Increased sleep pressure reduces resting state functional connectivity

Heterogeneity in functional connectivity: Dimensional predictors of individual variability during rest and task fMRI in psychosis

BACKGROUND

Individuals with schizophrenia spectrum disorders (SSD) often demonstrate cognitive impairments, associated with poor functional outcomes. While neurobiological heterogeneity has posed challenges when examining social cognition in SSD, it provides a unique opportunity to explore brain-behavior relationships. The aim of this study was to investigate the relationship between individual variability in functional connectivity during resting state and the performance of a social task and social and non-social cognition in a large sample of controls and individuals diagnosed with SSD.

METHODS

Neuroimaging and behavioral data were analyzed for 193 individuals with SSD and 155 controls (total n = 348). Individual variability was quantified through mean correlational distance (MCD) of functional connectivity between participants; MCD was defined as a global 'variability score'. Pairwise correlational distance was calculated as 1 - the correlation coefficient between a given pair of participants, and averaging distance from one participant to all other participants provided the mean correlational distance metric. Hierarchical regressions were performed on variability scores derived from resting state and Empathic Accuracy (EA) task functional connectivity data to determine potential predictors (e.g., age, sex, neurocognitive and social cognitive scores) of individual variability.

RESULTS

Group comparison between SSD and controls showed greater SSD MCD during rest (p = 0.00038), while no diagnostic differences were observed during task (p = 0.063). Hierarchical regression analyses demonstrated the persistence of a significant diagnostic effect during rest (p = 0.008), contrasting with its non-significance during the task (p = 0.50), after social cognition was added to the model. Notably, social cognition exhibited significance in both resting state and task conditions (both p = 0.01).

CONCLUSIONS

Diagnostic differences were more prevalent during unconstrained resting scans, whereas the task pushed participants into a more common pattern which better emphasized transdiagnostic differences in cognitive abilities. Focusing on variability may provide new opportunities for interventions targeting specific cognitive impairments to improve functional outcomes.

Impact of one night of sleep restriction on sleepiness and cognitive function: A systematic review and meta-analysis

Detrimental consequences of chronic sleep restriction on cognitive function are well established in the literature. However, effects of a single night of sleep restriction remain equivocal. Therefore, we synthesized data from 44 studies to investigate effects of sleep restriction to 2-6 h sleep opportunity on sleepiness and cognition in this meta-analysis. We investigated subjective sleepiness, sustained attention, choice reaction time, cognitive throughput, working memory, and inhibitory control. Results revealed a significant increase in subjective sleepiness following one night of sleep restriction (Standardized Mean Difference (SMD) = 0.986, p < 0.001), while subjective sleepiness was not associated with sleep duration during sleep restriction (β = -0.214, p = 0.039, significance level 0.01). Sustained attention, assessed via common 10-min tasks, was impaired, as demonstrated through increased reaction times (SMD = 0.512, p < 0.001) and attentional lapses (SMD = 0.489, p < 0.001). However, the degree of impaired attention was not associated with sleep duration (ps > 0.090). We did not find significant effects on choice reaction time, cognitive throughput, working memory, or inhibitory control. Overall, results suggest that a single night of restricted sleep can increase subjective sleepiness and impair sustained attention, a cognitive function crucial for everyday tasks such as driving.

Sleep Disordered Breathing and Risk for ADHD: Review of Supportive Evidence and Proposed Underlying Mechanisms

BACKGROUND

Accumulating evidence suggests that sleep disordered breathing (SDB) is under-recognized in youth and adults with ADHD. SDB may contribute to exacerbating pre-existing ADHD symptoms and may play a role in the development of cognitive deficits that may mimic ADHD symptoms.

METHOD

We conducted a focused review of publications on cross-prevalence, overlapping clinical and neurobiological characteristics and possible mechanisms linking SDB and ADHD.

RESULTS

Exiting studies suggest that co-occurrence of SDB and ADHD is as high as 50%, with frequent overlap of clinical symptoms such as distractibility and inattention. Mechanisms linking these conditions may include hypoxia during sleep, sleep fragmentation and activation of inflammation, all of which may affect brain structure and physiology to produce disturbances in attention.

CONCLUSIONS

The relationship between SDB and ADHD symptoms appear well-supported and suggests that more research is needed to better optimize procedures for SDB assessment in youth being evaluated and/or treated for ADHD.

EEG Information Transfer Changes in Different Daily Fatigue Levels During Drowsy Driving

A significant issue for traffic safety has been drowsy driving for decades. A number of studies have investigated the effects of acute fatigue on spectral power; and recent research has revealed that drowsy driving is associated with a variety of brain connections in a specific cortico-cortical pathway. In spite of this, it is still unclear how different brain regions are connected in drowsy driving at different levels of daily fatigue. This study identified the brain connectivity-behavior relationship among three different daily fatigue levels (low-, median- and high-fatigue) with the EEG data transfer entropy. According to the results, only low- and medium-fatigue groups demonstrated an inverted U-shaped change in connectivity from high performance to poor behavioral performance. In addition, from low- to high-fatigue groups, connectivity magnitude decreased in the frontal region and increased in the occipital region. These study results suggest that brain connectivity and driving behavior would be affected by different levels of daily fatigue.

Neural basis underlying the relation between internet addiction tendency and sleep quality: The intrinsic default-mode network connectivity pathways

Internet addiction (IA) tendency is considered an addictive behavior that results from excessive Internet use, and severely affecting an individual's physical health, emotion, and sleep. Although previous studies indicated that IA tendency was negatively correlated with sleep quality, the underlying neural basis of this relationship remained unclear. To address this issue, we utilized resting-state functional connectivity (RSFC) analysis to identify the neural pathways of the relationship between IA tendency and sleep quality. The behavioral results indicated a positive correlation between these two factors. And RSFC results revealed that IA tendency was positively related to the strength of functional connectivity within the default-mode network (DMN), including the right precuneus-left middle temporal gyrus (rPrcu-lMTG), the left anterior cingulate-left superior frontal gyrus (lAC-lSFG), and the left inferior parietal lobe-left medial superior frontal gyrus (lIPL-lMSFG). More importantly, mediation analysis demonstrated that IA tendency could mediate the relationship between these functional couplings and sleep quality. In conclusion, our findings suggest that intrinsic DMN connectivity may be an important neural pathways underlying the effects of IA tendency on sleep quality, and provide neural evidence for understanding the relationship between IA tendency and sleep quality.

Effect of total sleep deprivation on effective EEG connectivity for young male in resting-state networks in different eye states

Background

Many studies have investigated the effect of total sleep deprivation (TSD) on resting-state functional networks, especially the default mode network (DMN) and sensorimotor network (SMN), using functional connectivity. While it is known that the activities of these networks differ based on eye state, it remains unclear how TSD affects them in different eye states. Therefore, we aimed to examine the effect of TSD on DMN and SMN in different eye states using effective functional connectivity via isolated effective coherence (iCoh) in exact low-resolution brain electromagnetic tomography (eLORETA).

Methods

Resting-state electroencephalogram (EEG) signals were collected from 24 male college students, and each participant completed a psychomotor vigilance task (PVT) while behavioral data were acquired. Each participant underwent 36-h TSD, and the data were acquired in two sleep-deprivation times (rested wakefulness, RW: 0 h; and TSD: 36 h) and two eye states (eyes closed, EC; and eyes open, EO). Changes in neural oscillations and effective connectivity were compared based on paired t-test.

