Unihemispheric Sleep: An Enigma for Current Models of Sleep-Wake Regulation

Digital screen time usage, prevalence of excessive digital screen time, and its association with mental health, sleep quality, and academic performance among Southern University students

Background

Excessive digital screen time (EDST), which is defined as screen use that surpasses recommended limits, has been found to have detrimental effects on students' mental health and academic performance. However, there is a paucity of studies investigating EDST in university students in Thailand.

Objective

To investigate the prevalence, characteristics, and associations of excessive digital screen time with students' mental health, sleep quality, and academic performance.

Methods

A cross-sectional study was conducted at Southern University, Thailand, between December 2023 and January 2024. A total of 446 students completed self-administered questionnaires assessing DST characteristics, mental health, sleep quality, and academic performance. The tools used included the Depression Anxiety Stress Scale, Rosenberg Self-Esteem Scale, UCLA Loneliness Scale, and Pittsburgh Sleep Quality Index. DST was analyzed by device type and average weekly usage hours, focusing on smartphones, tablets, and computers. EDST was defined as daily usage exceeding 8 hours for smartphones, 6 hours for tablets, or 5 hours for computers. Participants exceeding these thresholds on any device were classified as having EDST. Sampling was conducted using quota sampling across faculties. Data were analyzed using chi-square tests, rank sum tests, and logistic regression, with significance set at P<0.05.

Results

Students' median age was 20 years (67.9% women). Most participants used smartphones for 4-6 hours daily (29.7%), tablets for <4 hours (29.8%), and computers for <4 hours (62.6%). Smartphones were primarily used for social media (73.1%), while tablets (28.4%) and computers (19.3%) were used for educational purposes. The prevalence of EDST was 48.4%, including 29.4% on tablets, 22.9% on smartphones, and 7.6% on computers. EDST was significantly associated with younger age (AOR 0.79; 95% CI 0.66-0.94) and enrollment in health science faculties (AOR 1.7; 95% CI 1.01-2.86).

Conclusion

A high prevalence of EDST was observed among university students, particularly on smartphones and tablets. Younger students and those in health science programs were more prone to EDST, potentially due to higher academic demands and social media use. Interventions to enhance self-awareness, regulate screen time, and develop time management skills are recommended to mitigate its negative effects on mental health and academic performance.

FlyVISTA, an integrated machine learning platform for deep phenotyping of sleep in Drosophila

There is great interest in using genetically tractable organisms such as Drosophila to gain insights into the regulation and function of sleep. However, sleep phenotyping in Drosophila has largely relied on simple measures of locomotor inactivity. Here, we present FlyVISTA, a machine learning platform to perform deep phenotyping of sleep in flies. This platform comprises a high-resolution closed-loop video imaging system, coupled with a deep learning network to annotate 35 body parts, and a computational pipeline to extract behaviors from high-dimensional data. FlyVISTA reveals the distinct spatiotemporal dynamics of sleep and wake-associated microbehaviors at baseline, following administration of the sleep-inducing drug gaboxadol, and with dorsal fan-shaped body drivers. We identify a microbehavior ("haltere switch") exclusively seen during quiescence that indicates a deeper sleep stage. These results enable the rigorous analysis of sleep in Drosophila and set the stage for computational analyses of microbehaviors in quiescent animals.

Sensory gating and gaining in sleep: the balance between the protection of sleep and the safeness of life (a review)

Sleep is a brain state characterised by a low vigilance level and diminished consciousness. Reaction to and processing of external stimuli is attenuated in sleep. During sleep, the reticular thalamic nucleus reduces the flow of sensory activity to the cerebral cortex through inhibition of the thalamus. This sensory gating process facilitates sleep. After reaching the afferent layers of primary cortex, the reduced sensory flow is adjusted, gained, and processed within various cortical layers before being transferred by the corticofugal system back to appropriate subdivisions of the thalamus as feedback. Thalamic subdivisions then dispatch this sensory information to related areas of the cerebral cortex, where it is (sub)consciously perceived. When necessary, a sleeping individual can be awakened by a wake-up call, either by stimuli indicating danger, or by personally meaningful stimuli. It is safe for a sleeping individual that it can be aroused when necessary. Evidently, there are two processes by which the brain adjusts the response to sensory stimuli before entering (sub)consciousness. Firstly 'sensory gating', a process favourable to the maintenance of sleep by reducing the sensory input to the brain through the reticular thalamic nucleus and secondly 'sensory gaining', a process implying that the gained preserved sensory input is continuously analysed by the corticofugal system to detect dangerous and relevant environmental elements, indispensable for safeness and well-being of the sleeper.

