Thermoregulatory processes are closely linked to sleep initiation and maintenance throughout the circadian cycle, and may contribute to the increased tendency to nap in older adults. This cross-sectional study examined whether habitual napping in healthy older individuals is associated with altered skin temperature-derived heat-loss dynamics and their relationship with sleep onset. Thirty self-reported habitual nappers and 28 non-nappers (59-82 y) completed a 40-hour multiple-nap protocol under controlled laboratory conditions, with continuous polysomnography and distal-proximal skin temperature gradients (DPG) recordings. DPG was analyzed across scheduled wake episodes and at lights-off preceding each nap opportunity. Habitual nappers exhibited distinct changes in thermoregulatory dynamics compared to non-nappers. Overall, they had a lower DPG during scheduled wakefulness, particularly during the afternoon nap window (14:45-17:30). Their circadian organization of the DPG also differed markedly: they had a higher 24-hour DPG amplitude, a more pronounced 12-hour component, and an earlier DPG phase than the non-nappers. During nap opportunities, shorter sleep onset latency (SOL) was associated with a faster increase in DPG after lights-off in both groups. However, in habitual nappers, sleep onset occurred more rapidly despite a reduced dependence on pre-sleep DPG increase. Together, these findings indicate that habitual napping in older adults is accompanied by altered heat-loss rhythms across the circadian cycle and a reduced coupling between pre-sleep thermoregulatory dynamics and sleep initiation. Circadian-driven thermoregulatory changes may underlie the greater propensity to nap in older adults and differentiate habitual nappers from non-nappers. However, the causal direction of this relationship requires further investigation.

Increased napping in later life is a common behaviour shaped by cultural, environmental and biological factors. Although brief naps can enhance alertness and memory, epidemiological evidence suggests that frequent or prolonged daytime sleep in older adults is associated with poorer physical health and accelerated cognitive decline, including episodic memory, possibly due to the underlying circadian disruption of the sleep–wake cycle. In this study, we tested whether restricting nap habits for 12 months would mitigate the age-related changes in cognitive functioning in healthy retirees (59–82 years). Fifty-eight habitual nappers were randomised either to a nap-control condition (n = 28), where they continued their usual nap routine, or to a nap-intervention condition (n = 30), where they received behavioural coaching to reduce the frequency and duration of daytime napping. A non-nappers group (n = 29) served as a reference. Cognitive performance, with a focus on episodic memory, was assessed at baseline and after the one-year intervention. Actimetric recordings showed that nap-intervention significantly decreased estimates of daytime nap frequency and duration throughout the study. Overall cognitive performance tended to decrease after a year in all participants, but the nap-control group exhibited a significantly greater decline in verbal episodic memory recall as compared to both non-nappers and nap-intervention participants. These results demonstrate that sleep–wake behaviour in older adults can be modified and suggest that targeted nap reduction may offer an accessible strategy to mitigate age-related decline in specific cognitive domains, regardless of whether habitual napping represents a causal or compensatory factor of neurobiological vulnerability.

Circadian rhythms and inter-individual differences in sleep-wake preferences, or chronotypes, influence cognitive performance. The synchrony effect-the alignment of time of day with chronotype-modulates attention, memory, and executive control. This study examined behavioural and neural correlates of synchrony effects during an auditory oddball task performed in morning (1.5 h after wake-up) and evening (10.5 h after wake-up) sessions by extreme morning-type (n = 16) and evening-type (n = 15) young (age range: 22-32 y.o.) individuals. Behaviourally, no main, nor interaction effects of chronotype or time of day were observed for overall reaction time metrics (all p > 0.05). However, overall reaction times during the task were longer in the final third of the task in the evening compared to the morning session for morning but not evening types (p < 0.05). Functional magnetic resonance imaging (fMRI) revealed neural correlates underlying the synchrony effect: the inferior frontal cortex (IFC) showed higher task-related activation at optimal times (morning for morning types, evening for evening types, pcorr < 0.05), putatively reflecting enhanced top-down control. Conversely, a medial orbitofrontal region (mOFC), part of the default mode network, was more active at non-optimal times (pcorr < 0.05), consistent with reduced task engagement and internally directed processes. These findings suggest that synchrony effects interact with time-on-task-dependent effects with implications for sustained attention in real-world settings.

