Manipulated overlapping reactivation of multiple memories promotes explicit gist abstraction.

Sleep is considered to promote gist abstraction on the basis of spontaneous memory reactivation. As speculated in the theory of 'information overlap to abstract (iOtA)', 'overlap' between reactivated memories, beyond reactivation, is crucial to gist abstraction. Yet so far, empirical research has not tested this theory by manipulating the factor of 'overlap'. In the current study, 'overlap' itself was manipulated by targeted memory reactivation (TMR), through simultaneously reactivating multiple memories that either contain or do not contain spatially overlapped gist information, to investigate the effect of overlapping reactivation on gist abstraction. This study had a factorial design of 2 factors with 2 levels respectively (spatial overlap/no spatial overlap, TMR/no-TMR). Accordingly, 82 healthy college students (aged 19 âˆ¼ 25, 57 females) were randomized into four groups. After learning 16 pictures, paired with 4 auditory cues (4 pictures - 1 cue) according to the grouping, participants were given a 90-minute nap opportunity. Then TMR cueing was conducted during N2 and slow wave sleep of the nap. Performance in memory task was used to measure gist abstraction. The results showed a significant main effect of TMR on both implicit and explicit gist abstraction, and a marginally significant interaction effect on explicit gist abstraction. Further analyses showed that explicit gist abstraction in the spatial overlap & TMR group was significantly better than in the control group. Moreover, explicit gist abstraction was positively correlated with spindle density. The current study thus indicates that TMR facilitates gist abstraction, and explicit gist abstraction may benefit more from overlapping reactivation.

Shared and distinct aberrations in frontal-striatal system functional patterns among patients with irritable bowel syndrome and major depressive disorder.

BACKGROUND: Considering the high comorbidity, shared risk factors, and genetic pathways between irritable bowel syndrome (IBS) and major depressive disorder (MDD), we hypothesized that there would be both shared and disorder-specific alterations in brain function. METHODS: A total of 39 IBS patients, 39 MDD patients, and 40 healthy controls (HCs) were enrolled and matched for sex, age, and educational level. All subjects underwent resting-state functional MRI. The clinical variables of anxiety, depression, gastrointestinal symptoms and alexithymia were recorded. The 12 subregions of the striatum were employed as seeds to assess their functional connectivity (FC) with every voxel throughout the whole brain. RESULTS: Compared to HC, IBS and MDD patients exhibited aberrant frontal-striatal circuitry. We observed a common decrease in FC between the dorsal striatum and regions of the hippocampus, sensorimotor cortex, and prefrontal cortex (PFC) in both IBS and MDD patients. Patients with IBS exhibited disorder-specific decreases in FC within the striatum, along with reduced connectivity between the ventral striatum and sensorimotor cortex. In contrast, MDD patients showed disorder-specific hyperconnectivity in the medial PFC-limbic system. Receiver operating characteristic curve analysis showed that frontal-striatal FC values could serve as transdiagnostic markers of IBS and MDD. Within the IBS group, striatal connectivity was not only negatively associated with weekly abdominal pain days but also negatively correlated with the levels of anxiety and alexithymia. CONCLUSIONS: This exploratory analysis indicated that patients with IBS and MDD exhibited both shared and disorder-specific frontal-striatal circuit impairments, potentially explaining both comorbidity and distinct phenotypes.

Challenges and Suggestions of Ethical Review on Clinical Research Involving Brain-Computer Interfaces.

Brain-computer interface (BCI) technology is rapidly advancing in medical research and application. As an emerging biomedical engineering technology, it has garnered significant attention in the clinical research of brain disease diagnosis and treatment, neurological rehabilitation, and mental health. However, BCI also raises several challenges and ethical concerns in clinical research. In this article, the authors investigate and discuss three aspects of BCI in medicine and healthcare: the state of international ethical governance, multidimensional ethical challenges pertaining to BCI in clinical research, and suggestive concerns for ethical review. Despite the great potential of frontier BCI research and development in the field of medical care, the ethical challenges induced by itself and the complexities of clinical research and brain function have put forward new special fields for ethics in BCI. To ensure "responsible innovation" in BCI research in healthcare and medicine, the creation of an ethical global governance framework and system, along with special guidelines for cutting-edge BCI research in medicine, is suggested.