Results

The behavioral results showed that PVT reaction time was significantly longer in TSD compared with that of RW. The EEG results showed that in the EO state, the activity of high-frequency bands in the DMN and SMN were enhanced compared to those of the EC state. Furthermore, when compared with the DMN and SMN of RW, in TSD, the activity of DMN was decreased, and SMN was increased. Moreover, the changed effective connectivity in the DMN and SMN after TSD was positively correlated with an increased PVT reaction time. In addition, the effective connectivity in the different network (EO-EC) of the SMN was reduced in the β band after TSD compared with that of RW.

Conclusion

These findings indicate that TSD impairs alertness and sensory information input in the SMN to a greater extent in an EO than in an EC state.

Reduced Resting-State EEG Power Spectra and Functional Connectivity after 24 and 36 Hours of Sleep Deprivation

Total sleep deprivation (TSD) leads to cognitive decline; however, the neurophysiological mechanisms underlying resting-state electroencephalogram (EEG) changes after TSD remain unclear. In this study, 42 healthy adult participants were subjected to 36 h of sleep deprivation (36 h TSD), and resting-state EEG data were recorded at baseline, after 24 h of sleep deprivation (24 h TSD), and after 36 h TSD. The analysis of resting-state EEG at baseline, after 24 h TSD, and after 36 h TSD using source localization analysis, power spectrum analysis, and functional connectivity analysis revealed a decrease in alpha-band power and a significant increase in delta-band power after TSD and impaired functional connectivity in the default mode network, precuneus, and inferior parietal lobule. The cortical activities of the precuneus, inferior parietal lobule, and superior parietal lobule were significantly reduced, but no difference was found between the 24 h and 36 h TSD groups. This may indicate that TSD caused some damage to the participants, but this damage temporarily slowed during the 24 h to 36 h TSD period.

Getting a Good Night's Sleep: Associations Between Sleep Duration and Parent-Reported Sleep Quality on Default Mode Network Connectivity in Youth

PURPOSE

Sleep plays an important role in healthy neurocognitive development, and poor sleep is linked to cognitive and emotional dysfunction. Studies in adults suggest that shorter sleep duration and poor sleep quality may disrupt core neurocognitive networks, particularly the default mode network (DMN)-a network implicated in internal cognitive processing and rumination. Here, we examine the relationships between sleep and within- and between-network resting-state functional connectivity (rs-FC) of the DMN in youth.

METHODS

This study included 3,798 youth (11.9 ± 0.6 years, 47.5% female) from the Adolescent Brain Cognitive Development cohort. Sleep duration and wake after sleep onset (WASO) were quantified using Fitbit watch recordings, and parent-reported sleep disturbances were measured using the Sleep Disturbance Scale for Children. We focused on rs-FC between the DMN and anticorrelated networks (i.e., dorsal attention network [DAN], frontoparietal network, salience network).

RESULTS

Both shorter sleep duration and greater sleep disturbances were associated with weaker within-network DMN rs-FC. Shorter sleep duration was also associated with weaker anticorrelation (i.e., higher rs-FC) between the DMN and two anticorrelated networks: the DAN and frontoparietal network. Greater WASO was also associated with DMN-DAN rs-FC, and the effects of WASO on rs-FC were most pronounced among children who slept fewer hours/night.

DISCUSSION

Together, these data suggest that different aspects of sleep are associated with distinct and interactive alterations in resting-state brain networks. Alterations in core neurocognitive networks may confer increased risk for emotional psychopathology and attention-related vulnerabilities. Our findings contribute to the growing number of studies demonstrating the importance of healthy sleep practices in youth.

Preliminary Development of a Brainwave Model for K1 Kickboxers Using Quantitative Electroencephalography (QEEG) with Open Eyes

K1 kickboxing fighting is characterised by high injury rates due to the low restrictions of fighting rules. In recent years, much attention has been paid to research on changes in brain function among athletes, including those in combat sports. One of the tools that are likely to help diagnose and assess brain function is quantitative electroencephalography (QEEG). Therefore, the aim of the present study was an attempt to develop a brainwave model using quantitative electroencephalography in competitive K1 kickboxers. A total of thirty-six male individuals were purposefully selected and then comparatively divided into two groups. The first group consisted of specialised K1 kickboxing athletes exhibiting a high level of sports performance (experimental group, n = 18, mean age: 29.83 ± 3.43), while the second group comprised healthy individuals not training competitively (control group, n = 18, mean age: 26.72 ± 1.77). Body composition assessment was performed in all participants before the main measurement process. Measurements were taken for kickboxers during the de-training period, after the sports competition phase. Quantitative electroencephalography of Delta, Theta, Alpha, sensimotor rhytm (SMR), Beta1 and Beta2 waves was performed using electrodes placed on nine measurement points (frontal: FzF3F4, central: CzC3C4, and parietal: PzP3P4) with open eyes. In the course of the analyses, it was found that the level of brain activity among the study population significantly differentiated the K1 formula competitors compared with the reference standards and the control group in selected measurement areas. For kickboxers, all results of the Delta amplitude activity in the area of the frontal lobe were significantly above the normative values for this wave. The highest value was recorded for the average value of the F3 electrode (left frontal lobe), exceeding the norm by 95.65%, for F4 by 74.45% and Fz by 50.6%, respectively. In addition, the Alpha wave standard value for the F4 electrode was exceeded by 14.6%. Normative values were found for the remaining wave amplitudes. Statistically significant differentiation of results, with a strong effect (d = 1.52-8.41), was shown for the activity of Delta waves of the frontal area and the central part of the parietal area (Fz,F3,F4,Cz-p < 0.001), Theta for the frontal area as well as the central and left parietal lobes (Fz,F3,F4-p < 0.001, Cz-p = 0.001, C3-p = 0.018; d = 1.05-3.18), Alpha for the frontal, parietal and occipital areas (for: Fz,F3-p < 0.001, F4-p = 0.036, Cz-p < 0.001, C3-p = 0.001, C4-p = 0.025, Pz-p = 0.010, P3-p < 0.001, P4-p = 0.038; d = 0.90-1.66), SMR for the central parietal and left occipital lobes (Cz-p = 0.043; d = 0.69, P3-p < 0.001; d = 1.62), Beta for the frontal area, occipital and central lobes and left parietal segment (Fz,F3-p < 0.001, F4-p = 0.008, Cz, C3, Pz, P3,P4-p < 0.001; d = 1.27-2.85) and Beta 2 for all measurement areas (Fz, F3, F4, Cz, C3, C4, Pz, P3, P4-p < 0.001; d = 1.90-3.35) among the study groups. Significantly higher results were shown in the kickboxer group compared to the control. In addition to problems with concentration or over-stimulation of neural structures, high Delta waves, with elevated Alpha, Theta and Beta 2 waves, can cause disorders in the limbic system and problems in the cerebral cortex.

Sleep Loss Influences the Interconnected Brain-Body Regulation of Cardiovascular Function in Humans

OBJECTIVE

Poor sleep is associated with hypertension, a major risk factor for cardiovascular disease. However, the mechanism(s) through which sleep loss affects cardiovascular health remains largely unknown, including the brain and body systems that regulate vascular function.

METHODS

Sixty-six healthy adults participated in a repeated-measures, crossover, experimental study involving assessments of cardiovascular function and brain connectivity after a night of sleep and a night of sleep deprivation.

