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.

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.

Rapid eye movement sleep (REMS) is increasingly suggested as a discriminant sleep state for subtle signs of age-related neurodegeneration. While REMS expression is under strong circadian control and circadian dysregulation increases with age, the association between brain aging and circadian REMS regulation has not yet been assessed. Here, we measure the circadian amplitude of REMS through a 40-h in-lab multiple nap protocol in controlled laboratory conditions, and brain microstructural integrity with quantitative multi-parameter mapping (MPM) imaging in 86 older individuals. We show that reduced circadian REMS amplitude is related to lower magnetization transfer saturation (MTsat), longitudinal relaxation rate (R1) and effective transverse relaxation rate (R2*) values in several white matter regions mostly located around the lateral ventricles, and with lower R1 values in grey matter clusters encompassing the hippocampus, parahippocampus, thalamus and hypothalamus. Our results further highlight the importance of considering circadian regulation for understanding the association between sleep and brain structure in older individuals.

Light exposure fundamentally influences human physiology and behavior, with light being the most important zeitgeber of the circadian system. Throughout the day, people are exposed to various scenes differing in light level, spectral composition and spatio-temporal properties. Personalized light exposure can be measured through wearable light loggers and dosimeters, including wrist-worn actimeters containing light sensors, yielding time series of an individual's light exposure. There is growing interest in relating light exposure patterns to health outcomes, requiring analytic techniques to summarize light exposure properties. Building on the previously published Python-based pyActigraphy module, here we introduce the module pyLight. This module allows users to extract light exposure data recordings from a wide range of devices. It also includes software tools to clean and filter the data, and to compute common metrics for quantifying and visualizing light exposure data. For this tutorial, we demonstrate the use of pyLight in one example dataset with the following processing steps: (1) loading, accessing and visual inspection of a publicly available dataset, (2) truncation, masking, filtering and binarization of the dataset, (3) calculation of summary metrics, including time above threshold (TAT) and mean light timing above threshold (MLiT). The pyLight module paves the way for open-source, large-scale automated analyses of light-exposure data.

Background:Light exposure significantly impacts human health, regulating our circadian clock, sleep-wake cycle and other physiological processes. With the emergence of wearable light loggers and dosimeters, research on real-world light exposure effects is growing. There is a critical need to standardize data collection and documentation across studies. Results:This article proposes a new metadata descriptor designed to capture crucial information within personalized light exposure datasets collected with wearable light loggers and dosimeters. The descriptor, developed collaboratively by international experts, has a modular structure for future expansion and customization. It covers four key domains: study design, participant characteristics, dataset details, and device specifications. Each domain includes specific metadata fields for comprehensive documentation. The user-friendly descriptor is available in JSON format. A web interface simplifies generating compliant JSON files for broad accessibility. Version control allows for future improvements. Conclusions:Our metadata descriptor empowers researchers to enhance the quality and value of their light dosimetry datasets by making them FAIR (findable, accessible, interoperable and reusable). Ultimately, its adoption will advance our understanding of how light exposure affects human physiology and behaviour in real-world settings.

Sleep has been suggested to contribute to myelinogenesis and associated structural changes in the brain. As a principal hallmark of sleep, slow-wave activity (SWA) is homeostatically regulated but also differs between individuals. Besides its homeostatic function, SWA topography is suggested to reflect processes of brain maturation. Here, we assessed whether interindividual differences in sleep SWA and its homeostatic response to sleep manipulations are associated with in-vivo myelin estimates in a sample of healthy young men. Two hundred twenty-six participants (18-31 y.) underwent an in-lab protocol in which SWA was assessed at baseline (BAS), after sleep deprivation (high homeostatic sleep pressure, HSP) and after sleep saturation (low homeostatic sleep pressure, LSP). Early-night frontal SWA, the frontal-occipital SWA ratio, as well as the overnight exponential SWA decay were computed over sleep conditions. Semi-quantitative magnetization transfer saturation maps (MTsat), providing markers for myelin content, were acquired during a separate laboratory visit. Early-night frontal SWA was negatively associated with regional myelin estimates in the temporal portion of the inferior longitudinal fasciculus. By contrast, neither the responsiveness of SWA to sleep saturation or deprivation, its overnight dynamics, nor the frontal/occipital SWA ratio were associated with brain structural indices. Our results indicate that frontal SWA generation tracks inter-individual differences in continued structural brain re-organization during early adulthood. This stage of life is not only characterized by ongoing region-specific changes in myelin content, but also by a sharp decrease and a shift towards frontal predominance in SWA generation.