Suspected duloxetine-induced restless legs syndrome phenotypic variant: a case report.

BACKGROUND: Restless arms syndrome (RAS) is the most common variant of restless legs syndrome (RLS), which is easy to be ignored in clinical practice due to the lack of specific diagnostic criteria. When effective therapeutic agents induced RAS and symptoms persisted after briefly observation, clinicians will face the challenge of weighing efficacy against side effects. CASE PRESENTATION: A 67-year-old woman was admitted to a geriatric psychiatric ward with depression. Upon admission, the escitalopram dose was reduced from 15 mg to 10 mg per day, and the duloxetine dose was increased from 60 mg to 80 mg per day. The next night before bedtime, she developed itching and creeping sensations deep inside bilateral shoulders and arms, with the urge to move, worsening at rest, and alleviation after hammering. The symptoms persisted when escitalopram was discontinued. A history of RLS was confirmed. Treatment with 40 mg of duloxetine and 0.125 mg of pramipexole significantly improved depression, and the paresthesia disappeared, with no recurrence occurring 6 months after discharge. DISCUSSION AND CONCLUSIONS: This case suggests that psychiatrists should pay attention to RLS variants when increasing doses of duloxetine. Long-term improvement can be achieved through dosage reduction combined with dopaminergic drugs instead of immediate discontinuation.

Benefits of napping habits in healthy adults: Maintaining alerting performance and cortisol levels change within 90 min of habitual napping time.

BACKGROUND: Napping is garnering increased attention as a strategy for adults to sustain alertness and alleviate stress in contemporary society. The nuances of napping habits are emerging as an independent factor influencing the extent of individual benefits. This study aimed to demonstrate the long-term benefits of napping and explore the impact of napping habits on individual alertness, as well as whether this effect was correlated with cortisol levels. METHODS: The study involved 80 healthy adults categorized into two groups based on self-reported napping habits: habitual nappers (n = 49) and non-habitual nappers (n = 31). Karolinska Sleepiness Scale (KSS), psychomotor vigilance task (PVT), and saliva collection were performed every 30 min within 90 min in the absence of napping during the afternoon dip. The measurements were analyzed using repeated measures ANOVA and Pearson correlation analyses. RESULTS: There was an interaction between groups and time in reaction speed and lapse number of PVT and cortisol (all p < 0.05). Post hoc analysis found that habitual nappers maintained higher objective alertness and experienced more significant increases in cortisol over time (all p < 0.05). The cortisol levels at sleepiness time were negatively associated with the slowest 10 % reaction speed of PVT in non-habitual nappers (r = -0.409, p = 0.022). CONCLUSION: Under the premise of mitigating the impacts of acute nap deprivation on sleep homeostasis and rhythm, napping habits emerge as a potential factor influencing the ability of individuals to sustain heightened alertness.

Understanding the cognitive and neuroimaging bases underlying the detrimental impact of sleep deprivation on reciprocity.

Although the impact of sleep loss on social behaviors has been widely observed in recent years, the mechanisms underpinning these impacts remain unclear. In this study, we explored the detrimental effects of sleep deprivation on reciprocity behavior as well as its underlying psychological and neuroimaging mechanisms by combining sleep manipulation, an interpersonal interactive game, computational modeling and neuroimaging. Our results suggested that after sleep deprivation, individuals showed reduced reciprocity behavior, mainly due to their reduced weights on communal concern when making social decisions. At neural level, we demonstrated that sleep deprivation's effects were observed in the precuneus (hyperactivity) and temporoparietal junction, dorsal lateral prefrontal cortex (DLPFC) (both hypoactivity), and reduced reciprocity was also accounted for by increased precuneus-thalamus connectivity and DLPFC-thalamus connectivity. Our findings contributed to the understanding of the psychological and neuroimaging bases underlying the deleterious impact of sleep deprivation on social behaviors.