The interplay between sleep and ecophysiology, behaviour and responses to environmental change in fish

Evidence of behavioural sleep has been observed in every animal species studied to date, but current knowledge of the behaviour, neurophysiology and ecophysiology associated with sleep is concentrated on mammals and birds. Fish are a hugely diverse group that can offer novel insights into a variety of sleep-related behaviours across environments, but the ecophysiological relevance of sleep in fish has been largely overlooked. Here, we systematically reviewed the literature to assess the current breadth of knowledge on fish sleep, and surveyed the diverse physiological effects and behaviours associated with sleep. We also discuss possible ways in which unstudied external factors may alter sleep behaviours. For example, predation risk may alter sleep patterns, as has been shown in mammalian, avian and reptilian species. Other environmental factors - such as water temperature and oxygen availability - have the potential to alter sleep patterns in fish differently than for terrestrial endotherms. Understanding the ecological influences on sleep in fish is vital, as sleep deprivation has the potential to affect waking behaviour and fitness owing to cognitive and physiological impairments, possibly affecting ecological phenomena and sensitivity to environmental stressors in ways that have not been considered.

Adaptive changes in BMAL2 with increased locomotion associated with the evolution of unihemispheric slow-wave sleep in mammals

Marine mammals, especially cetaceans, have evolved a very special form of sleep characterized by unihemispheric slow-wave sleep (USWS) and a negligible amount or complete absence of rapid-eye-movement sleep; however, the underlying genetic mechanisms remain unclear. Here, we detected unique, significant selection signatures in basic helix-loop-helix ARNT like 2 (BMAL2; also called ARNTL2), a key circadian regulator, in marine mammal lineages, and identified two nonsynonymous amino acid substitutions (K204E and K346Q) in the important PER-ARNT-SIM domain of cetacean BMAL2 via sequence comparison with other mammals. In vitro assays revealed that these cetacean-specific mutations specifically enhanced the response to E-box-like enhancer and consequently promoted the transcriptional activation of PER2, which is closely linked to sleep regulation. The increased PER2 expression, which was further confirmed both in vitro and in vivo, is beneficial for allowing cetaceans to maintain continuous movement and alertness during sleep. Concordantly, the locomotor activities of zebrafish overexpressing the cetacean-specific mutant bmal2 were significantly higher than the zebrafish overexpressing the wild-type gene. Subsequently, transcriptome analyses revealed that cetacean-specific mutations caused the upregulation of arousal-related genes and the downregulation of several sleep-promoting genes, which is consistent with the need to maintain hemispheric arousal during USWS. Our findings suggest a potential close relationship between adaptive changes in BMAL2 and the remarkable adaptation of USWS and may provide novel insights into the genetic basis of the evolution of animal sleep.

Acetylcholine and metacognition during sleep

Acetylcholine is a neurotransmitter and neuromodulator involved in a variety of cognitive functions. Additionally, acetylcholine is involved in the regulation of REM sleep: cholinergic neurons in the brainstem and basal forebrain project to and innervate wide areas of the cerebral cortex, and reciprocally interact with other neuromodulatory systems, to produce the sleep-wake cycle and different sleep stages. Consciousness and cognition vary considerably across and within sleep stages, with metacognitive capacity being strikingly reduced even during aesthetically and emotionally rich dream experiences. A notable exception is the phenomenon of lucid dreaming-a rare state whereby waking levels of metacognitive awareness are restored during sleep-resulting in individuals becoming aware of the fact that they are dreaming. The role of neurotransmitters in these fluctuations of consciousness and cognition during sleep is still poorly understood. While recent studies using acetylcholinesterase inhibitors suggest a potential role of acetylcholine in the occurrence of lucid dreaming, the underlying mechanisms by which this effect is produced remains un-modelled and unknown; with the causal link between cholinergic mechanisms and upstream psychological states being complex and elusive. Several theories and approaches targeting the association between acetylcholine and metacognition during wakefulness and sleep are highlighted in this review, moving through microscopic, mesoscopic and macroscopic levels of analysis to detail this phenomenon at several organisational scales. Several exploratory hypotheses will be developed to guide future research towards fully articulating how metacognition is affected by activity at the acetylcholine receptor.

