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Sleep and physical activity levels are both associated with cognitive performance among older adults; however, the brain mechanisms underlying these beneficial relationships remain poorly understood. This study investigated cross-sectional associations of actigraphic estimates of physical activity and sleep with cognition and diffusion imaging-based measures of medial temporal lobe (MTL) gray matter microstructural integrity in adults free of dementia. Participants were 132 older adults from the Biomarkers of Cognitive Decline Among Normal Individuals (BIOCARD) cohort study (119 cognitively unimpaired and 13 with mild cognitive impairment; mean age=70.8 years). Multiple linear regression analyses assessed the relationships between total volume of physical activity (TVPA), total sleep time (TST), and sleep efficiency (SE) with cognitive performance and MTL microstructural integrity. Results indicated that greater TVPA and SE were both independently associated with higher hippocampal and parahippocampal microstructure integrity (indicated by lower mean diffusivity) and better visuospatial processing abilities, independent of the volume of these structures and of amyloid burden, measured by positron emission tomography. Additionally, higher hippocampal microstructure statistically mediated the independent associations of physical activity and sleep with visuospatial abilities, independent of MTL volume and Aβ load. These findings suggest that physical activity and sleep are independently associated with cognitive performance, and that hippocampal microstructural integrity may be an underlying mechanism supporting these associations., Competing Interests: Conflict of Interest Vadim Zipunnikov consults with Takeda Pharmaceuticals. The details of the contracts are disclosed through the Johns Hopkins University eDisclose system and have no direct or apparent relationship with the current paper. Adam Spira received payment for serving as a consultant for Merck, received honoraria from Springer Nature Switzerland AG for guest editing special issues of Current Sleep Medicine Reports, and is a paid consultant to Sequoia Neurovitality, BellSant, Inc., and Amissa, Inc. These roles have no direct or apparent relationship with the current paper. Arnold Bakker is a paid consultant to AgeneBio, Inc. Arnold Bakker’s role in the current study was in compliance with the conflict of interest policies of the Johns Hopkins School of Medicine. His consulting role has no direct or apparent relationship with the current paper. The authors verify that each of the following statements is true pertaining to the submitted manuscript., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Few studies of the association between accelerometry-assessed physical activity with major depressive disorder (MDD) have considered the influence of both the averages and variability features, the physical health correlates of depression, or the extent to which changes in sleep and physical activity reflect current state versus enduring patterns of MDD in people with depression., Methods: The sample includes 2307 participants from a population cohort from Lausanne, Switzerland. Average and variability of daily sleep (SL), physical activity (PA), and circadian rhythmicity (CR) were derived from accelerometry., Results: Cardiovascular risk factors, particularly cigarette smoking and body mass index (BMI), were significantly associated with both the average and variability of SL, PA, and CR, and with MDD. Lower average and less variable physical activity, as well as more variable circadian rhythmicity were associated with remitted MDD, whereas later sleep midpoint and greater variation of sleep duration variability were associated with depressive states., Limitation: The cross-sectional nature and two-week assessment period limit within-person interpretations and directional inferences., Conclusion: The findings demonstrate the importance of considering both the average and variability of accelerometry-derived phenotypes that may distinguish state from trait manifestations of MDD. Further, the confounding influence of smoking, particularly on state manifestations of MDD, should be considered in studies of accelerometer derived phenotypes, particularly sleep characteristics. Interventions for depression should therefore consider modification of health behaviors such as smoking and overweight, as well as stabilizing the 24-hour rest-activity cycle, rather than treatments that focus solely on mood, sleep or physical activity alone., Competing Interests: Declaration of competing interest The authors declare that there are no conflicts of interest., (Copyright © 2025. Published by Elsevier B.V.)