The insensitivity of sleep to an unfamiliar sleeping environment in patients with insomnia disorder.

BACKGROUND: Sleeping in an unfamiliar environment, such as a sleep laboratory, is thought to disturb sleep in healthy individuals and could express a hyperarousal state called the first night effect. Insomnia disorder (ID) is a highly prevalent health problem characterized by increased arousal during the night and daytime. Whether or not a similar phenomenon occurs in patients with ID is unclear. This study aimed to investigate the effect of an unfamiliar environment on the sleep of patients with ID. METHODS: In an unfamiliar sleep laboratory, polysomnographic recording testing was performed for two consecutive nights in patients with ID and age- and sex-matched healthy control subjects (HC). We collected sleep diaries and questionnaires regarding sleep, medical conditions, psychological status, and health history. Sleep continuity and architecture in both groups were compared and analyzed for two consecutive nights. RESULTS: Participants with ID (n = 39)  and HC (n = 35) demonstrated differentially poor sleep on laboratory adaptation after exposure to the sleep laboratory. Patients with ID had longer rapid eye movement (REM) latency on the first night than on the second sleep night. HC showed increased duration and percentage of N1, decreased duration and percentage of N3, and decreased REM percentage during initial nights compared to subsequent nights. The other sleep variables showed no differences between the first and second sleep nights in patients with ID and HC. CONCLUSIONS: An unfamiliar sleep environment does not aggravate the disruption of sleep continuity and sleep architecture but only affects the REM latency in patients with ID compared with HC.

A Semi-Supervised Multi-Scale Arbitrary Dilated Convolution Neural Network for Pediatric Sleep Staging.

Sleep staging is essential for assessing sleep quality and diagnosing sleep disorders. However, sleep staging is a labor-intensive process, making it arduous to obtain large quantities of high-quality labeled data for automatic sleep staging. Meanwhile, most of the research on automatic sleep staging pays little attention to pediatric sleep staging. To address these challenges, we propose a semi-supervised multi-scale arbitrary dilated convolution neural network (SMADNet) for pediatric sleep staging using the scalogram with a high height-to-width ratio generated by the continuous wavelet transform (CWT) as input. To extract more extended time dimensional feature representations and adapt to scalograms with a high height-to-width ratio in SMADNet, we introduce a multi-scale arbitrary dilation convolution block (MADBlock) based on our proposed arbitrary dilated convolution (ADConv). Finally, we also utilize semi-supervised learning as the training scheme for our network in order to alleviate the reliance on labeled data. Our proposed model has achieved performance comparable to state-of-the-art supervised learning methods with 30% labels. Our model is tested on a private pediatric dataset and achieved 79% accuracy, 72% kappa, and 75% MF1. Therefore, our model demonstrates a powerful feature extraction capability and has achieved performance comparable to state-of-the-art supervised learning methods with a small number of labels.

First-night effect in insomnia disorder: a systematic review and meta-analysis of polysomnographic findings.

Polysomnographic studies have been performed to investigate the first-night effect in insomnia disorder. However, these studies have revealed discrepant findings. This meta-analysis aimed to summarise and quantify the characteristics of the first-night effect in insomnia disorder. We performed a systematic search of the PubMed, Medline, EMBASE, Web of Science and PsycINFO databases to identify studies published through October 2019. A total of 11,862 articles were identified, and seven studies with eight independent populations were included in the meta-analysis. A total of 639 patients with insomnia disorder and 171 healthy controls underwent more than 2 consecutive nights of in-laboratory polysomnography. Pooled results demonstrated that both variables of sleep continuity and sleep architecture, other than slow-wave sleep were significantly altered in the first-night effect in insomnia disorder. Furthermore, the results indicated that patients with insomnia disorder had a disruption of sleep continuity in the first-night effect, including increased sleep onset latency and reduced total sleep time, compared to healthy controls. Overall, the findings show that patients with insomnia disorder experience the first-night effect, rather than reverse first-night effect, and the profiles of the first-night effect in patients with insomnia are different from healthy controls. These indicate that an adaptation night is necessary when sleep continuity and sleep architecture is to be studied in patients with insomnia disorder. More well-designed studies with large samples are needed to confirm the results.