RESULTS

First, sleep deprivation significantly increased blood pressure-both systolic and diastolic. Interestingly, this change was independent of any increase in heart rate, inferring a vasculature-specific rather than direct cardiac pathway. Second, sleep loss compromised functional brain connectivity within the vascular control network, specifically the insula, anterior cingulate, amygdala, and ventral and medial prefrontal cortices. Third, sleep loss-related changes in brain connectivity and vascular tone were not independent, but significantly interdependent, with changes within the vascular control brain network predicting the sleep-loss shift toward hypertension.

CONCLUSIONS

These findings establish an embodied framework in which sleep loss confers increased risk of cardiovascular disease through an impact upon central brain control of vascular tone, rather than a direct impact on accelerated heart rate itself.

Adolescent sleep and the foundations of prefrontal cortical development and dysfunction

Modern life poses many threats to good-quality sleep, challenging brain health across the lifespan. Curtailed or fragmented sleep may be particularly damaging during adolescence, when sleep disruption by delayed chronotypes and societal pressures coincides with our brains preparing for adult life via intense refinement of neural connectivity. These vulnerabilities converge on the prefrontal cortex, one of the last brain regions to mature and a central hub of the limbic-cortical circuits underpinning decision-making, reward processing, social interactions and emotion. Even subtle disruption of prefrontal cortical development during adolescence may therefore have enduring impact. In this review, we integrate synaptic and circuit mechanisms, glial biology, sleep neurophysiology and epidemiology, to frame a hypothesis highlighting the implications of adolescent sleep disruption for the neural circuitry of the prefrontal cortex. Convergent evidence underscores the importance of acknowledging, quantifying and optimizing adolescent sleep's contributions to normative brain development and to lifelong mental health.

Shared brain and genetic architectures between mental health and physical activity

Physical activity is correlated with, and effectively treats various forms of psychopathology. However, whether biological correlates of physical activity and psychopathology are shared remains unclear. Here, we examined the extent to which the neural and genetic architecture of physical activity and mental health are shared. Using data from the UK Biobank (N = 6389), we applied canonical correlation analysis to estimate associations between the amplitude and connectivity strength of subnetworks of three major neurocognitive networks (default mode, DMN; salience, SN; central executive networks, CEN) with accelerometer-derived measures of physical activity and self-reported mental health measures (primarily of depression, anxiety disorders, neuroticism, subjective well-being, and risk-taking behaviors). We estimated the genetic correlation between mental health and physical activity measures, as well as putative causal relationships by applying linkage disequilibrium score regression, genomic structural equational modeling, and latent causal variable analysis to genome-wide association summary statistics (GWAS N = 91,105-500,199). Physical activity and mental health were associated with connectivity strength and amplitude of the DMN, SN, and CEN (r's ≥ 0.12, p's < 0.048). These neural correlates exhibited highly similar loading patterns across mental health and physical activity models even when accounting for their shared variance. This suggests a largely shared brain network architecture between mental health and physical activity. Mental health and physical activity (including sleep) were also genetically correlated (|rg| = 0.085-0.121), but we found no evidence for causal relationships between them. Collectively, our findings provide empirical evidence that mental health and physical activity have shared brain and genetic architectures and suggest potential candidate subnetworks for future studies on brain mechanisms underlying beneficial effects of physical activity on mental health.

Isolation of subjectively reported sleepiness and objectively measured vigilance during sleep deprivation: a resting-state fMRI study

Subjectively reported sleepiness and objectively measured vigilance are often used to assess and monitor operating performance. Evidence suggests that the response patterns of the two measures are independent of each other. However, the neural mechanism underlying this phenomenon remains unclear. This study aimed to investigate whether subjective sleepiness and objective vigilance were associated with each other. Thirty-three participants were subjected to 34 h of acute sleep deprivation. We collected sleepiness, vigilance, and resting-state fMRI data. We also located the neural mechanism of isolation of object and subject parameters. Firstly, the correlation analysis showed that there was no statistically significant correlation between the changes in vigilance and sleepiness during the sleep deprivation period. Then, implementing the support vector machine algorithm through functional connectivities as features, we found that different functional connectivity patterns underline the isolation of these two factors during sleep deprivation. The functional connectivities involved in characterizing the vulnerability of objective vigilance are more extensive, involving the connectivities within the sensorimotor network, between the subcortical and cortical network, and among multiple cortical networks. The functional connectivity involved in characterizing the vulnerability of subjective sleepiness is limited to the communication between the subcortical thalamus and the somatosensory cortex. In addition, we found that implementing global signal regression would reduce the model's power to predict vigilance and sleepiness. This work contributes to our understanding of how sleep deprivation affects individual cognition and behavior, and will be of use in the evaluation and prediction of cognitive performance during sleep loss.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-021-09772-0.

Distinct neural responses of morningness and eveningness chronotype to homeostatic sleep pressure revealed by resting-state functional magnetic resonance imaging

Background

Chronotype is an appropriate variable to investigate sleep homeostatic and circadian rhythm. Based on functional MRI, the resting‐state functional connectivity (rsFC) of insula‐angular decrease with the increase in homeostatic sleep pressure (HSP). However, the distinct neural response of different chronotype remained to be clarified. Therefore, we investigated how HSP influenced insular‐angular neural interaction of different chronotype.

Methods

64 morningness‐chronotype (MCPs) and 128 eveningness‐chronotype participants (ECPs) received resting‐state functional MRI (rsfMRI) scan. HSP was divided into three levels (Low, Medium, and High) based on the elapsed time awake. Insular‐angular rsFC was calculated for MCPs and ECPs on each HSP.

Results

As the levels of HSP increased, the negative rsFC between right insular and bilateral angular increased in MCPs while decreased in ECPs. Specifically, ECPs compared with MCPs showed lower rsFC at medium levels of HSP, but higher rsFC at high levels of HSP. In addition, ECPs compared with MCPs exhibited lower rsFC between right insular and right angular at low levels of HSP.

Conclusion

The distinct modes of rsFC was found in different chronotype in response to HSP. The results provided the foundation and evidence for investigating the processes of circadian rhythm and sleep homeostatic.

Changes in ventromedial prefrontal cortex functional connectivity are correlated with increased risk-taking after total sleep deprivation

There is evidence indicating that people are more likely to take risks when they are sleep-deprived than during resting wakefulness (RW). The ventromedial prefrontal cortex (vmPFC) could have a crucial psychophysiological role in this phenomenon. However, the intrinsic patterns of functional organization of the human vmPFC and their relationship with risk-taking during sleep deprivation (SD) are unclear. This study investigated the relationship between functional connectivity in the vmPFC and cerebral cortex and the risk-taking tendency after SD. The study participants were 21 healthy college students who underwent functional magnetic resonance imaging twice in the resting state, once during RW and once after 36 h of SD. The vmPFC was analyzed bilaterally for functional connectivity between the regions of interest. Correlation analysis was performed to evaluate changes in functional connectivity between the vmPFC and the cerebral cortex and risk-taking before and after SD. A single night of SD produced a definite deficit in functional connectivity between the vmPFC and thalamus bilaterally and an increase in functional connectivity between the vmPFC and dorsolateral prefrontal cortex (dlPFC) and the parietal lobe. We also found that the likelihood of risk-taking was positively correlated with increased functional connectivity between the vmPFC and dlPFC and negatively correlated with decreased functional connectivity between the vmPFC and thalamus bilaterally. These results demonstrate that lack of sleep substantially impairs functional connectivity between the vmPFC and the cerebral cortex, which in turn predicts the risk-taking behavior found after SD.