Objective: The evaluate the association between changes in accelerometry-derived activity patterns and brain atrophy in people with multiple sclerosis (PwMS)., Methods: We included PwMS aged ≥40 years with approximately annual brain MRI who wore GT9X Actigraph accelerometers every three months over two years. Functional principal components analysis (fPCA) summarized overall activity and timing. Additional indices included total and 2-hour specific activity, sedentary time, and circadian rhythm parameters. Whole brain segmentation used SLANT-CRUISE. Generalized estimating equations quantifying between- and within-person effects modeled associations between accelerometry changes and MRI outcomes, adjusting for demographic and clinical factors., Results: We included 233 PwMS (mean age: 54.4 years, SD: 8.6, 30% male) who wore accelerometers an average of 6.3 times over 58 days across two years. fPCA showed within-person increases in the first fPC, representing low nighttime and high morning activity, were associated with slower brain atrophy (per 1 SD increase: 0.24%; 95% CI: 0.10, 0.40; p=0.0009). Similarly, a 10% increase in 8:00-10:00 AM activity was associated with 0.49% higher whole brain volume (95% CI: 0.19, 0.79; p=0.001) over time, while increased nighttime activity (0:00-2:00) was linked to -0.28% brain volume loss (95% CI: -0.48, -0.08; p=0.007). Higher moderate-to-vigorous activity and daytime activity were associated with greater brain volume preservation longitudinally., Interpretation: Changes in activity patterns, particularly increased nighttime activity and reduced morning activity, are linked to brain atrophy in PwMS. Accelerometry offers a scalable, sensitive method for tracking MS progression and may be beneficial as a recruitment or outcome measure in trials., Competing Interests: Conflicts of Interest Kathryn Fitzgerald receives consulting fees from SetPoint Medical. Ellen Mowry serves as PI for investigator-initiated studies from Biogen and Genentech. She also receives royalties for editorial duties on UpToDate and consulting fees from BeCareLink, LLC.

Although prior studies have examined associations of personality traits with sleep, most have investigated self-reported sleep, been cross-sectional, and focused on younger and middle-aged adults. We investigated associations of personality with actigraphic sleep parameters and changes in sleep in 398 cognitively normal adults aged 40-95 years (M ± SD = 70.1 ± 12.0) in the Baltimore Longitudinal Study of Aging. Participants completed the Revised NEO Personality Inventory (NEO-PI-R) and 6.61 days +/-1.01 nights of wrist actigraphy at the same study visit. Participants with wrist actigraphy at multiple study visits had actigraphy data at 3.11 ± 1.52 visits (follow-up = 2.35 ± 0.70 years). Adjusting for age, sex, race, education, depressive symptoms, comorbidities and interactions of these variables with time, greater extraversion was associated with higher sleep efficiency. After further adjustment for BMI, sleep medication use, and sleep apnea symptoms, greater extraversion was associated with shorter total sleep time, and greater openness was associated with shorter average wake bout length. We observed numerous interactions of personality with sex and age, with stronger personality-sleep associations generally present at younger ages (i.e., aged 50-60 vs. 70-80) and sex differences in associations. Middle-aged and older adults higher in extraversion and lower in openness may be more vulnerable to poor sleep and may benefit from screening for sleep disturbances., Competing Interests: Declarations. Competing interests: Adam Spira received payment for serving as a consultant for Merck, received honoraria from Springer Nature Switzerland AG for guest editing special issues of Current Sleep Medicine Reports, and is a paid consultant to Sequoia Neurovitality, BellSant, Inc. and Amissa, Inc. The other authors declare no competing interests., (© 2024. The Authors. Parts of this work were authored by US Federal Government authors and are not under copyright protection in the US; foreign copyright protection may apply. 2024.)