The association between oral and gut microbiota in male patients with alcohol dependence.

Introduction: The relationship between oral and gut microbiota in alcohol dependence (AD) is not well understood, particularly the effects of oral microbiota on the intestinal microbiota. The current study aimed to explore the association between oral and gut microbiota in AD to clarify whether oral microbiota could ectopically colonize into the gut. Methods: 16S rRNA sequence libraries were used to compare oral and gut microbial profiles in persons with AD and healthy controls (HC). Source Tracker and NetShift were used to identify bacteria responsible for ectopic colonization and indicate the driver function of ectopic colonization bacteria. Results: The α-diversity of oral microbiota and intestinal microbiota was significantly decreased in persons with AD (all p < 0.05). Principal coordinate analysis indicated greater similarity between oral and gut microbiota in persons with AD than that in HC, and oral-gut overlaps in microbiota were found for 9 genera in persons with AD relative to only 3 genera in HC. The contribution ratio of oral microbiota to intestinal microbiota composition in AD is 5.26% based on Source Tracker，and the AD with ectopic colonization showed the daily maximum standard drinks, red blood cell counts, hemoglobin content, and PACS scores decreasing (all p < 0.05). Discussion: Results highlight the connection between oral-gut microbiota in AD and suggest novel potential mechanistic possibilities.

Depression, anxiety, and burnout among psychiatrists during the COVID-19 pandemic: a cross-sectional study in Beijing, China.

BACKGROUND: With the rise of reported mental disorders and behavioral issues after the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, psychiatrists and mental health care are urgently needed more than ever before. The psychiatric career carries a high emotional burden and stressful demands, which bring issues on psychiatrists' mental health and well-being into question. To investigate the prevalence and risk factors of depression, anxiety, and work burnout among psychiatrists in Beijing during the COVID-19 pandemic. METHODS: This cross-sectional survey was conducted from January 6 to January 30, 2022, two years after COVID-19 was declared a global pandemic. Recruitment was performed using a convenience sample approach by sending online questionnaires to psychiatrists in Beijing. The symptoms of depression, anxiety, and burnout were evaluated using the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Maslach Burnout Inventory-General Survey (MBI-GS). The perceived stress and social support were measured by the Chinese Perceived Stress Scale (CPSS) and Social Support Rating Scale (SSRS), respectively. RESULTS: The data of 564 psychiatrists (median [interquartile range] age, 37 [30-43] years old) of all 1532 in Beijing were included in the statistical analysis. The prevalence of symptoms of depression, anxiety and burnout were 33.2% (95% CI, 29.3-37.1%, PHQ-9 ≥ 5), 25.4% (95% CI, 21.8-29.0%, GAD-7 ≥ 5) and 40.6% (95% CI, 36.5-44.7%, MBI-GS ≥ 3 in each of the three subdimensions), respectively. The psychiatrist with a higher score on perceived stress was more likely to suffer from depressive symptoms (adjusted odds ratios [ORs]: 4.431 [95%CI, 2.907-6.752]); the anxiety symptoms (adjusted ORs: 8.280 [95%CI, 5.255-13.049]), and the burnout conditions (adjusted ORs: 9.102 [95%CI, 5.795-14.298]). Receiving high social support was an independent protective factor against symptoms of depression (adjusted ORs: 0.176 [95%CI, [0.080-0.386]), anxiety (adjusted ORs: 0.265 [95%CI, 0.111-0.630]) and burnout (adjusted ORs: 0.319 [95%CI, 0.148-0.686]). CONCLUSIONS: Our data suggest a considerable proportion of psychiatrists also suffer from depression, anxiety, and burnout. Perceived stress and social support influence depression, anxiety, and burnout. For public health, we must work together to reduce the pressure and increase social support to mitigate mental health risks in psychiatrists.