Abstract This article introduces a comprehensive metadata descriptor aimed at capturing crucial metadata information within personalized light exposure datasets. This metadata descriptor fills a critical gap in the field of personalized light exposure research by promoting standardized documentation of light exposure metadata. Light exposure profoundly impacts human physiology and behaviour, playing a central role in regulating the circadian system and influencing various physiological processes. As research on the real-world effects of light exposure gains momentum through the development of wearable sensors and light-logging technologies incorporating digital health approaches, there is a need to harmonize and standardize data collection and documentation across diverse studies and settings. The metadata descriptor was collaboratively developed by an international team of experts through a scoping exercise and synchronous discussions. It covers study-level, participant-level, dataset-level, and device-level metadata. The structure of the descriptor was designed to be modular, allowing for future expansions and customizations. The metadata descriptor comprises four main domains: study-level information, participant-level information, dataset-level information, and device-level information. Each domain includes specific metadata fields, ensuring comprehensive documentation of the data collection process. The metadata descriptor is available in JavaScript Object Notation (JSON) format, facilitating both human and machine readability. A user-friendly web interface has been developed for generating compliant JSON files, making it accessible to a wide range of users. The descriptor follows versioning principles to accommodate future updates and improvements. Following a description of the latest version, the article outlines several future directions for the metadata descriptor, including validation in real-world settings, independent evaluation, community-driven development, implementation in multiple software languages, and endorsement by scientific organizations. Integration with data repositories and platforms is also essential for streamlining data management and sharing. The metadata descriptor adheres to FAIR data principles, ensuring data is findable, accessible, interoperable, and reusable. Researchers are encouraged to adopt this descriptor to enhance the quality and utility of their light dosimetry datasets, ultimately advancing our understanding of the non-visual effects of light in real-world contexts.

Light exposure fundamentally influences human physiology and behavior, with light being the most important zeitgeber of the circadian system. Throughout the day, people are exposed to various scenes differing in light level, spectral composition and spatio-temporal properties. Personalized light exposure can be measured through wearable light loggers and dosimeters, including wrist-worn actimeters containing light sensors, yielding time courses of an individual’s light exposure. There is growing interest in relating light exposure patterns to health outcomes, requiring analytic techniques to summarize light exposure properties. Building on the previously published Python-based pyActigraphy module, here we introduce the module pyLight. This module allows users to extract light exposure data recordings from a wide range of devices. It also includes software tools to clean and filter the data, and to compute common metrics for quantifying and visualizing light exposure data. For this tutorial, we demonstrate the use of pyLight in three examples: (1) loading, accessing and visual inspection of a dataset, (2) truncation, masking, filtering and binarization of the dataset, (3) calculation of summary metrics, including time above threshold (TAT) and mean light timing above threshold (MLit). The pyLight module paves the way for open-source, large-scale automated analyses of light-exposure data.

Circadian dysfunction increases with age, leading to changes in the circadian regulation of physiological and biological rhythms, including sleep. Actigraphy studies demonstrated that altered 24-h rest-activity patterns, an estimate of circadian sleep-wake regulation, is related to cognitive decline and tightly linked to Alzheimer’s disease progression. Here, we assessed whether circadian sleep regulation, measured during a multiple naps protocol, is related to brain microstructural integrity in a group of cognitively unimpaired older adults. Eighty-six retired older individuals (mean age [SD] = 69.9 ± 5.2 y.o., 32 females, Table 1 ) with no major sleep disorders or medical condition, underwent an in-lab 40-h multiple naps protocol and brain structural magnetic resonance imaging. As rapid eye movement (REM) sleep is under strong circadian control, circadian REM sleep amplitude was computed by fitting a Gaussian curve on REM sleep duration (% of total sleep time) measured for each nap opportunity. The multiparametric mapping protocol was used to derive indices of brain tissue microstructure using magnetization transfer saturation (MTsat), R1 and R2* maps (hMRI toolbox v0.2.2). Statistical models were adjusted for age, sex, education, and for additional covariates related to sleep architecture and its circadian modulation, including mean REM% and sleep efficiency (SE), the accumulation of REM sleep and sleep need (slope of a fitted first-order polynomial curve), and circadian SE amplitude. Whole-brain voxel-based quantification analysis revealed that low circadian REM amplitude was related to low MTsat, R1 and R2* values in several white matter regions mostly located around the lateral ventricles ( Figure 1A ). In addition, a significant association was observed between low circadian REM amplitude and low R1 values in two grey matter clusters encompassing the hippocampus, entorhinal cortex, thalamus and hypothalamus ( Figure 1B ). Our findings provide first evidence that changes in circadian sleep regulation is associated with microstructural changes in key brain regions sensitive to the aging process and involved in sleep-wake regulation. These results further emphasize the relevance of monitoring circadian sleep regulation for the early detection of individuals at risk for neurodegeneration and cognitive decline.