Mobile health studies often collect multiple within-day self-reported assessments of participants' behavior and well-being on different scales such as physical activity (continuous scale), pain levels (truncated scale), mood states (ordinal scale), and the occurrence of daily life events (binary scale). These assessments, when indexed by time of day, can be treated and analyzed as functional data corresponding to their respective types: continuous, truncated, ordinal, and binary. Motivated by these examples, we develop a functional principal component analysis that deals with all four types of functional data in a unified manner. It employs a semiparametric Gaussian copula model, assuming a generalized latent non-paranormal process as the underlying generating mechanism for these four types of functional data. We specify latent temporal dependence using a covariance estimated through Kendall's τ $$ \tau $$ bridging method, incorporating smoothness in the bridging process. The approach is then extended with methods for handling both dense and sparse sampling designs, calculating subject-specific latent representations of observed data, latent principal components and principal component scores. Simulation studies demonstrate the method's competitive performance under both dense and sparse sampling designs. The method is applied to data from 497 participants in the National Institute of Mental Health Family Study of Mood Spectrum Disorders to characterize differences in within-day temporal patterns of mood in individuals with the major mood disorder subtypes, including Major Depressive Disorder and Type 1 and 2 Bipolar Disorder. Software implementation of the proposed method is provided in an R-package., (© 2024 The Author(s). Statistics in Medicine published by John Wiley & Sons Ltd.)

Objectively measuring physical activity (PA) has consistently shown an association with reduced all-cause mortality risk in cross-sectional studies. However, the strength of this association may change over time. We quantify the time-varying, covariate-adjusted association between the total volume of PA and all-cause mortality over a 12-year follow-up period using Cox regression with a time varying effect of population-referenced quantile total activity count adjusted for traditional risk factors. Analyses focus on participants 50-84 years old with adequate accelerometer wear time and without missing covariates. The findings suggest that (1) the use of baseline PA in Cox models with long follow-up periods may be inappropriate without time-varying effects and (2) the use of accelerometry derived volume of PA in risk score calculations may be most appropriate for short-term to medium-term risk scores., Competing Interests: Competing interests: CC is consulting with Bayer and Johnson and Johnson on methods development for wearable devices in clinical trials. The details of the contracts are disclosed through the Johns Hopkins University eDisclose system and have no direct or apparent relationship with this manuscript., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Cannabis may be an alternative or adjunct to opioid therapy for chronic pain. However, there are limited data on patterns of opioid medication and medical cannabis use. The current study investigated the feasibility of using Ecological Momentary Assessment (EMA) to assess patterns of prescription opioids and medical cannabis among individuals experiencing chronic pain., Method: The study included 133 participants recruited online. Participants were 42.6 (SD = 13.9) years old on average and the majority were men (57.9 %) and Non-Hispanic White (63.2 %). Participants completed a baseline assessment, followed by 30 days of EMA data collection with four randomly prompted past-hour surveys and one daily diary per day, and a follow-up survey that assessed perceived EMA burden. Simple and multivariable linear regression models were estimated to investigate participant predictors of the proportion of EMA surveys completed (past-hour surveys and daily diaries in separate models)., Results: Compliance rates for EMA prompts were 89.7 % for daily diaries and 63.3 % for past-hour surveys. In multivariable regression, participants holding a graduate degree completed a lower proportion of daily diaries ( b  = -0.109, SE  = 0.052, p  < .05) and past-hour surveys ( b  = -0.148, SE  = 0.071, p  < .05), compared to those with less than a 4-year degree. Participants completing a higher proportion of daily diaries reported greater ease of use at follow-up ( b  = 0.050, SE  = 0.022, p  < .05) and those completing a higher proportion of past-hour surveys desired higher rewards ( b  = 0.066, SE  = 0.033, p  < .05)., Conclusions: Study results confirm the feasibility of using EMA methods to assess patterns of prescription opioids and medical cannabis among individuals experiencing chronic pain., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: In the past 3 years, KED has been paid as a consultant for Canopy, MindMed, and Cessation Therapeutics; received honoraria for advisory board work for Canopy Corporation and Beckley-Canopy; and received research and salary support from the National Institutes on Drug Abuse and Cure Addiction Now. PHF is on the advisory board for Ninnion Therapeutics. RV has received honoraria or consulting fees from Charlotte's Web, Jazz Pharmaceuticals, WebMD, Syqe Medical, and Mira1a Therapeutics., (© 2024 The Authors.)