Thalamic network under wakefulness after sleep onset and its coupling with daytime fatigue in insomnia disorder: An EEG-fMRI study.

BACKGROUND: Fatigue is the most common daytime impairment of insomnia disorder (ID). Thalamus is acknowledged as the key brain region closely associated with fatigue. However, the thalamus-based neurobiological mechanisms of fatigue in patients with ID remain unknown. METHODS: Forty-two ID patients and twenty-eight well-matched healthy controls (HCs) underwent simultaneous electroencephalography--functional magnetic resonance imaging. We calculated the functional connectivity (FC) between the thalamic seed and each voxel across the whole brain in two conditions of wakefulness--after sleep onset (WASO) and before sleep onset. A linear mixed effect model was used to determine the condition effect of the thalamic FC. The correlation between daytime fatigue and the thalamic connectivity was explored. RESULTS: After sleep onset, the connectivity with the bilateral thalamus was increased in the cerebellar and cortical regions. Compared with HCs, ID patients showed significantly lower FC between left thalamus and left cerebellum under the WASO condition. Furthermore, thalamic connectivity with cerebellum under the WASO condition was negatively correlated with Fatigue Severity Scale scores in the pooled sample. CONCLUSIONS: These findings contribute to an emerging framework that reveals the link between insomnia-related daytime fatigue and the altered thalamic network after sleep onset, further highlighting the possibility that this neural pathway is a therapeutic target for meaningfully mitigating fatigue.

The disruption of white matter integrity of systemic striatal circuits in alcohol-dependent males with physiological cue reactivity.

Alcohol dependence (AD) is a chronic and relapsing disorder. Conditioned cues associated with the rewarding properties of drugs could trigger motivational/physiological reactions and render subjects vulnerable to relapse. Striatal circuit dysfunction has been implicated in alcohol addiction behaviours. However, little is known about the striatal tracts structural connectivity changes underlying cue induced reactivity in AD. In our present study, we recruited 51 patients with AD; 31 individuals had physiological response. We used seed-based classification by probabilistic tractography with nine target masks to explore the white matter integrity of striatal circuits in physiological responders (N = 31), non-responders (N = 20), and healthy controls (N = 27). Compared with healthy controls, physiological responders showed lower fractional anisotropy (FA) and/or higher mean diffusivity in the striatum-dorsolateral prefrontal cortex (dlPFC), striatum-ventral lateral prefrontal cortex, striatum-supplementary motor area (SMA), and striatum-insular. Considering age and smoking are potential nuisances to diffusion parameters, an analysis of covariance also was conducted and similar results were found. We also found the cue-induced physiological response was negatively associated with the FA of the striatum-SMA (r = -0.287; p = 0.045) and left striatum-dlPFC (r = -0.253; p = 0.079) in AD. In our study, we found abnormal integrity of striatal circuit structural connectivity in AD with physiological cue reactivity, especially trajectory from prefrontal cortex and insular. We also found the FA of striatal tracks was negatively associated with the degree of cue reactivity. Our findings provide further evidence for reduced white matter integrity of striatal circuits for cue reactivity in male individuals with AD.

Disrupted diurnal oscillations of the gut microbiota in patients with alcohol dependence.