Functional connectome mediates the association between sleep disturbance and mental health in preadolescence: A longitudinal mediation study

Sleep disturbance is known to be associated with various mental disorders and often precedes the onset of mental disorders in youth. Given the increasingly acknowledged bidirectional influence between sleep disturbance and mental disorders, we aim to identify a shared neural mechanism that underlies sleep disturbance and mental disorders in preadolescents. We analyzed a dataset of 9,350 9–10 year‐old children, among whom 8,845 had 1‐year follow‐up data, from the Adolescent Brain Cognitive Development (ABCD) study. Linear mixed‐effects models, mediation analysis, and longitudinal mediation analysis were used to investigate the relationship between sleep disturbance, mental disorders, and resting‐state network connectivity. Out of 186 unique connectivities, the effect of total sleep disturbance (TSP, from Sleep Disturbance Scale) and mental problems (MP, from Child Behavior Checklist) converged in the default mode network (DMN) and the dorsal attention network (DAN). Within‐ and between‐network connectivities (DMN‐DAN, DMN‐DMN, DAN‐DAN) mediated the relationship between baseline TSD and MP at 1‐year follow‐up and the relationship between baseline MP and TSD at 1‐year follow‐up. The pathway model in which sleep disturbance and mental problems affect each other through two anticorrelated brain networks (DMN and DAN) suggests a common neural mechanism between them. Longitudinally, a less segregated DMN and DAN is associated with negative outcomes on mental well‐being and sleep disturbance a year later. These findings have important implications for the design of prevention and neurofeedback intervention for mental disorders and sleep problems.

Bidirectional Association Between Sleep and Brain Atrophy in Aging

Human brain aging is characterized by the gradual deterioration of its function and structure, affected by the interplay of a multitude of causal factors. The sleep, a periodically repeating state of reversible unconsciousness characterized by distinct electrical brain activity, is crucial for maintaining brain homeostasis. Indeed, insufficient sleep was associated with accelerated brain atrophy and impaired brain functional connectivity. Concurrently, alteration of sleep-related transient electrical events in senescence was correlated with structural and functional deterioration of brain regions responsible for their generation, implying the interconnectedness of sleep and brain structure. This review discusses currently available data on the link between human brain aging and sleep derived from various neuroimaging and neurophysiological methods. We advocate the notion of a mutual relationship between the sleep structure and age-related alterations of functional and structural brain integrity, pointing out the position of high-quality sleep as a potent preventive factor of early brain aging and neurodegeneration. However, further studies are needed to reveal the causality of the relationship between sleep and brain aging.

Task-based and Resting State Functional MRI in Children

Functional MR imaging (MRI) is a valuable tool for presurgical planning and is well established in adult patients. The use of task-based fMRI is increasing in pediatric populations because it provides similar benefits for pre-surgical planning in children. This article reviews special adaptations that are required for successful applications of task-based fMRI in children, especially in the motor and language systems. The more recently introduced method of resting state fMRI is reviewed and its relative advantages and disadvantages discussed. Common pitfalls and other systems and networks that may be of interest in special circumstances also are reviewed.

Altered cerebrocerebellar functional connectivity in patients with obstructive sleep apnea and its association with cognitive function

STUDY OBJECTIVES

Previous functional MRI studies have reported altered brain networks in patients with obstructive sleep apnea (OSA). However, the extent and pattern of abnormal connectivity were inconsistent across studies, and cerebrocerebellar connections have been rarely assessed. We investigated functional network changes in cerebral and cerebellar cortices of OSA patients.

METHODS

Resting-state functional MRI, polysomnography and neuropsychological (NP) test data were acquired from 74 OSA patients (age: 45.8±10.7 years) and 33 healthy subjects (39.6±9.3 years). Connectivity matrices were extracted by computing correlation coefficients from various ROIs, and Fisher r-to-z transformations. In the functional connections that showed significant group differences, linear regression was conducted to examine the association between connectivity and clinical characteristics.

RESULTS

Patients with OSA showed reduced functional connectivity (FC) in cerebrocerebellar connections linking different functional networks, and greater FC in cortical between-network connections in prefrontal regions involving the default mode network and the control network. For OSA group, we found no correlation between FC and sleep parameters including lowest SaO2 and arousal index in the connections where significant associations were observed in healthy subjects. FC changes in default mode network (DMN) areas were related to reduced verbal fluency in OSA. Lower local efficiency and lower clustering coefficient of the salience network in the left cerebellum were also observed in OSA.

CONCLUSIONS

OSA affects mainly the cerebrocerebellar pathway. The disruption of function in these connections are related to sleep fragmentation and hypoxia during sleep. These abnormal network functions, especially DMN, are suggested to participate in cognitive decline of OSA.

Sleep inconsistency between weekends and weekdays is associated with changes in brain function during task and rest

STUDY OBJECTIVES

Sleep deprivation and circadian disruptions impair brain function and cognitive performance, but few studies have examined the effect of sleep inconsistency. Here, we investigated how inconsistent sleep duration and sleep timing between weekends (WE) and weekdays (WD) correlated with changes in behavior and brain function during task and at rest in 56 (30 female) healthy human participants.

METHODS

WE-WD differences in sleep duration and sleep midpoint were calculated using 1-week actigraphy data. All participants underwent 3 Tesla blood-oxygen-level-dependent functional Magnetic Resonance Imaging (fMRI) to measure brain activity during a visual attention task (VAT) and in resting-state condition.

RESULTS

We found that WE-WD inconsistency of sleep duration and sleep midpoint were uncorrelated with each other (r = .08, p = .58) and influenced behavior and brain function differently. Our healthy participants showed relatively small WE-WD differences (WE-WD: 0.59 hours). Longer WE sleep duration (relative to WD sleep duration) was associated with better attentional performance (3-ball: β = .30, t = 2.35, p = .023; 4-ball: β = .30, t = 2.21, p = .032) and greater deactivation of the default mode network (DMN) during VAT (p < .05, cluster-corrected) and greater resting-state functional connectivity (RSFC) between anterior DMN and occipital cortex (p < .01, cluster-corrected). In contrast, later WE sleep timing (relative to WD sleep timing) (WE-WD: 1.11 hours) was associated with worse performance (4-ball: β = -.33, t = -2.42, p = .020) and with lower occipital activation during VAT and with lower RSFC within the DMN.

CONCLUSIONS

Our results document the importance of consistent sleep timing for brain function in particular of the DMN and provide evidence of the benefits of WE catch-up sleep in healthy adults.

Regional brain metabolism differentiates narcolepsy type 1 and idiopathic hypersomnia

STUDY OBJECTIVES

Daytime sleepiness is a manifestation of multiple sleep and neurologic disorders. Few studies have assessed patterns of regional brain metabolism across different disorders of excessive daytime sleepiness. One such disorder, idiopathic hypersomnia (IH), is particularly understudied.

METHODS

People with IH, narcolepsy (NT1), and non-sleepy controls underwent [ 18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) with electroencephalography (EEG). Participants were instructed to resist sleep and were awoken if sleep occurred. Voxel-wise parametric analysis identified clusters that significantly differed between each pair of groups, with a minimum cluster size of 100 voxels at a cluster detection threshold of p < 0.005. Correlations between glucose metabolism and sleep characteristics were evaluated.

RESULTS

Participants (77% women) had IH (n = 16), NT1 (n = 14), or were non-sleepy controls (n = 9), whose average age was 33.8 (+/-10.7) years. Compared to controls, NT1 participants demonstrated hypermetabolism in fusiform gyrus, middle occipital gyrus, superior and middle temporal gyri, insula, cuneus, precuneus, pre- and post-central gyri, and culmen. Compared to controls, IH participants also demonstrated hypermetabolism in precuneus, inferior parietal lobule, superior and middle temporal gyri, and culmen. Additionally, IH participants demonstrated altered metabolism of the posterior cingulate. Most participants fell asleep. Minutes of N1 during uptake was significantly negatively correlated with metabolism of the middle temporal gyrus.