The circadian system orchestrates sleep timing and structure and is altered with increasing age. Sleep propensity, and particularly REM sleep is under strong circadian control and has been suggested to play an important role in brain plasticity. In this exploratory study, we assessed whether surface-based brain morphometry indices are associated with circadian sleep regulation and whether this link changes with age. Twenty-nine healthy older (55-82 years; 16 men) and 28 young participants (20-32 years; 13 men) underwent both structural magnetic resonance imaging and a 40-h multiple nap protocol to extract sleep parameters over day and night time. Cortical thickness and gyrification indices were estimated from T1-weighted images acquired during a classical waking day. We observed that REM sleep was significantly modulated over the 24-h cycle in both age groups, with older adults exhibiting an overall reduction in REM sleep modulation compared to young individuals. Interestingly, when taking into account the observed overall age-related reduction in REM sleep throughout the circadian cycle, higher day-night differences in REM sleep were associated with increased cortical gyrification in the right inferior frontal and paracentral regions in older adults. Our results suggest that a more distinctive allocation of REM sleep over the 24-h cycle is associated with regional cortical gyrification in aging, and thereby point towards a protective role of circadian REM sleep regulation for age-related changes in brain organization.

ABSTRACT Study objectives Daytime napping is frequently reported among the older population and has attracted increasing attention due to its association with multiple health conditions. Here, we tested whether napping in the aged is associated with altered circadian regulation of sleep, sleepiness and vigilance performance. Methods Sixty healthy older individuals (mean age: 69y., 39 women) were recruited with respect to their napping habits (30 nappers, 30 non-nappers). All participants underwent an in-lab 40-h multiple nap protocol (10 cycles of 80 mins of sleep opportunity alternating with 160 mins of wakefulness), preceded and followed by a baseline and recovery sleep period. Saliva samples for melatonin assessment, sleepiness and vigilance performance were collected during wakefulness and electrophysiological data were recorded to derive sleep parameters during scheduled sleep opportunities. Results The circadian amplitude of melatonin secretion was reduced in nappers, compared to non-nappers. Furthermore, nappers were characterized by higher sleep efficiencies and REM sleep proportion during day-compared to night-time naps. The nap group also presented altered modulation in sleepiness and vigilance performance at specific circadian phases. Discussion Our data indicate that napping is associated with an altered circadian sleep-wake propensity rhythm and thereby contribute to the understanding of the biological correlates underlying napping and/or sleep-wake cycle fragmentation during healthy aging. Altered circadian sleep-wake promotion can lead to a less distinct allocation of sleep into night-time and/or a reduced wakefulness drive during the day, thereby potentially triggering the need to sleep at adverse circadian phase. SIGNIFICANCE STATEMENT While napping has raised increasing interest as a health risk factor in epidemiological studies, its underlying regulation processes in the aged remain largely elusive. Here we assessed whether napping in the older population is associated with physiological and behavioral changes in circadian sleep-wake characteristics. Our data indicate that, concomitant to a reduced circadian amplitude in melatonin secretion, healthy older nappers are characterized by reduced day-night differences in sleep efficiency and more particularly in REM sleep, compared to their non-napping counterparts. These results suggest altered circadian response as a cause or consequence of chronic napping in the aged and thereby contribute to the understanding of nap regulation during healthy aging.

Le vieillissement s’accompagne d’une fragmentation du sommeil et d’une déstabilisation du cycle de repos-activité sur 24 h. Cela pourrait être lié à une perturbation sous-jacente du rythme circadien, reflétée par l’habitude du repos diurne. Nous pensons que la sieste est associée à une altération du rythme circadien, évalué par l’extraction du gradient de température distal-proximal (DPG). Cinquante-huit sujets en bonne santé (69,5 + 5,8 ans) ont été répartis en 2 groupes selon leurs habitudes de sieste, évaluées par actimétrie. Ils ont pris part à un protocole de routine constante (CR) à siestes multiples de 40-h, alternant 10 cycles de 160 min d’éveil et 80 min de sieste. Le DPG était extrait par iButtons situés sur les membres proximaux et distaux. La somnolence était évaluée 3 fois par épisodes d’éveil par le questionnaire KSS, et l’efficience de sommeil (ES) était dérivée de mesures polysomnographiques pendant les siestes. Des ANOVA à mesures répétées ont été effectuées pour voir si la sieste impacte la modulation du DPG, de la somnolence ou de l’ES. Le DPG est supérieur lors des opportunités de siestes que lors de l’éveil (p < 0,001), et est modulé circadiennement, tout comme la somnolence et l’ES (p < 0,001). Les siesteurs ont une température proximale supérieure aux contrôles, quel que soit l’état de veille (p = 0,002), et montrent une meilleure ES, surtout lors de la journée (p < 0,001). En l’absence de différence de somnolence diurne, la sieste semble être liée à une altération de la régulation de la température proximale et à une répartition moins distincte de l’ES sur un cycle de 24 h.