Group-level studies have highlighted the roles of aging, poor sleep, and brain atrophy in cognitive performance (CP) but have overlooked inter-individual variability. We predict CP from feature sets (demographic, subjective/objective sleep parameters, and regional brain morphometry) using multisite ENIGMA-Sleep data (n = 2,372). Linear and non-linear machine learning models were trained on the largest cohort (n = 845), and the best-performing models were validated on independent cohorts. Subsequently, based on the best-performing model on the largest cohort, we characterized feature importance and interactions across all cohorts. We observed that a combination of demographic, sleep, and brain parameters moderately predicted CP, with age emerging as the key predictor. Model explanations further suggested that age was the primary driver of prediction models, while sleep played a smaller role that varied across subgroups. These findings endorsed inter-individual variability and complex interaction between aging, sleep, brain, and CP.

Background:Quantification of alterations in fractal motor activity regulation (FMAR) has the potential to improve early detection of Alzheimer's disease. To improve the clinical relevance of such marker, our analysis aims to investigate potential determinants such as age, sex, physical activity and race and ethnicity in a large community-dwelling multi-ethnic cohort of older Asian, Black, Hispanic and White individuals. Methods:We analysed week-long actigraphy recordings from 1508 older adults (55 to 90 years) of the MESA Sleep dataset. Long-range correlations in activity levels, a marker of fractal regulation, were assessed via a scaling exponent extracted with a Detrended Fluctuation Analysis over two different time ranges. Bayesian linear models were used to compare scaling exponent values between ethnic groups and test their associations with various determinants, such as age, sex and physical activity levels. Results:We found opposite effects of age on FMAR at both short and long time scales, respectively ( β Age = 0.014/ σ Age , 95% C.I. [0.009, 0.019] and β Age = -0.015/ σ Age , 95% C.I. [-0.026, -0.005]), as well as differences between women and men at long time scales ( β Sex Men = + 0.028 , 95% C.I. [0.012, 0.044]). We also confirmed that higher activity levels were linked to less degraded FMAR ( β MDA = 0.007/ σ MDA , 95% C.I. [0.003, 0.011] at short time scales and β MDA = 0.032/ σ MDA , 95% C.I. [0.024, 0.041] at long time scales). Finally, we observed that Black and Hispanic participants, as well as Asian participants, exhibiting lower values in scaling exponents at short and long time scales, respectively ( β Black = -0.026, 95% C.I. [-0.035, -0.017], β Hispanic = -0.018, 95% C.I. [-0.027, -0.009] and β Asian = -0.065, 95% C.I. [-0.091, -0.039]), compared to White participants. Conclusion:Using a large multi-ethnic cross-sectional dataset, our analysis provided support and clarified the interaction effect of age and sex on FMAR. It also confirmed, in humans, the influence of activity levels on FMAR observed in rodents and demonstrated for the first time that FMAR alterations are modulated by race and ethnicity.

Ageing well in place requires a living environment that meets the evolving needs of older adults. While the role of safety in healthy ageing is widely recognised, the contribution of a stimulating environment has received less attention. This study aims to develop an expert-weighted system quantifying how living environments provide physical and cognitive stimulation, as well as safety for older adults. Following an iterative process, multidisciplinary experts in ageing and housing weighted the importance of items for assessing an older adult’s level of physical and cognitive stimulation, and safety. They then judged sub-items for their influence (increase, decrease, or neutral) within each domain. Each sub-item was also assessed as beneficial, harmful, or person-dependent. Final weights were computed by multiplying importance and influence values. Agreement was assessed using the Median Absolute Deviation for importance (MAD < 2.5) and a ≥75% threshold for influence. For importance, 76% of stimulation-related items and 85% of safety items reached consensus, with remaining outliers explored through qualitative analyses. For influence, ≥75% agreement was achieved for 50% of physical-stimulation sub-items, 33% of cognitive-stimulation sub-items, and 59% of safety sub-items. Most sub-items were considered beneficial across domains. This weighting system allows an older adult’s living environment to be evaluated in terms of physical and cognitive stimulation, as well as safety. However, as some items and sub-items did not reach the predefined agreement thresholds, these weightings should be used with caution. These weightings enables benchmarking, environmental audits and targeted design interventions to support ageing well in place.