CONCLUSION

NT1 and IH demonstrate somewhat overlapping, but distinct, patterns of regional metabolism.

Decreased resting-state alpha-band activation and functional connectivity after sleep deprivation

Cognitive abilities are impaired by sleep deprivation and can be recovered when sufficient sleep is obtained. Changes in alpha-band oscillations are considered to be closely related to sleep deprivation. In this study, power spectrum, source localization and functional connectivity analyses were used to investigate the changes in resting-state alpha-band activity after normal sleep, sleep deprivation and recovery sleep. The results showed that the global alpha power spectrum decreased and source activation was notably reduced in the precuneus, posterior cingulate cortex, cingulate gyrus, and paracentral lobule after sleep deprivation. Functional connectivity analysis after sleep deprivation showed a weakened functional connectivity pattern in a widespread network with the precuneus and posterior cingulate cortex as the key nodes. Furthermore, the changes caused by sleep deprivation were reversed to a certain extent but not significantly after one night of sleep recovery, which may be due to inadequate time for recovery sleep. In conclusion, large-scale resting-state alpha-band activation and functional connectivity were weakened after sleep deprivation, and the inhibition of default mode network function with the precuneus and posterior cingulate cortex as the pivotal nodes may be an important cause of cognitive impairment. These findings provide new insight into the physiological response to sleep deprivation and determine how sleep deprivation disrupts brain alpha-band oscillations.

Brain functional connectivity upon awakening from sleep predicts interindividual differences in dream recall frequency

Why do some individuals recall dreams every day while others hardly ever recall one? We hypothesized that sleep inertia-the transient period following awakening associated with brain and cognitive alterations-could be a key mechanism to explain interindividual differences in dream recall at awakening. To test this hypothesis, we measured the brain functional connectivity (combined electroencephalography-functional magnetic resonance imaging) and cognition (memory and mental calculation) of high dream recallers (HR, n = 20) and low dream recallers (LR, n = 18) in the minutes following awakening from an early-afternoon nap. Resting-state scans were acquired just after or before a 2 min mental calculation task, before the nap, 5 min after awakening from the nap, and 25 min after awakening. A comic was presented to the participants before the nap with no explicit instructions to memorize it. Dream(s) and comic recall were collected after the first post-awakening scan. As expected, between-group contrasts of the functional connectivity at 5 min post-awakening revealed a pattern of enhanced connectivity in HR within the default mode network (DMN) and between regions of the DMN and regions involved in memory processes. At the behavioral level, a between-group difference was observed in dream recall, but not comic recall. Our results provide the first evidence that brain functional connectivity right after awakening is associated with interindividual trait differences in dream recall and suggest that the brain connectivity of HR at awakening facilitates the maintenance of the short-term memory of the dream during the sleep-wake transition.

Disrupted prefrontal neuronal oscillations and morphology induced by sleep deprivation in young APP/PS1 transgenic AD mice

Emerging evidence suggests that sleep deprivation (SD) is a public health epidemic and increase the risk of Alzheimer's disease (AD) progression. However, the underlying mechanisms remain to be fully investigated. In this study, we investigate the impact of 72 h SD on the prefrontal cortex (PFC) of 3∼4-months-old APP/PS1 transgenic AD mice - at an age before the onset of plaque formation and memory decline. Our results reveal that SD alters delta, theta and high-gamma oscillations in the PFC, accompanied by increased levels of excitatory postsynaptic signaling (NMDAR, GluR1, and CaMKII) in AD mice. SD also caused alteration in the dendritic length and dendritic branches of PFC pyramidal neurons, accompanied by a reduction in neuroprotective agent CREB. This study suggests that failure to acquire adequate sleep could trigger an early electrophysiological, molecular, and morphological alteration in the PFC of AD mice. Therapeutic interventions that manipulate sleep by targeting these pathways may be a promising approach toward delaying the progression of this incurable disease.

Waking EEG functional connectivity in middle-aged and older adults with obstructive sleep apnea

OBJECTIVES

The present study aimed at investigating changes in waking electroencephalography (EEG), most specifically regarding spectral power and functional connectivity, in middle-aged and older adults with obstructive sleep apnea (OSA). We also explored whether changes in spectral power or functional connectivity are associated with polysomnographic characteristics and/or neuropsychological performance.

METHODS

In sum, 19 OSA subjects (apnea-hypopnea index ≥ 20, age: 63.6 ± 6.4) and 22 controls (apnea-hypopnea index ≤ 10, age: 63.6 ± 6.7) underwent a full night of in-laboratory polysomnography (PSG) followed by a waking EEG and a neuropsychological assessment. Waking EEG spectral power and imaginary coherence were compared between groups for all EEG frequency bands and scalp regions. Correlation analyses were performed between selected waking EEG variables, polysomnographic parameters and neuropsychological performance.

RESULTS

No group difference was observed for EEG spectral power for any frequency band. Regarding the imaginary coherence, when compared to controls, OSA subjects showed decreased EEG connectivity between frontal and temporal regions in theta and alpha bands as well as increased connectivity between frontal and parietal regions in delta and beta 1 bands. In the OSA group, these changes in connectivity correlated with lower sleep efficiency, lower total sleep time and higher apnea-hypopnea index. No relationship was found with neuropsychological performance.

CONCLUSIONS

Contrary to spectral power, imaginary coherence was sensitive enough to detect changes in brain function in middle-aged and older subjects with OSA when compared to controls. Whether these changes in cerebral connectivity predict cognitive decline needs to be investigated longitudinally.

Functional Connectivity Abnormalities of Brain Regions With Structural Deficits in Primary Insomnia Patients

OBJECTIVES

The present study examined the abnormal resting state functional connections (RSFCs) in structural deficit brain regions of primary insomnia (PI) patients.

METHODS

Thirty-three PI patients and 38 well-matched healthy controls participated in our study. We used voxel-based morphometry and RSFC to study functional connectivity abnormalities of brain regions with structural deficits in PI patients.

RESULTS

PI patients showed decreased gray matter (GM) volume in the left dorsolateral prefrontal cortex, left orbitofrontal cortex (OFC), bilateral middle frontal gyrus (MFC), right inferior frontal gyrus (IFG), and left inferior temporal gyrus. Gray matter volume in the right MFC negatively correlated with Self-Rating Scale of Sleep (SRSS) scores, and GM volume in the right IFG negatively correlated with SRSS and Insomnia Severity Index (ISI) scores. Therefore, the right MFC and right IFG were selected as regions of interest for RSFC analysis. PI patients had weakened RSFC between the right inferior parietal gyrus (IPC) and the right MFC compared to the healthy controls and between the left OFC and right IFG. The RSFC between the right MFC and right IPC negatively correlated with SRSS scores. The RSFC between the right IFG and left OFC negatively correlated with SRSS, ISI, SAS, and SDS scores.

CONCLUSIONS

The present study found structural changes in the right MFC and right IFG accompanied by RSFC changes. This finding may provide novel insights into the neural mechanisms of PI via combining structural and functional modality information.