Taking Sides: Asymmetries in the Evolution of Human Brain Development in Better Understanding Autism Spectrum Disorder

Confirmation from structural, functional, and behavioral studies agree and suggest a configuration of atypical lateralization in individuals with autistic spectrum disorders (ASD). It is suggested that patterns of cortical and behavioral atypicality are evident in individuals with ASDs with atypical lateralization being common in individuals with ASDs. The paper endeavors to better understand the relationship between alterations in typical cortical asymmetries and functional lateralization in ASD in evolutionary terms. We have proposed that both early genetic and/or environmental influences can alter the developmental process of cortical lateralization. There invariably is a “chicken or egg” issue that arises whether atypical cortical anatomy associated with abnormal function, or alternatively whether functional atypicality generates abnormal structure.

Cross-Scale Dynamicity of Entropy and Connectivity in the Sleeping Brain

Introduction: The concept of local sleep refers to the phenomenon of local brain activity that modifies neural networks during unresponsive global sleep. Such network rewiring may differ across spatial scales; however, the global and local alterations in brain systems remain elusive in human sleep. Materials and Methods: We examined cross-scale changes of brain networks in sleep. Functional magnetic resonance imaging data were acquired from 28 healthy participants during nocturnal sleep. We adopted both metrics of connectivity (functional connectivity [FC] and regional homogeneity [ReHo]) and complexity (multiscale entropy) to explore the global and local functionality of the neural assembly across nonrapid eye movement sleep stages. Results: Long-range FC decreased with sleep depth, whereas local ReHo peaked at the N2 stage and reached its lowest level at the N3 stage. Entropy exhibited a general decline at the local scale (Scale 1) as sleep deepened, whereas the coarse-scale entropy (Scale 3) was consistent across stages. Discussion: The negative correlation between Scale-1 entropy and ReHo reflects the enhanced signal regularity and synchronization in sleep, identifying the information exchange at the local scale. The N2 stage showed a distinctive pattern toward local information processing with scrambled long-distance information exchange, indicating a specific time window for network reorganization. Collectively, the multidimensional metrics indicated an imbalanced global-local relationship among brain functional networks across sleep-wake stages.

Insomnia subtypes characterised by objective sleep duration and NREM spectral power and the effect of acute sleep restriction: an exploratory analysis

Insomnia disorder (ID) is a heterogeneous disorder with proposed subtypes based on objective sleep duration. We speculated that insomnia subtyping with additional power spectral analysis and measurement of response to acute sleep restriction may be informative in overall assessment of ID. To explore alternative classifications of ID subtypes, insomnia patients (n = 99) underwent two consecutive overnight sleep studies: (i) habitual sleep opportunity (polysomnography, PSG) and, (ii) two hours less sleep opportunity (electroencephalography, EEG), with the first night compared to healthy controls (n = 25). ID subtypes were derived from data-driven classification of PSG, EEG spectral power and interhemispheric EEG asymmetry index. Three insomnia subtypes with different sleep duration and NREM spectral power were identified. One subtype (n = 26) had shorter sleep duration and lower NREM delta power than healthy controls (short-sleep delta-deficient; SSDD), the second subtype (n = 51) had normal sleep duration but lower NREM delta power than healthy controls (normal-sleep delta-deficient; NSDD) and a third subtype showed (n = 22) no difference in sleep duration or delta power from healthy controls (normal neurophysiological sleep; NNS). Acute sleep restriction improved multiple objective sleep measures across all insomnia subtypes including increased delta power in SSDD and NSDD, and improvements in subjective sleep quality for SSDD (p = 0.03), with a trend observed for NSDD (p = 0.057). These exploratory results suggest evidence of novel neurophysiological insomnia subtypes that may inform sleep state misperception in ID and with further research, may provide pathways for personalised care.