OBJECTIVE:To translate the Physical Activity Scale for the Elderly (PASE) questionnaire into French, adapt it to the French European culture and validate it. MATERIAL AND METHODS:The PASE was translated and culturally adapted using a 5-step validated process. The investigation of the measurement properties included the internal consistency, test-retest reliability, construct validity and floor and ceiling effects. RESULTS:The translation faced no major problems, with moderate cultural adjustments. Unfamiliar activities such as American football, shuffleboard or aerobic dancing were adjusted, while common sports like yoga, aqua cycling and electric cycling were added. Validation study involved 89 older participants (median age of 73 (69.5 - 77) years, 58% of women). Moderate internal consistency was found (Cronbach's alpha= 0.571). Test-retest reliability was very good for household activities (ICC= 0.712 (95% CI= 0.496 - 0.845)) and work-related activities (ICC= 0.955 (95% CI= 0.908 - 0.978)) but was lower in the leisure section (ICC= 0.163 (95% CI= - 0.183 - 0.473)), leading to a moderate overall score (ICC= 0.455 (95% CI= 0.125 - 0.608)). This result could be attributed to the weather conditions that were not similar between the two test-intervals, which affects leisure activities (most of which take place outdoors). Construct validity was almost confirmed (66.67% of the ideal 75% hypothesis was validated). No floor or ceiling effects were detected. CONCLUSION:The French PASE appears to be a reliable and relatively valid tool for assessing household and work-related activities. However, PASE should be used with caution, especially when assessing leisure time activities, ensuring that the meteorological conditions are consistent between the two reliability tests.

To review the role of physical activity as a mediator in the association between the living environment and sleep. Observational and experimental studies in English were included regardless of participants’ age, gender, or ethnicity. Searches were conducted in Medline (via PuMed), Scopus and Embase, supplemented by manual searches. Study selection was performed by two independent reviewers on the basis of titles, abstracts, and full-text articles. Data extraction and quality assessment (using JBI critical appraisal tools) were also carried out by two reviewers. The PRISMA 2020 guidelines were followed throughout. After removing duplicates, 1147 studies were screened, of which 5 studies (4 cross-sectional and 1 longitudinal) met the inclusion criteria. These studies were of moderate methodological quality. Improved access to recreational facilities was indirectly associated with longer sleep duration, lower risk of wake after sleep onset (WASO) and later wake time through increased physical activity. Strengthened neighborhood social cohesion, and reduced neighborhood violence and problems (i.e., noise, lack of access to shops and parks, litter, etc.) were indirectly associated with longer sleep duration, a lower risk of short sleep duration and better sleep quality through increased physical activity. Physical activity appears to be a potential promising mediator between the living environment and sleep, but evidence remains limited due to the small number of studies on this topic. Future studies using a rigorous mediation methodology and including household-level factors are needed. Prospero [ID: CRD42024580376].

Mind blanking (MB) is the inability to report mental events during unconstraint thinking. Previous work shows that MB is linked to decreased levels of cortical arousal, indicating dominance of cerebral mechanisms when reporting mental states. What remains inconclusive is whether MB can also ensue from autonomic arousal manipulations, pointing to the implication of peripheral physiology to mental events. Using experience sampling, neural, and physiological measurements in 26 participants, we first show that MB was reported more frequently in low arousal conditions, elicited by sleep deprivation. Also, there was partial evidence for a higher occurence of MB reports in high arousal conditions, elicited by intense physical exercise. Transition probabilities revealed that, after sleep deprivation, mind wandering was more likely to be followed by MB and less likely to be followed by more mind wandering reports. Using classification schemes, we found higher performance of a balanced random forest classifier trained on both neural and physiological markers in comparison to performance when solely neural or physiological were used. Collectively, we show that both cortical and autonomic arousal affect MB report occurrences. Our results establish that MB is supported by combined brain-body configurations, and, by linking mental and physiological states, they pave the way for novel embodied accounts of spontaneous thinking. ‘The stage 1 protocol for this Registered Report was accepted in principle on 02/01/23. The protocol, as accepted by the journal, can be found at: 10.17605/OSF.IO/SH2YE’ Techniques: Life sciences techniques, Biophysical methods [Electrocardiography - EKG]; Life sciences techniques, Biophysical methods [Electroencephalography - EEG]; CTS received date: 27.11.2024.