Importance: Accelerometry has been increasingly used as an objective index of sleep, physical activity, and circadian rhythms in people with mood disorders. However, most prior research has focused on sleep or physical activity alone without consideration of the strong within- and cross-domain intercorrelations; and few studies have distinguished between trait and state profiles of accelerometry domains in major depressive disorder (MDD)., Objectives: To identify joint and individual components of the domains derived from accelerometry, including sleep, physical activity, and circadian rhythmicity using the Joint and Individual Variation Explained method (JIVE), a novel multimodal integrative dimension-reduction technique; and to examine associations between joint and individual components with current and remitted MDD., Design, Setting, and Participants: This cross-sectional study examined data from the second wave of a population cohort study from Lausanne, Switzerland. Participants included 2317 adults (1164 without MDD, 185 with current MDD, and 968 with remitted MDD) with accelerometry for at least 7 days. Statistical analysis was conducted from January 2021 to June 2023., Main Outcomes and Measures: Features derived from accelerometry for 14 days; current and remitted MDD. Logistic regression adjusted for age, sex, body mass index, and anxiety and substance use disorders., Results: Among 2317 adults included in the study, 1261 (54.42%) were female, and mean (SD) age was 61.79 (9.97) years. JIVE reduced 28 accelerometry features to 3 joint and 6 individual components (1 sleep, 2 physical activity, 3 circadian rhythms). Joint components explained 58.5%, 79.5%, 54.5% of the total variation in sleep, physical activity, and circadian rhythm domains, respectively. Both current and remitted depression were associated with the first 2 joint components that were distinguished by the salience of high-intensity physical activity and amplitude of circadian rhythm and timing of both sleep and physical activity, respectively. MDD had significantly weaker circadian rhythmicity., Conclusions and Relevance: Application of a novel multimodal dimension-reduction technique demonstrates the importance of joint influences of physical activity, circadian rhythms, and timing of both sleep and physical activity with MDD; dampened circadian rhythmicity may constitute a trait marker for MDD. This work illustrates the value of accelerometry as a potential biomarker for subtypes of depression and highlights the importance of consideration of the full 24-hour sleep-wake cycle in future studies.

Study Objectives: To compare sleep and 24-hour rest/activity rhythms (RARs) between cognitively normal older adults who are β-amyloid-positive (Aβ+) or Aβ- and replicate a novel time-of-day-specific difference between these groups identified in a previous exploratory study., Methods: We studied 82 cognitively normal participants from the Baltimore Longitudinal Study of Aging (aged 75.7 ± 8.5 years, 55% female, 76% white) with wrist actigraphy data and Aβ+ versus Aβ- status measured by [11C] Pittsburgh compound B positron emission tomography. RARs were calculated using epoch-level activity count data from actigraphy. We used novel, data-driven function-on-scalar regression analyses and standard RAR metrics to cross-sectionally compare RARs between 25 Aβ+ and 57 Aβ- participants., Results: Compared to Aβ- participants, Aβ+ participants had higher mean activity from 1:00 p.m. to 3:30 p.m. when using less conservative pointwise confidence intervals (CIs) and from 1:30 p.m. to 2:30 p.m. using more conservative, simultaneous CIs. Furthermore, Aβ+ participants had higher day-to-day variability in activity from 9:00 a.m. to 11:30 a.m. and lower variability from 1:30 p.m. to 4:00 p.m. and 7:30 p.m. to 10:30 p.m. according to pointwise CIs, and lower variability from 8:30 p.m. to 10:00 p.m. using simultaneous CIs. There were no Aβ-related differences in standard sleep or RAR metrics., Conclusions: Findings suggest Aβ+ older adults have higher, more stable day-to-day afternoon/evening activity than Aβ- older adults, potentially reflecting circadian dysfunction. Studies are needed to replicate our findings and determine whether these or other time-of-day-specific RAR features have utility as markers of preclinical Aβ deposition and if they predict clinical dementia and agitation in the afternoon/evening (i.e. "sundowning")., (© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background and Aims: Physical inactivity and poor sleep are common in older adults and may interact to contribute