Two nights of recovery sleep restores hippocampal connectivity but not episodic memory after total sleep deprivation

Sleep deprivation significantly impairs a range of cognitive and brain function, particularly episodic memory and the underlying hippocampal function. However, it remains controversial whether one or two nights of recovery sleep following sleep deprivation fully restores brain and cognitive function. In this study, we used functional magnetic resonance imaging (fMRI) and examined the effects of two consecutive nights (20-hour time-in-bed) of recovery sleep on resting-state hippocampal connectivity and episodic memory deficits following one night of total sleep deprivation (TSD) in 39 healthy adults in a controlled in-laboratory protocol. TSD significantly reduced memory performance in a scene recognition task, impaired hippocampal connectivity to multiple prefrontal and default mode network regions, and disrupted the relationships between memory performance and hippocampal connectivity. Following TSD, two nights of recovery sleep restored hippocampal connectivity to baseline levels, but did not fully restore memory performance nor its associations with hippocampal connectivity. These findings suggest that more than two nights of recovery sleep are needed to fully restore memory function and hippocampal-memory associations after one night of total sleep loss.

Sleep/Wake Regularity Associated with Default Mode Network Structure among Healthy Adolescents and Young Adults

Sleep deprivation and disorders are linked to reduced DMN connectivity. Less is known about how naturalistic sleep patterns - specifically sleep irregularity - relate to the DMN, particularly among adolescents and young adults. Additionally, no studies have utilized graph theory analysis to clarify whether sleep-related decreases in connectivity reflect global or local DMN changes. Twenty-five healthy adolescents and young adults (age range = 12-22; mean = 18.08; SD = 2.64, 56% female) completed 7 days of actigraphy and resting-state fMRI. Sleep regularity was captured by the Sleep Regularity Index (SRI) and the relationship between the SRI and DMN was examined using graph theory analysis. Analogous analyses explored relationships between the SRI and additional resting-state networks. Greater sleep regularity related to decreased path length (increased network connectivity) in DMN regions, particularly the right and left lateral parietal lobule, and the Language Network, including the left inferior frontal gyrus and the left posterior superior frontal gyrus. Findings were robust to covariates including sex and age. Sleep and DMN function may be tightly linked during adolescence and young adulthood, and reduced DMN connectivity may reflect local changes within the network. Future studies should assess how this relationship impacts cognitive development and neuropsychiatric outcomes in this age group.

Impaired Coupling of the Brain's Default Network During Sleep Deprivation: A Resting-State EEG Study

INTRODUCTION

Sleep deprivation (SD) has a negative influence on mood and emotion processing, and previous studies have elucidated the impaired coupling within the default network (DN) after SD. However, the dynamic characteristic with high temporal precision was rarely investigated in the DN after SD.

METHODS

Here, the resting-state EEG after nocturnal sleep (NS) and SD was collected from 31 participants. The cortical electrical activities of the posterior cingulate cortex (PCC) and the anterior medial prefrontal cortex (aMPFC) were reconstructed applying the eLORETA, and the functional connectivity (FC) of PCC-aMPFC was calculated using the power envelope connectivity (PEC).

RESULTS

Compared with NS, the power spectrums of the PCC and the FC of PCC-aMPFC were significantly reduced in the α band after SD. Interestingly, the impaired PCC-aMPFC integration was positively correlated with the decreased positive affect, implying that the DN plays a critical role in the subjective mood state. Our moderation analysis further revealed that the intensity of the DN posterior-anterior interaction moderated sleep loss and positive affect.

DISCUSSION

Overall, the results reveal the strong relationship between the uncoupling of DN and the feeling down of mood. Our research may contribute towards a better understanding of the mood and cognition processing after sleep loss.

Integrating sleep, neuroimaging, and computational approaches for precision psychiatry

In advancing precision psychiatry, we focus on what imaging technology and computational approaches offer for the future of diagnostic subtyping and personalized tailoring of interventions for sleep impairment in mood and anxiety disorders. Current diagnostic criteria for mood and anxiety tend to lump different forms of sleep disturbance together. Parsing the biological features of sleep impairment and brain circuit dysfunction is one approach to identifying subtypes within these disorders that are mechanistically coherent and offer targets for intervention. We focus on two large-scale neural circuits implicated in sleep impairment and in mood and anxiety disorders: the default mode network and negative affective network. Through a synthesis of existing knowledge about these networks, we pose a testable framework for understanding how hyper- versus hypo-engagement of these networks may underlie distinct features of mood and sleep impairment. Within this framework we consider whether poor sleep quality may have an explanatory role in previously observed associations between network dysfunction and mood symptoms. We expand this framework to future directions including the potential for connecting circuit-defined subtypes to more distal features derived from digital phenotyping and wearable technologies, and how new discovery may be advanced through machine learning approaches.

Impact of acute sleep deprivation on dynamic functional connectivity states

Sleep deprivation (SD) could amplify the temporal fluctuation of spontaneous brain activities that reflect different arousal levels using a dynamic functional connectivity (dFC) approach. Therefore, we intended to evaluate the test–retest reliability of dFC characteristics during rested wakefulness (RW), and to explore how the properties of these dynamic connectivity states were affected by extended durations of acute sleep loss (28/52 hr). We acquired resting‐state fMRI and neuropsychological datasets in two independent studies: (a) twice during RW and once after 28 hr of SD (n = 15) and (b) after 52 hr of SD and after 14 hr of recovery sleep (RS; n = 14). Sliding‐window correlations approach was applied to estimate their covariance matrices and corresponding three connectivity states were generated. The test–retest reliability of dFC properties demonstrated mean dwell time and fraction of connectivity states were reliable. After SD, the mean dwell time of a specific state, featured by strong subcortical–cortical anticorrelations, was significantly increased. Conversely, another globally hypoconnected state was significantly decreased. Subjective sleepiness and objective performances were separately positive and negative correlated with the increased and decreased state. Two brain connectivity states and their alterations might be sufficiently sensitive to reflect changes in the dynamics of brain mental activities after sleep loss.

Beyond sleepy: structural and functional changes of the default-mode network in idiopathic hypersomnia

Idiopathic hypersomnia (IH) is characterized by excessive daytime sleepiness but, in contrast to narcolepsy, does not involve cataplexy, sleep-onset REM periods, or any consistent hypocretin-1 deficiency. The pathophysiological mechanisms of IH remain unclear. Because of the involvement of the default-mode network (DMN) in alertness and sleep, our aim was to investigate the structural and functional modifications of the DMN in IH. We conducted multimodal magnetic resonance imaging (MRI) in 12 participants with IH and 15 good sleeper controls (mean age ± SD: 32 ± 9.6 years, range 22-53 years, nine males). Self-reported as well as objective measures of daytime sleepiness were collected. Gray matter volume and cortical thickness were analyzed to investigate brain structural differences between good sleepers and IH. Structural covariance and resting-state functional connectivity were analyzed to investigate changes in the DMN. Participants with IH had greater volume and cortical thickness in the precuneus, a posterior hub of the DMN. Cortical thickness in the left medial prefrontal cortex was positively correlated with thickness of the precuneus, and the strength of this correlation was greater in IH. In contrast, functional connectivity at rest was lower within the anterior DMN (medial prefrontal cortex) in IH, and correlated with self-reported daytime sleepiness. The present results show that IH is associated with structural and functional differences in the DMN, in proportion to the severity of daytime sleepiness, suggesting that a disruption of the DMN contributes to the clinical features of IH. Larger volume and thickness in this network might reflect compensatory changes to lower functional connectivity in IH.