Ageing is associated with alterations in circadian rhythms and thermoregulation, contributing to a fragmentation of the sleep–wake cycle and possibly age-related changes in cognitive performance. In this study, we investigated the relationship between visuo-spatial working memory (vsWM) performance and thermoregulation in young (18–34 years) and old (64–84 years) healthy human adults. Variations in the distal–proximal skin temperature gradient (DPG) were continuously monitored over the 24 h cycle in a field setting. vsWM was assessed during morning (09:00) and evening sessions (17:00) using an object–location binding task. As expected, a reduced circadian DPG amplitude was observed in old as compared to young participants. Likewise, old participants produced more errors than the young ones in object identification and location, suggesting reduced vsWM ability. Notwithstanding this, no significant association was found between circadian DPG modulation and vsWM performance, nor between testing time-of-day and cognitive performance. Further research is needed to explore environmental factors and the timing of peak circadian rhythms to better understand the interplay between circadian biology and cognitive ageing.

Sleep deprivation impairs sustained attention, as measured on the psychomotor vigilance task. This is manifested in a general slowing of reaction times and an increase in periods of unresponsiveness, increasing the risk of accidents. However, the mechanisms are not fully understood. This study combines experiments and modeling to better explain and quantify the changes of sustained attention under sleep deprivation. A total of 317 male participants (age 22.1 $\pm$ 2.7 y) underwent 40 h of sleep deprivation under a constant routine protocol. A 10-minute psychomotor vigilance task was performed at 2-h intervals, and saliva melatonin was sampled every hour to monitor circadian phase. We report a bimodal distribution of reaction speed in the data. An approximately normal primary peak characterizes typical performance (reaction time ≲0.5 s), while periods of unresponsiveness correspond to reaction times ≳1.5 s and are reflected in a secondary peak which emerges after ∼20 h of wakefulness. We developed a minimal, stochastic model that accurately reproduces the data, attributing the bimodality of the distribution to bistability in vigilance state. We find general response slowing to be subject to an ultradian oscillation (∼3 cycles per day), while periods of unresponsiveness are disproportionately affected during the wake maintenance zone. Our results attribute periods of unresponsiveness to the coexistence of two vigilance states in the sleep-deprived brain, enabling new approaches in understanding vulnerability to sleep loss. Statement of Significance Sleep deprivation is prevalent in modern society, leading to an increased risk of accidents due to lapses in attention. In many scenarios, like shiftwork, simply getting more sleep is not an option, so a better understanding of mechanisms is needed. Our study, for the first time, shows a bimodality of response rates during sleep deprivation. We explain this by the co-existence of two vigilance states in the brain. The first state corresponds to typical reaction times in all individuals, while the second state is linked to unresponsiveness with reaction times ≳1.5 s and is observed in ∼60% of individuals. Our model enables new approaches to predict and prevent accidents and new insights into the physiology of sustained attention.