to age- and disease-related cognitive decline. However, prior work regarding the associations among physical activity, and cognition in older adults is primarily limited to subjective questionnaires that are susceptible to inaccuracies and recall bias. Therefore, this study examined whether objectively measured physical activity and sleep characteristics, each estimated using actigraphy, are independently or interactively associated with cognitive performance., Methods: The study included 157 older adults free of dementia (136 cognitively unimpaired; 21 MCI; M age = 71.7) from the BIOCARD cohort., Results: Using multiple linear regression, cognition was regressed on estimated total volume of physical activity (TVPA), sleep efficiency (SE), wake after sleep onset (WASO), and total sleep time (TST) (adjusted for age, sex, education, diagnosis, vascular risk factors, and Apolipoprotein E (APOE)-e4 genetic status). Models were also run for domain-specific cognitive composite scores. TVPA and SE each were positively associated with a global cognitive composite score. TVPA was positively associated with executive function and language composites, and SE was positively related to executive function, visuospatial, and language composites. Importantly, a TVPA by SE interaction (p = 0.015) suggested that adults with the poorest SE experienced the greatest benefit from physical activity in relation to global cognition. The other sleep metrics were unrelated to cognitive performance., Conclusion: These results suggest that TVPA and SE may synergistically benefit cognition in older adults., Competing Interests: Conflicts of Interest: Dr. Vadim Zipunnikov consults with Takeda Pharmaceuticals. The details of the contracts are disclosed through the Johns Hopkins University eDisclose system and have no direct or apparent relationship with the current paper. Adam Spira received payment for serving as a consultant for Merck, received honoraria from Springer Nature Switzerland AG for guest editing special issues of Current Sleep Medicine Reports, and is a paid consultant to Sequoia Neurovitality and BellSant, Inc. Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Background and Objectives: The aim of this study was to examine the diurnal links between average and changes in average levels of prospectively rated mood, sleep, energy, and stress as predictors of incident headache in a community-based sample., Methods: This observational study included structured clinical diagnostic assessment of both headache syndromes and mental disorders and electronic diaries that were administered 4 times per day for 2 weeks yielding a total of 4,974 assessments. The chief outcomes were incident morning (am) and later-day (pm) headaches. Generalized linear mixed-effects models were used to evaluate the average and lagged values of predictors including subjectively rated mood, anxiety, energy, stress, and sleep quality and objectively measured sleep duration and efficiency on incident am and pm headaches., Results: The sample included 477 participants (61% female), aged 7 through 84 years. After adjusting for demographic and clinical covariates and emotional states, incident am headache was associated with lower average (ß = -0.206*; confidence intervals: -0.397 to -0.017) and a decrease in average sleep quality on the prior day (ß = -0.172*; confidence interval: -0.305, -0.039). Average stress and changes in subjective energy levels on the prior day were associated with incident headaches but with different valence for am (decrease) (ß = -0.145* confidence interval: -0.286, -0.005) and pm (increase) (ß = 0.157*; confidence interval: 0.032, 0.281) headache. Mood and anxiety disorders were not significantly associated with incident headache after controlling for history of a diagnosis of migraine., Discussion: Both persistent and acute changes in arousal states manifest by subjective sleep quality and energy are salient precursors of incident headaches. Whereas poorer sleep quality and decreased energy on the prior day were associated with incident morning headache, an increase in energy and greater average stress were associated with headache onsets later in the day. Different patterns of predictors of morning and later-day incident headache highlight the role of circadian rhythms in the manifestations of headache. These findings may provide insight into the pathophysiologic processes underlying migraine and inform clinical intervention and prevention. Tracking these systems in real time with mobile technology provides a valuable ancillary tool to traditional clinical assessments.