Effects of Chronic Sleep Restriction on the Brain Functional Network, as Revealed by Graph Theory

Sleep is a complex and dynamic process for maintaining homeostasis, and a lack of sleep can disrupt whole-body functioning. No organ is as vulnerable to the loss of sleep as the brain. Accordingly, we examined a set of task-based functional magnetic resonance imaging (fMRI) data by using graph theory to assess brain topological changes in subjects in a state of chronic sleep restriction, and then identified diurnal variability in the graph-theoretic measures. Task-based fMRI data were collected in a 1.5T MR scanner from the same participants on two days: after a week of fully restorative sleep and after a week with 35% sleep curtailment. Each day included four scanning sessions throughout the day (at approximately 10:00 AM, 2:00 PM, 6:00 PM, and 10:00 PM). A modified spatial cueing task was applied to evaluate sustained attention. After sleep restriction, the characteristic path length significantly increased at all measurement times, and small-worldness significantly decreased. Assortativity, a measure of network fault tolerance, diminished over the course of the day in both conditions. Local graph measures were altered primarily across the limbic system (particularly in the hippocampus, parahippocampal gyrus, and amygdala), default mode network, and visual network.

Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing

Converging evidence from structural, metabolic and functional connectivity MRI suggests that neurodegenerative diseases, such as Alzheimer's disease, target specific neural networks. However, age-related network changes commonly co-occur with neuropathological cascades, limiting efforts to disentangle disease-specific alterations in network function from those associated with normal ageing. Here we elucidate the differential effects of ageing and Alzheimer's disease pathology through simultaneous analyses of two functional connectivity MRI datasets: (i) young participants harbouring highly-penetrant mutations leading to autosomal-dominant Alzheimer's disease from the Dominantly Inherited Alzheimer's Network (DIAN), an Alzheimer's disease cohort in which age-related comorbidities are minimal and likelihood of progression along an Alzheimer's disease trajectory is extremely high; and (ii) young and elderly participants from the Harvard Aging Brain Study, a cohort in which imaging biomarkers of amyloid burden and neurodegeneration can be used to disambiguate ageing alone from preclinical Alzheimer's disease. Consonant with prior reports, we observed the preferential degradation of cognitive (especially the default and dorsal attention networks) over motor and sensory networks in early autosomal-dominant Alzheimer's disease, and found that this distinctive degradation pattern was magnified in more advanced stages of disease. Importantly, a nascent form of the pattern observed across the autosomal-dominant Alzheimer's disease spectrum was also detectable in clinically normal elderly with clear biomarker evidence of Alzheimer's disease pathology (preclinical Alzheimer's disease). At the more granular level of individual connections between node pairs, we observed that connections within cognitive networks were preferentially targeted in Alzheimer's disease (with between network connections relatively spared), and that connections between positively coupled nodes (correlations) were preferentially degraded as compared to connections between negatively coupled nodes (anti-correlations). In contrast, ageing in the absence of Alzheimer's disease biomarkers was characterized by a far less network-specific degradation across cognitive and sensory networks, of between- and within-network connections, and of connections between positively and negatively coupled nodes. We go on to demonstrate that formalizing the differential patterns of network degradation in ageing and Alzheimer's disease may have the practical benefit of yielding connectivity measurements that highlight early Alzheimer's disease-related connectivity changes over those due to age-related processes. Together, the contrasting patterns of connectivity in Alzheimer's disease and ageing add to prior work arguing against Alzheimer's disease as a form of accelerated ageing, and suggest multi-network composite functional connectivity MRI metrics may be useful in the detection of early Alzheimer's disease-specific alterations co-occurring with age-related connectivity changes. More broadly, our findings are consistent with a specific pattern of network degradation associated with the spreading of Alzheimer's disease pathology within targeted neural networks.

The neurophysiological basis of excessive daytime sleepiness: suggestions of an altered state of consciousness

Excessive daytime sleepiness (EDS) is characterized by difficulty staying awake during daytime, though additional features may be present. EDS is a significant problem for clinical and non-clinical populations, being associated with a range of negative outcomes that also represent a burden for society. Extreme EDS is associated with sleep disorders, most notably the central hypersomnias such as narcolepsy, Kleine-Levin syndrome, and idiopathic hypersomnia (IH). Although investigation of these conditions indicates that EDS results from diminished sleep quality, the underlying cause for this impairment remains uncertain. One possibility could be that previous research has been too narrow in scope with insufficient attention paid to non-sleep-related aspects. Here, we offer a broader perspective in which findings concerning the impact of EDS on cortical functioning are interpreted in relation to current understanding about the neural basis of consciousness. Alterations in the spatial distribution of cortical activity, in particular reduced connectivity of frontal cortex, suggest that EDS is associated with an altered state of consciousness.

Abnormal functional connectivity density in sleep-deprived subjects

Sleep deprivation (SD) can alter the intrinsic brain functional organization. However, its effects on intrinsic low-frequency connectivity in the whole brain have not been well characterized. In this study, we used voxel-based functional connectivity density (FCD) analysis to investigate the effects of SD on the spontaneous functional organization of the brain. Thirty-seven healthy participants underwent this within-subject crossover functional magnetic resonance imaging (fMRI) study during rested wakefulness (RW) and after 36 h of total sleep deprivation (TSD). Decreased long-/short-range FCDs were observed in the posterior cingulate cortex, precuneus, inferior parietal lobule, dorsolateral prefrontal cortex, dorsomedial prefrontal cortex, and ventromedial prefrontal cortex. Increased long-/short-range FCDs were found in the sensory integration and arousal regulating areas, including the postcentral gyrus, thalamus, superior temporal gyrus, and occipital-temporal cortex. Moreover, a significant negative correlation was found between the short-range FCD of the PCC and the reaction time of Psychomotor Vigilance Task. In the present study, spontaneous functional organization with significant group-wise differences between RW and TSD sessions was identified. Our findings extend our understanding of the neural mechanism of how brain activity is altered in sleep-deprived individuals.

Perspectives in affective disorders: Clocks and sleep

Mood disorders are often characterised by alterations in circadian rhythms, sleep disturbances and seasonal exacerbation. Conversely, chronobiological treatments utilise zeitgebers for circadian rhythms such as light to improve mood and stabilise sleep, and manipulations of sleep timing and duration as rapid antidepressant modalities. Although sleep deprivation ("wake therapy") can act within hours, and its mood-elevating effects be maintained by regular morning light administration/medication/earlier sleep, it has not entered the regular guidelines for treating affective disorders as a first-line treatment. The hindrances to using chronotherapeutics may lie in their lack of patentability, few sponsors to carry out large multi-centre trials, non-reimbursement by medical insurance and their perceived difficulty or exotic "alternative" nature. Future use can be promoted by new technology (single-sample phase measurements, phone apps, movement and sleep trackers) that provides ambulatory documentation over long periods and feedback to therapist and patient. Light combinations with cognitive behavioural therapy and sleep hygiene practice may speed up and also maintain response. The urgent need for new antidepressants should hopefully lead to reconsideration and implementation of these non-pharmacological methods, as well as further clinical trials. We review the putative neurochemical mechanisms underlying the antidepressant effect of sleep deprivation and light therapy, and current knowledge linking clocks and sleep with affective disorders: neurotransmitter switching, stress and cortico-limbic reactivity, clock genes, cortical neuroplasticity, connectomics and neuroinflammation. Despite the complexity of multi-system mechanisms, more insight will lead to fine tuning and better application of circadian and sleep-related treatments of depression.