Background: Patients with alcohol dependence (AD) can exhibit gut dysbacteria. Dysbacteria may co-occur with disruptions of circadian rhythmicity of the gut flora, which can aggravate AD. Herein, this study aimed to investigate diurnal oscillations of the gut microbiota in AD patients. Methods: Thirty-two patients with AD, based on the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, and 20 healthy subjects were enrolled in this study. Demographic and clinical data were collected by self-report questionnaires. Fecal samples at 7:00 AM, 11:00 AM, 3:00 PM, and 7:00 PM were collected from each subject. 16S rDNA sequencing was conducted. Wilcoxon and Kruskal-Wallis tests were performed to characterize alterations and oscillations of the gut microbiota. Results: We found that ß-diversity of the gut microbiota in AD patients oscillated diurnally compared with healthy subjects (p = 0.01). Additionally, 0.66% of operational taxonomic units oscillated diurnally in AD patients versus 1.68% in healthy subjects. At different taxonomic levels, bacterial abundance oscillated diurnally in both groups, such as Pseudomonas and Prevotella pallens (all p < 0.05). ß-diversity of the gut microbiota in AD patients with high daily alcohol consumption, high-level cravings, short AD durations, and mild withdrawal symptoms oscillated diurnally compared with other AD patients (all p < 0.05). Conclusion: The gut microbiota in AD patients exhibits disruptions of diurnal oscillation, which may provide novel insights into mechanisms of AD and the development of therapeutic strategies.

[Identifying Depressive Disorder With Sleep Electroencephalogram Data: A Study Based on Deep Learning].

Objective: To explore the effectiveness of using deep learning network combined Vision Transformer (ViT) and Transformer to identify patients with depressive disorder on the basis of their sleep electroencephalogram (EEG) signals. Methods: The sleep EEG signals of 28 patients with depressive disorder and 37 normal controls were preprocessed. Then, the signals were converted into image format and the feature information on frequency domain and spatial domain was retained. After that, the images were transmitted to the ViT-Transformer coding network for deep learning of the EEG signal characteristics of the rapid eye movement (REM) sleep and non-rapid eye movement (NREM) sleep in patients with depressive disorder and those in normal controls, respectively, and to identify patients with depressive disorder. Results: Based on the ViT-Transformer network, after examining different EEG frequencies, we found that the combination of delta, theta, and beta waves produced better results in identifying depressive disorder. Among the different EEG frequencies, EEG signal features of delta-theta-beta combination waves in REM sleep achieved 92.8% accuracy and 93.8% precision for identifying depression, with the recall rate of patients with depression being 84.7%, and the F0.5 value being 0.917±0.074. When using the delta-theta-beta combination EEG signal features in NREM sleep to identify depressive disorder, the accuracy was 91.7%, the precision was 90.8%, the recall rate was 85.2%, and the F0.5 value was 0.914±0.062. In addition, through visualization of the sleep EEG of different sleep stages for the whole night, it was found that classification errors usually occurred during transition to a different sleep stage. Conclusion: Using the deep learning ViT-Transformer network, we found that the EEG signal features in REM sleep based on delta-theta-beta combination waves showed better effect in identifying depressive disorder.

Efficacy and tolerability of pharmacological treatments for insomnia in adults: A systematic review and network meta-analysis.