The purpose of Bidsme is to organize a given medical image dataset following the "Brain Imaging Data Structure" (BIDS; Gorgolewski et al., 2016).Bidsme is an all-in-one organizer tool, that not only renames and re-structures the original data files, but also extracts and formats the necessary metadata.During the data organization, Bidsme provides the user with the full control over these processes, allowing the use of non-standard metadata and file names, as well as the addition of modalities not yet described by the BIDS.Instead of strictly imposing this structure, Bidsme allows the user to fully configure how the source dataset will be organized and what metadata will be included.Bidsme can be used both as Python package and command-line tool, and includes a tutorial with a test dataset.

Context: Cognitive fatigue (CF) is a disabling symptom frequently reported by patients with Multiple Sclerosis (pwMS). Whether pwMS in the early disease stages present an increased sensitivity to fatigue induction remains debated. Objective measures of CF have been validated neither for clinical nor research purposes. This study aimed at (i) assessing how fatigue induction by manipulation of cognitive load affects subjective fatigue and behavioural performance in newly diagnosed pwMS and matched healthy controls (HC); and (ii) exploring the relevance of eye metrics to describe CF in pwMS. Methods: Nineteen pwMS with disease duration < 5 years and 19 matched HC participated to this study. CF was induced with a dual-task in two separate sessions with varying cognitive load (High and Low cognitive load conditions, HCL and LCL). Accuracy, reaction times (RTs), subjective fatigue and sleepiness states were assessed. Bayesian Analyses of Variance for repeated measures (rmANOVA) explored the effects of time, group and load condition on the assessed variables. Eye metrics (number of long blinks, pupil size and pupil response speed: PRS) were obtained during the CF task for a sub-sample (16 pwMS and 15 HC) and analysed with Generalized Linear Mixed Models (GLMM). Results: Performance (accuracy and RTs) was lower in the HCL condition and accuracy decreased over time (BFsincl > 100) while RTs did not significantly vary. Performance over task and conditions followed the same pattern of evolution across groups (BFsincl < 0.08) suggesting that pwMS did not show increased alteration of performance during fatigue induction. Regarding subjective state, both fatigue and sleepiness increased following the task (BFsincl > 15), regardless of condition and group (BFsincl < 3). CF in pwMS seems to be associated with PRS, as PRS decreased during the task amongst pwMS only and especially in the HCL condition (all p < .05). A significant Condition*Group interaction was observed regarding long blinks (p < .0001) as well as an expected effect of cognitive load condition on pupil diameter (p < .01). Conclusion: These results suggest that newly diagnosed pwMS and HC behave similarly during fatigue induction, in terms of both performance decrement and accrued fatigue sensation. Eye metric data further reveal a sus-ceptibility to CF in pwMS, which can be objectively measured.

Growing epidemiological evidence points toward an association between fragmented 24-h rest-activity cycles and cognition in the aged. Alterations in the circadian timing system might at least partially account for these observations. Here, we tested whether daytime rest (DTR) is associated with changes in concomitant 24-h rest probability profiles, circadian timing and neurobehavioural outcomes in healthy older adults. Sixty-three individuals (59-82 years) underwent field actigraphy monitoring, in-lab dim light melatonin onset assessment and an extensive cognitive test battery. Actimetry recordings were used to measure DTR frequency, duration and timing and to extract 24-h rest probability profiles. As expected, increasing DTR frequency was associated not only with higher rest probabilities during the day, but also with lower rest probabilities during the night, suggesting more fragmented night-time rest. Higher DTR frequency was also associated with lower episodic memory performance. Moreover, later DTR timing went along with an advanced circadian phase as well as with an altered phase angle of entrainment between the rest-activity cycle and circadian phase. Our results suggest that different DTR characteristics, as reflective indices of wake fragmentation, are not only underlined by functional consequences on cognition, but also by circadian alteration in the aged.