Circadian rhythms shape the temporal organization of sleep and wakefulness and evolve throughout the adult lifespan, leading to higher sleep-wake cycle fragmentation with ageing. The increasing prevalence of daytime napping represents a visible manifestation of such fragmentation and has been suggested to forecast age-related cognitive decline. Here, we assessed the impact of napping on functional brain correlates of performance on a Sternberg working memory (WM) task using functional magnetic resonance imaging in 60 healthy older individuals, prospectively recruited with respect to their napping habits (39 females, age: 59–82y). As compared to non-nappers, nappers showed reduced hemispheric asymmetry in the dorsolateral prefrontal cortex (DLPFC, p< 0.001) and decreased performance at high WM load levels. Only in non-nappers was increased ipsilateral activation in the DLPFC associated with better performance at high WM load levels (p < 0.05), while contralateral activation across all WM load levels was not associated with better performance. These findings indicate that functional brain compensation and dedifferentiation processes vary according to an individual’s napping phenotype, potentially serving as a marker of inter-individual differences in cognitive and brain aging. ### Competing Interest Statement The authors have declared no competing interest. This study was supported by the European Research Council (ERC, ERC-StG‐COGNAP) under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 757763). This study was also supported by the Fonds National de la Recherche Scientifique–FNRS under Grant nr T.0220.20 and by research grant from the University of Liège. C. S. and G. V. are research associates and M.De., M.Do. and S.D. received PhD grants from the Fonds de la Recherche Scientifique–FNRS, Belgium.

Fixed sleep schedules with an 8 h time in bed (TIB) are used to ensure participants are well-rested before laboratory studies. However, such schedules may lead to cumulative excess wakefulness in young individuals. Effects on older individuals are unknown. We combine modelling and experimental data to quantify the effects of sleep debt on sleep propensity in healthy younger and older participants. A model of arousal dynamics was fitted to sleep data from 22 young (20–31 y.o.) and 26 older (61–82 y.o.) individuals (25 male) undertaking 10 short sleep–wake cycles during a 40 h napping protocol, following >1 week of fixed 8 h TIB schedules. Homeostatic sleep drive at the study start was varied systematically to identify best fits between observed and predicted sleep profiles for individuals and group averages. Daytime sleep duration was the same on the two days of the protocol within the groups but different between the groups (young: 3.14 ± 0.98 h vs. 3.06 ± 0.75 h, older: 2.60 ± 0.98 h vs. 2.37 ± 0.64 h). The model predicted an initial homeostatic drive of 11.2 ± 3.5% (young) and 10.1 ± 3.5% (older) above well-rested. Individual variability in first-day, but not second-day, sleep patterns was explained by the differences in the initial homeostatic drive for both age groups. Our study suggests that both younger and older participants arrive at the laboratory with cumulative sleep debt, despite 8 h TiB schedules, which dissipates after the first four sleep opportunities on the protocol. This has implications for protocol design and the interpretation of laboratory studies.