Objective and subjective measures of prior sleep-wake behavior predict functional connectivity in the default mode network during NREM sleep

INTRODUCTION

Prior sleep behavior has been shown to correlate with waking resting-state functional connectivity (FC) in the default mode network (DMN). However, the impact of sleep history on FC during sleep has not been investigated. The aim of this study was to establish whether there is an association between intersubject variability in habitual sleep behaviors and the strength of FC within the regions of the DMN during non-rapid eye movement (NREM) sleep.

METHODS

Wrist actigraphy and sleep questionnaires were used as objective and subjective measures of habitual sleep behavior, and EEG-functional MRI during NREM sleep was used to quantify sleep.

RESULTS

There was a significant, regionally specific association between the interindividual variability in objective (total sleep time on the night before scanning) and subjective (Insomnia Severity Index) measures of prior sleep-wake behavior and the strength of DMN FC during subsequent wakefulness and NREM sleep. In several cases, FC was related to sleep measures independently of sleep stage, suggesting that previous sleep history effects sleep FC globally across the stages.

CONCLUSIONS

This work highlights the need to consider a subject's prior sleep history in studies utilizing FC analysis during wakefulness and sleep, and indicates the complexity of the impact of sleep on the brain both in the short and long term.

Intracortical Causal Information Flow of Oscillatory Activity (Effective Connectivity) at the Sleep Onset Transition

We investigated the sleep onset transition in humans from an effective connectivity perspective in a baseline condition (approx. 16 h of wakefulness) and after sleep deprivation (40 h of sustained wakefulness). Using EEG recordings (27 derivations), source localization (LORETA) allowed us to reconstruct the underlying patterns of neuronal activity in various brain regions, e.g., the default mode network (DMN), dorsolateral prefrontal cortex and hippocampus, which were defined as regions of interest (ROI). We applied isolated effective coherence (iCOH) to assess effective connectivity patterns at the sleep onset transition [2 min prior to and 10 min after sleep onset (first occurrence of stage 2)]. ICOH reveals directionality aspects and resolves the spectral characteristics of information flow in a given network of ROIs. We observed an anterior-posterior decoupling of the DMN, and moreover, a prominent role of the posterior cingulate cortex guiding the process of the sleep onset transition, particularly, by transmitting information in the low frequency range (delta and theta bands) to other nodes of DMN (including the hippocampus). In addition, the midcingulate cortex appeared as a major cortical relay station for spindle synchronization (originating from the thalamus; sigma activity). The inclusion of hippocampus indicated that this region might be functionally involved in sigma synchronization observed in the cortex after sleep onset. Furthermore, under conditions of increased homeostatic pressure, we hypothesize that an anterior-posterior decoupling of the DMN occurred at a faster rate compared to baseline overall indicating weakened connectivity strength within the DMN. Finally, we also demonstrated that cortico-cortical spindle synchronization was less effective after sleep deprivation than in baseline, thus, reflecting the reduction of spindles under increased sleep pressure.

Poor Sleep Quality Associates With Decreased Functional and Structural Brain Connectivity in Normative Aging: A MRI Multimodal Approach

Sleep is a ubiquitous phenomenon, essential to the organism homeostasis. Notwithstanding, there has been an increasing concern with its disruption, not only within the context of pathological conditions, such as neurologic and psychiatric diseases, but also in health. In fact, sleep complaints are becoming particularly common, especially in middle-aged and older adults, which may suggest an underlying susceptibility to sleep quality loss and/or its consequences. Thus, a whole-brain modeling approach to study the shifts in the system can cast broader light on sleep quality mechanisms and its associated morbidities. Following this line, we sought to determine the association between the standard self-reported measure of sleep quality, the Pittsburgh Sleep Quality Index (PSQI) and brain correlates in a normative aging cohort. To this purpose, 86 participants (age range 52–87 years) provided information regarding sociodemographic parameters, subjective sleep quality and associated psychological variables. A multimodal magnetic resonance imaging (MRI) approach was used, with whole-brain functional and structural connectomes being derived from resting-state functional connectivity (FC) and probabilistic white matter tractography (structural connectivity, SC). Brain regional volumes and white matter properties associations were also explored. Results show that poor sleep quality was associated with a decrease in FC and SC of distinct networks, overlapping in right superior temporal pole, left middle temporal and left inferior occipital regions. Age displayed important associations with volumetric changes in the cerebellum cortex and white matter, thalamus, hippocampus, right putamen, left supramarginal and left lingual regions. Overall, results suggest that not only the PSQI global score may act as a proxy of changes in FC/SC in middle-aged and older individuals, but also that the age-related regional volumetric changes may be associated to an adjustment of brain connectivity. These findings may also represent a step further in the comprehension of the role of sleep disturbance in disease, since the networks found share regions that have been shown to be affected in pathologies, such as depression and Alzheimer's disease.

Sleep-related brain atrophy and disrupted functional connectivity in older adults

Aging associates with sleep dysfunction as well as brain alterations. However, the association between age-related brain alterations and their subjective sleep changes is less understood. To address this issue, we recorded T1 weighted structural and resting-state functional magnetic resonance imaging from both young (n = 62) and older adults (n = 108). In addition, all participants completed a battery of psychometric tests, including the Pittsburg Sleep Quality Index. We found that the age-related atrophy of cerebral gray matter, hippocampal and thalamic volume were associated with subjective sleep decline, and the atrophy of cerebral gray matter mediated the age effect on sleep. In addition, older adults exhibited decreased functional connectivity within the medial temporal lobe subsystem than their young counterparts. Moreover, there is a significant positive association between sleep and functional connectivity in young but not in older adults. In light of our findings, we suggest a neuropathological model in which age-related brain alterations may partially explain the well-documented declines in sleep with aging.

Current sleep disturbance in older people with a lifetime history of depression is associated with increased connectivity in the Default Mode Network

BACKGROUND

The present study investigated Default Mode Network (DMN) functional connectivity in subjects with a lifetime history of major depression, comparing those with and without current sleep disturbance. Controls were included to assess DMN abnormalities specific to depression.

METHODS

A total of 93 adults aged 50 years and over were recruited from the Healthy Brain Ageing Clinic at the Brain and Mind Centre, Sydney, Australia. The sample comprised two groups, including 22 controls and 71 participants with a lifetime history of DSM-IV major depression (with depressive episode current or remitted). 52 of those with a lifetime history of depression also met criteria for Mild Cognitive Impairment (MCI). Participants underwent resting-state fMRI along with comprehensive psychiatric, neuropsychological, and medical assessment. Subjective sleep quality was assessed via the Pittsburgh Sleep Quality Index (PSQI). Sleep disturbance was defined as a PSQI score > 5. A total of 68% (n = 48) of cases with a lifetime history of depression met criteria for sleep-disturbance. DMN functional connectivity was assessed via ROI-to-ROI analyses.

RESULTS

Relative to controls, those with lifetime major depression demonstrated significantly increased functional connectivity between the ventromedial prefrontal cortex and the temporal pole. Within the depression group (n = 48), those with current sleep disturbance had significantly increased connectivity between the anterior medial prefrontal cortex and both the parahippocampal cortex and the hippocampal formation, relative to those without sleep disturbance (n = 23). These results were present after controlling for MCI diagnosis.

CONCLUSIONS

Current sleep disturbance together with depression is associated with distinct abnormalities in DMN functioning incorporating regions responsible for self-reflection and declarative memory processes. Impaired sleep is associated with increased connectivity between these regions. Future studies may augment these findings with complementary imaging techniques including cortical thickness and diffusion tensor imaging, as well as high density electroencephalogram recording.