Insomnia is one of the most common and burdensome disorders in adults. We compared and ranked insomnia medication on the basis of their efficacy and tolerability. We performed a systematic review and network meta-analysis of placebo-controlled or head-to-head randomized controlled trials for primary insomnia in adults comparing 20 drugs. We searched eight databases and seven trial registers from inception to March 1st, 2022. Primary outcomes included sleep latency (SL), awake time after sleep onset (WASO) and discontinuation for adverse events (AED), and secondary outcomes included total sleep time (TST), sleep efficiency (SE), sleep quality (SQ) and adverse events (ADE). Pooled standardized mean differences or odds ratios with 95% credible intervals were estimated using pairwise and network meta-analysis with random-effects. Differences among trial findings were explored in subgroup and sensitivity analyses. Confidence in evidence was assessed using GRADE. The PROSPERO registered number is CRD42020182144. We identified 22,538 records and included 69 studies (17,319 patients). Orexin receptor antagonists (ORAs) are more efficacious than benzodiazepine-like drugs (Z-drugs) and placebo for WASO and SE, and better than melatonin receptor agonists (MRAs) for SL, WASO and SE. ORAs ranked the best in SL (SUCRA value: 0.84), WASO (0.93), TST (0.86) and SE (0.96). Lemborexant and daridorexant (two ORAs) showed greater efficacy than placebo for SL, WASO, and TST, with good tolerability. Z-drugs were more efficacious than placebo for SL, WASO, TST and SE, but with higher risk to safety. Zaleplon and eszopiclone had better efficacy than placebo for TST and SQ respectively. MRAs may also be efficacious for sleep-onset insomnia with good safety. However, the long-term adverse effects of all medications are unclear. Insomnia medications differ in their efficacy and tolerability. ORAs have superior efficacy and tolerability. These findings should aid clinicians in matching risk/benefits of drugs available in their countries to insomnia symptoms.

State-dependent and region-specific alterations of cerebellar connectivity across stable human wakefulness and NREM sleep states.

Sleep regulation and functioning may rely on systematic coordination throughout the whole brain, including the cerebellum. However, whether and how interactions between the cerebellum and other brain regions vary across sleep stages remain poorly understood. Here, using simultaneous EEG-fMRI recordings captured from 73 participants during wakefulness and non-rapid eye movement (NREM) sleep, we constructed cerebellar connectivity among intrinsic functional networks with intra-cerebellar, neocortical and subcortical regions. We uncovered that cerebellar connectivity exhibited sleep-dependent alterations: slight differences between wakefulness and N1/N2 sleep and greater changes in N3 sleep than other states. Region-specific cerebellar connectivity changes between N2 sleep and N3 sleep were also revealed: general breakdown of intra-cerebellar connectivity, enhancement of limbic-cerebellar connectivity and alterations of cerebellar connectivity with spatially specific neocortices. Further correlation analysis showed that functional connectivity between the cerebellar Control II network and regions (including the insula, hippocampus, and amygdala) correlated with delta power during N3 and beta power during N2 sleep. These findings systematically reveal altered cerebellar connectivity among intrinsic networks from wakefulness to deep sleep and highlight the potential role of the cerebellum in sleep regulation and functioning.

Increased connectivity of the anterior cingulate cortex is associated with the tendency to awakening during N2 sleep in patients with insomnia disorder.

STUDY OBJECTIVES: To investigate the relationship between sleep transition dynamics and stage-specific functional connectivity (FC) of the anterior cingulate cortex (ACC) in patients with insomnia disorder (ID). METHODS: Simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) data from 37 patients with ID and 30 well-matched healthy controls (HCs) were recorded during wakefulness and different sleep stages and subsequently analyzed. A Markov chain model was used to estimate the transition probability between each stage. The FC between the ACC (set as the seed) and voxels across the whole brain was calculated. A linear mixed effect model was used to determine the group-by-stage interaction of the seed-based connectivity. The correlation between the sleep-stage transition probability and the ACC-based connectivity was explored. RESULTS: Patients with ID exhibited a higher likelihood of transitioning from N2 to wakefulness than HCs. A significant group-by-stage interaction of connectivity with the bilateral ACC was observed in the cerebellar, subcortical, and cortical regions. Moreover, a significant positive correlation was found in patients with ID between the transition probability from N2 to wakefulness and the FC of the ACC with the anterior cerebellum in N2 (r = 0.48). CONCLUSIONS: This exploratory analysis indicates that enhanced FC between the ACC and cerebellum represents a potential neural pathway underlying the greater likelihood of patients with ID waking during N2 sleep. These findings contribute to an emerging framework that reveals the link between sleep maintenance difficulty and ACC function, further highlighting the possibility that N2 sleep is a therapeutic target for meaningfully reducing sleep disruption.