Journal of Sleep ResearchEarly View e14160 LETTER TO THE EDITOR Probing the embodiment of sleep functions: Insights from cardiac responses to word-induced relaxation during sleep Matthieu Koroma, Corresponding Author Matthieu Koroma [email protected] orcid.org/0000-0003-2269-7841 Physiology of Cognition Lab, GIGA-CRC In Vivo Imaging, GIGA Institute, University of Liège, Liège, Belgium Fund for Scientific Research FNRS, Brussels, Belgium Sleep & Chronobiology Laboratory, GIGA-CRC In Vivo Imaging, GIGA Institute, University of Liège, Liège, Belgium Correspondence Matthieu Koroma and Athena Demertzi, Physiology of Cognition Lab, GIGA-CRC In Vivo Imaging Center, University of Liège, Allée du 6 Août, 8 (B30), 4000 Sart Tilman, Liège, Belgium. Email: [email protected] and [email protected] Contribution: Conceptualization, ​Investigation, Writing - original draft, Methodology, Validation, Visualization, Writing - review & editing, Project administration, Formal analysis, Software, Data curation, Resources, Funding acquisition, SupervisionSearch for more papers by this authorJonas Beck, Jonas Beck orcid.org/0000-0002-4637-5911 Swiss Sleep House Bern, Department of Neurology, Inselspital, Bern, Switzerland Contribution: ​Investigation, Validation, Formal analysis, Data curation, Visualization, Writing - review & editing, Methodology, ResourcesSearch for more papers by this authorChristina Schmidt, Christina Schmidt orcid.org/0000-0002-9867-012X Physiology of Cognition Lab, GIGA-CRC In Vivo Imaging, GIGA Institute, University of Liège, Liège, Belgium Fund for Scientific Research FNRS, Brussels, Belgium Sleep & Chronobiology Laboratory, GIGA-CRC In Vivo Imaging, GIGA Institute, University of Liège, Liège, Belgium Psychology & Neuroscience of Cognition (PsyNCog), University of Liège, Liège, Belgium Contribution: Conceptualization, Writing - original draft, Methodology, Validation, Visualization, Project administration, Formal analysis, Supervision, Writing - review & editing, Funding acquisitionSearch for more papers by this authorBjörn Rasch, Björn Rasch orcid.org/0000-0001-7607-3415 Department of Psychology, University of Fribourg, Fribourg, Switzerland Contribution: Data curation, Resources, Project administration, Formal analysis, Visualization, Validation, Funding acquisition, ​Investigation, Conceptualization, Supervision, Methodology, Writing - review & editingSearch for more papers by this authorAthena Demertzi, Corresponding Author Athena Demertzi [email protected] orcid.org/0000-0001-8021-3759 Physiology of Cognition Lab, GIGA-CRC In Vivo Imaging, GIGA Institute, University of Liège, Liège, Belgium Fund for Scientific Research FNRS, Brussels, Belgium Sleep & Chronobiology Laboratory, GIGA-CRC In Vivo Imaging, GIGA Institute, University of Liège, Liège, Belgium Psychology & Neuroscience of Cognition (PsyNCog), University of Liège, Liège, Belgium Correspondence Matthieu Koroma and Athena Demertzi, Physiology of Cognition Lab, GIGA-CRC In Vivo Imaging Center, University of Liège, Allée du 6 Août, 8 (B30), 4000 Sart Tilman, Liège, Belgium. Email: [email protected] and [email protected] Contribution: Supervision, Conceptualization, ​Investigation, Validation, Visualization, Writing - review & editing, Formal analysis, Project administration, Resources, Data curation, Methodology, Writing - original draft, Funding acquisitionSearch for more papers by this author Matthieu Koroma, Corresponding Author Matthieu Koroma [email protected] orcid.org/0000-0003-2269-7841 Physiology of Cognition Lab, GIGA-CRC In Vivo Imaging, GIGA Institute, University of Liège, Liège, Belgium Fund for Scientific Research FNRS, Brussels, Belgium Sleep & Chronobiology Laboratory, GIGA-CRC In Vivo Imaging, GIGA Institute, University of Liège, Liège, Belgium Correspondence Matthieu Koroma and Athena Demertzi, Physiology of Cognition Lab, GIGA-CRC In Vivo Imaging Center, University of Liège, Allée du 6 Août, 8 (B30), 4000 Sart Tilman, Liège, Belgium. Email: [email protected] and [email protected] Contribution: Conceptualization, ​Investigation, Writing - original draft, Methodology, Validation, Visualization, Writing - review & editing, Project administration, Formal analysis, Software, Data curation, Resources, Funding acquisition, SupervisionSearch for more papers by this authorJonas Beck, Jonas Beck orcid.org/0000-0002-4637-5911 Swiss Sleep House Bern, Department of Neurology, Inselspital, Bern, Switzerland Contribution: ​Investigation, Validation, Formal analysis, Data curation, Visualization, Writing - review & editing, Methodology, ResourcesSearch for more papers by this authorChristina Schmidt, Christina Schmidt orcid.org/0000-0002-9867-012X Physiology of Cognition Lab, GIGA-CRC In Vivo Imaging, GIGA Institute, University of Liège, Liège, Belgium Fund for Scientific Research FNRS, Brussels, Belgium Sleep & Chronobiology Laboratory, GIGA-CRC In Vivo Imaging, GIGA Institute, University of Liège, Liège, Belgium