimers disease (AD) which correlate with the severity of amyloid-{beta} deposition (A{beta}) and cognitive impairment. However, the timing of these alterations in vivo with respect to disease progression is unclear. Here, in longitudinal recordings from APP/PS1/PV-cre (AD mice) from 3-6 months, we found reduced sleep slow-wave power (0.5-4 Hz) in hippocampus and medial prefrontal cortex in AD mice as young as 3 months old, compared to non-AD (PV-cre) mice, well before overt pathology. This finding was primarily due to reductions in the NREM delta range (1.5-4 Hz), a hallmark of restorative functions of sleep. In contrast, beta (15-30 Hz) power linked to insomnia was significantly higher across all sleep-wake states. Loss of deep NREM sleep was not compensated by an increase in NREM sleep time, instead NREM sleep during the dark (active) phase was slightly but significantly lower in AD mice. 40-Hz auditory steady-state responses and associated evoked calcium responses of hippocampal PV neurons recorded using fiber photometry were also impaired by 3 months old. However, Y-maze performance in 3- and 6-month-old AD mice was not significantly different from non-AD mice. These results reveal reduced deep sleep and PV-associated 40-Hz activity as very early changes amenable to early intervention occurring prior to cognitive deficits. Furthermore, they establish APP/PS1 mice as a good model to causally test the relationship between sleep, PV neuronal activity and amyloid-mediated pathology.