Sleep- and time of day-linked RNA transcript expression in wild-type and IL1 receptor accessory protein-null mice

Sleep regulation involves interleukin-1β (IL1) family members, TNF, and circadian clock genes. Previously, we characterized spontaneous sleep and sleep after 8 h of sleep deprivation (SD) ending at zeitgeber time (ZT)4 and ZT16 in wild-type (WT) and IL1 receptor accessory protein (AcP)- and brain-specific AcP (AcPb)-knockout (KO) mice. Here, we applied quantitative reverse transcriptase polymerase chain reaction and Spearman gene pair expression correlation methods to characterize IL1, IL1 receptor 1 (IL1R1), AcP, AcPb, Period 1 (Per1), Clock, adenosine deaminase (Ada), peptidoglycan recognition protein 1 (Pglyrp1), and TNF mRNA expressions under conditions with distinct sleep phenotypes. In WT mice, IL1, IL1R1, AcP, Ada, and Clock mRNAs were higher at ZT4 (mid-sleep period) than at ZT16. mRNA expressions differed substantially in AcP and AcPb KO mice at those times. After SD ending at ZT4, only WT mice had a non-rapid eye movement sleep (NREMS) rebound, and AcPb and IL1R1 mRNA increases were unique to WT mice. In AcPb KO mice, which have spontaneous high EEG slow wave power, AcP and Pglyrp1 mRNAs were elevated relative to WT mice at ZT4. At ZT4, the AcPb KO - WT Spearman correlation difference networks showed high positive correlations between IL1R1 and IL1, Per1, and Clock and high negative correlations between TNF and Pglyrp1 and Ada. At ZT16, the WT mice gene pair expression network was mostly negative, whereas in AcP KO mice, which have substantially more rapid eye movement sleep than WT mice, it was all positive. We conclude that gene pair expression correlations depend on the presence of AcP and AcPb.NEW & NOTEWORTHY Spearman gene pair expression correlations depend upon the presence or absence of interleukin-1 receptor accessory protein and upon sleep phenotype.

Local sleep

The historic sleep regulatory paradigm invokes "top-down" imposition of sleep on the brain by sleep regulatory circuits. While remaining conceptually useful, many sleep phenomena are difficult to explain using that paradigm, including, unilateral sleep, sleep-walking, and poor performance after sleep deprivation. Further, all animals sleep after non-lethal brain lesions, regardless of whether the lesion includes sleep regulatory circuits, suggesting that sleep is a fundamental property of small viable neuronal/glial networks. That small areas of the brain can exhibit non-rapid eye movement sleep-like states is summarized. Further, sleep-like states in neuronal/glial cultures are described. The local sleep states, whether in vivo or in vitro, share electrophysiological properties and molecular regulatory components with whole animal sleep and exhibit sleep homeostasis. The molecular regulatory components of sleep are also involved in plasticity and inflammation. Like sleep, these processes, are initiated by local cell-activity dependent events, yet have at higher levels of tissue organization whole body functions. While there are large literatures dealing with local initiation and regulation of plasticity and inflammation, the literature surrounding local sleep is in its infancy and clinical applications of the local sleep concept are absent. Regardless, the local use-dependent sleep paradigm can advise and advance future research and clinical applications.

New Neuroscience Tools That Are Identifying the Sleep-Wake Circuit

The complexity of the brain is yielding to technology. In the area of sleep neurobiology, conventional neuroscience tools such as lesions, cell recordings, c-Fos, and axon-tracing methodologies have been instrumental in identifying the complex and intermingled populations of sleep- and arousal-promoting neurons that orchestrate and generate wakefulness, NREM, and REM sleep. In the last decade, new technologies such as optogenetics, chemogenetics, and the CRISPR-Cas system have begun to transform how biologists understand the finer details associated with sleep-wake regulation. These additions to the neuroscience toolkit are helping to identify how discrete populations of brain cells function to trigger and shape the timing and transition into and out of different sleep-wake states, and how glia partner with neurons to regulate sleep. Here, we detail how some of the newest technologies are being applied to understand the neural circuits underlying sleep and wake.