Psychology & Neuroscience of Cognition (PsyNCog), University of Liège, Liège, Belgium Contribution: Conceptualization, Writing - original draft, Methodology, Validation, Visualization, Project administration, Formal analysis, Supervision, Writing - review & editing, Funding acquisitionSearch for more papers by this authorBjörn Rasch, Björn Rasch orcid.org/0000-0001-7607-3415 Department of Psychology, University of Fribourg, Fribourg, Switzerland Contribution: Data curation, Resources, Project administration, Formal analysis, Visualization, Validation, Funding acquisition, ​Investigation, Conceptualization, Supervision, Methodology, Writing - review & editingSearch for more papers by this authorAthena Demertzi, Corresponding Author Athena Demertzi [email protected] orcid.org/0000-0001-8021-3759 Physiology of Cognition Lab, GIGA-CRC In Vivo Imaging, GIGA Institute, University of Liège, Liège, Belgium Fund for Scientific Research FNRS, Brussels, Belgium Sleep & Chronobiology Laboratory, GIGA-CRC In Vivo Imaging, GIGA Institute, University of Liège, Liège, Belgium Psychology & Neuroscience of Cognition (PsyNCog), University of Liège, Liège, Belgium Correspondence Matthieu Koroma and Athena Demertzi, Physiology of Cognition Lab, GIGA-CRC In Vivo Imaging Center, University of Liège, Allée du 6 Août, 8 (B30), 4000 Sart Tilman, Liège, Belgium. Email: [email protected] and [email protected] Contribution: Supervision, Conceptualization, ​Investigation, Validation, Visualization, Writing - review & editing, Formal analysis, Project administration, Resources, Data curation, Methodology, Writing - original draft, Funding acquisitionSearch for more papers by this author First published: 14 February 2024 https://doi.org/10.1111/jsr.14160Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Open Research DATA AVAILABILITY STATEMENT The data that support the findings of this study are openly available in OSF at https://osf.io/jn7ar/, reference number doi:10.17605/OSF.IO/JN7AR. REFERENCES Azzalini, D., Rebollo, I., & Tallon-Baudry, C. (2019). Visceral signals shape brain dynamics and cognition. Trends in Cognitive Sciences, 23(6), 488–509. https://doi.org/10.1016/j.tics.2019.03.007 10.1016/j.tics.2019.03.007 PubMedWeb of Science®Google Scholar Beck, J., Loretz, E., & Rasch, B. (2021). Exposure to relaxing words during sleep promotes slow-wave sleep and subjective sleep quality. Sleep, 44(11), zsab148. https://doi.org/10.1093/sleep/zsab148 10.1093/sleep/zsab148 PubMedWeb of Science®Google Scholar Chouchou, F., & Desseilles, M. (2014). Heart rate variability: A tool to explore the sleeping brain? Frontiers in Neuroscience, 8, 402. https://doi.org/10.3389/fnins.2014.00402 10.3389/fnins.2014.00402 PubMedWeb of Science®Google Scholar Kluyver, T., Ragan-Kelley, B., Pérez, F., Granger, B. E., Bussonnier, M., Frederic, J., Kelley, K., Hamrick, J. B., Grout, J., Corlay, S., & Ivanov, P. (2016). Jupyter notebooks – A publishing format for reproducible computational workflows. Position Power Acad Publ Play Agents Agendas. Google Scholar Oudiette, D., & Paller, K. A. (2013). Upgrading the sleeping brain with targeted memory reactivation. Trends in Cognitive Sciences, 17(3), 142–149. https://doi.org/10.1016/j.tics.2013.01.006 10.1016/j.tics.2013.01.006 PubMedWeb of Science®Google Scholar Park, H. D., & Tallon-Baudry, C. (2014). The neural subjective frame: From bodily signals to perceptual consciousness. Transactions of the Royal Society B: Biological Sciences, 369(1641), 20130208. https://doi.org/10.1098/rstb.2013.0208 10.1098/rstb.2013.0208 PubMedWeb of Science®Google Scholar Raimondo, F., Rohaut, B., Demertzi, A., Valente, M., Engemann, D. A., Salti, M., Fernandez Slezak, D., Naccache, L., & Sitt, J. D. (2017). Brain-heart interactions reveal consciousness in noncommunicating patients: Brain-heart interactions. Annals of Neurology, 82(4), 578–591. https://doi.org/10.1002/ana.25045 10.1002/ana.25045 PubMedWeb of Science®Google Scholar Wei, Y., & Van Someren, E. J. (2020). Interoception relates to sleep and sleep disorders. Current Opinion in Behavioral Sciences, 33, 1–7. https://doi.org/10.1016/j.cobeha.2019.11.008 10.1016/j.cobeha.2019.11.008 Web of Science®Google Scholar Whitehurst, L. N., Cellini, N., McDevitt, E. A., Duggan, K. A., & Mednick, S. C. (2016). Autonomic activity during sleep predicts memory consolidation in humans. Proceedings of the National Academy of Sciences, 113(26), 7272–7277. https://doi.org/10.1073/pnas.1518202113 10.1073/pnas.1518202113 CASPubMedWeb of Science®Google Scholar Whitehurst, L. N., Chen, P. C., Naji, M., & Mednick, S. C. (2020). New directions in sleep and memory research: The role of autonomic activity. Current Opinion in Behavioral Sciences, 33, 17–24. https://doi.org/10.1016/j.cobeha.2019.11.001 10.1016/j.cobeha.2019.11.001 Web of Science®Google Scholar Early ViewOnline Version of Record before inclusion in an issuee14160 ReferencesRelatedInformation

Circadian rhythms are inherent to living organisms from single cells to humans and operate on a genetically determined cycle of approximately 24 hours. These endogenous rhythms are aligned with the external light/dark cycle of the Earth's rotation and offer the advantage of anticipating environmental changes. Circadian rhythms act directly on human cognition and indirectly through their fundamental influence on sleep/wake cycles. The strength of the circadian regulation of performance depends on the accumulated sleep debt and the cognitive domain, and it has been suggested to involve the activation of ascending arousal systems and their interaction with attention and other cognitive processes. In addition, attention-related cortical responses show extensive circadian rhythms, the phases of which vary across brain regions. This review discusses the impact of the circadian system on sleep/wake regulation and cognitive performance. It further addresses the health implications of circadian disruption, particularly in relation to mental and neurological disorders.

Sleep, circadian rhythms, and mental health are reciprocally interlinked. Disruption to the quality, continuity, and timing of sleep can precipitate or exacerbate psychiatric symptoms in susceptible individuals, while treatments that target sleep—circadian disturbances can alleviate psychopathology. Conversely, psychiatric symptoms can reciprocally exacerbate poor sleep and disrupt clock-controlled processes. Despite progress in elucidating underlying mechanisms, a cohesive approach that integrates the dynamic interactions between psychiatric disorder with both sleep and circadian processes is lacking. This review synthesizes recent evidence for sleep—circadian dysfunction as a transdiagnostic contributor to a range of psychiatric disorders, with an emphasis on biological mechanisms. We highlight observations from adolescent and young adults, who are at greatest risk of developing mental disorders, and for whom early detection and intervention promise the greatest benefit. In particular, we aim to a) integrate sleep and circadian factors implicated in the pathophysiology and treatment of mood, anxiety, and psychosis spectrum disorders, with a transdiagnostic perspective; b) highlight the need to reframe existing knowledge and adopt an integrated approach which recognizes the interaction between sleep and circadian factors; and c) identify important gaps and opportunities for further research.

The regional integrity of brain subcortical structures has been implicated in sleep-wake regulation, however, their associations with sleep parameters remain largely unexplored. Here, we assessed association between quantitative Magnetic Resonance Imaging (qMRI)-derived marker of the myelin content of the brainstem and the variability in the sleep electrophysiology in a large sample of 18-to-31 years healthy young men (N = 321; similar to 22 years). Separate Generalized Additive Model for Location, Scale and Shape (GAMLSS) revealed that sleep onset latency and slow wave energy were significantly associated with MTsat estimates in the brainstem (p(corrected) <= 0.03), with overall higher MTsat value associated with values reflecting better sleep quality. The association changed with age, however (MTsat-by-age interaction-p(corrected) <= 0.03), with higher MTsat value linked to better values in the two sleep metrics in the younger individuals of our sample aged similar to 18 to 20 years. Similar associations were detected across different parts of the brainstem (p(corrected) <= 0.03), suggesting that the overall maturation and integrity of the brainstem was associated with both sleep metrics. Our results suggest that myelination of the brainstem nuclei essential to regulation of sleep is associated with inter-individual differences in sleep characteristics during early adulthood. They may have implications for sleep disorders or neurological diseases related to myelin.