Sleep and physical activity, two important health behaviors, are often studied independently using different accelerometer types and body locations. Understanding whether accelerometers designed for monitoring each behavior can provide similar sleep parameter estimates may help determine whether one device can be used to measure both behaviors. Three hundred and thirty one adults (70.7 ± 13.7 years) from the Baltimore Longitudinal Study of Aging wore the ActiGraph GT9X Link and the Actiwatch 2 simultaneously on the non-dominant wrist for 7.0 ± 1.6 nights. Total sleep time (TST), wake after sleep onset (WASO), sleep efficiency, number of wake bouts, mean wake bout length, and sleep fragmentation index (SFI) were extracted from ActiGraph using the Cole-Kripke algorithm and from Actiwatch using the software default algorithm. These parameters were compared using paired t-tests, Bland-Altman plots, and Deming regression models. Stratified analyses were performed by age, sex, and body mass index (BMI). Compared to the Actiwatch, the ActiGraph estimated comparable TST and sleep efficiency, but fewer wake bouts, longer WASO, longer wake bout length, and higher SFI (all p < .001). Both devices estimated similar 1-min and 1% differences between participants for TST and SFI (β = 0.99, 95% CI: 0.95, 1.03, and 0.91, 1.13, respectively), but not for other parameters. These differences varied by age, sex, and/or BMI. The ActiGraph and the Actiwatch provide comparable absolute and relative estimates of TST, but not other parameters. The discrepancies could result from device differences in movement collection and/or sleep scoring algorithms. Further comparison and calibration is required before these devices can be used interchangeably., (© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Greater physical activity and better sleep are associated with reduced risk of cognitive decline and dementia among older adults, but little is known about their combined associations with measures of brain function and neuropathology. This study investigated potential independent and interactive cross-sectional relationships between actigraphy-estimated total volume of physical activity (TVPA) and sleep patterns [i.e., total sleep time (TST), sleep efficiency (SE)] with resting-state functional magnetic resonance imaging (rs-fMRI) measures of large scale network connectivity and positron emission tomography (PET) measures of amyloid-β. Participants were 135 non-demented older adults from the BIOCARD study (116 cognitively normal and 19 with mild cognitive impairment; mean age = 70.0 years). Using multiple linear regression analyses, we assessed the association between TVPA, TST, and SE with connectivity within the default-mode, salience, and fronto-parietal control networks, and with network modularity, a measure of network segregation. Higher TVPA and SE were independently associated with greater network modularity, although the positive relationship of SE with modularity was only present in amyloid-negative individuals. Additionally, higher TVPA was associated with greater connectivity within the default-mode network, while greater SE was related to greater connectivity within the salience network. In contrast, longer TST was associated with lower network modularity, particularly among amyloid-positive individuals, suggesting a relationship between longer sleep duration and greater network disorganization. Physical activity and sleep measures were not associated with amyloid positivity. These data suggest that greater physical activity levels and more efficient sleep may promote more segregated and potentially resilient functional networks and increase functional connectivity within specific large-scale networks and that the relationship between sleep and functional networks connectivity may depend on amyloid status., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Alzheimer's disease (AD) is a leading cause of mortality and morbidity among aging populations worldwide. Despite arduous research efforts, treatment options for this devastating neurodegenerative disease are limited. Sleep disturbances, through their link to changes in neural excitability and impaired clearance of interstitial abnormal protein aggregates, are a key risk factor for the development of AD. Research also suggests that the neuroprotective effects of sleep are particularly active during slow wave sleep. Given the strong link between sleep disturbance and AD, targeting sleep in the prodromal stages of AD, such as in mild cognitive impairment (MCI), represents a promising avenue for slowing the onset of AD-related cognitive decline. In efforts to improve sleep in older individuals, several pharmacologic approaches have been employed, but many pose safety risks, concern for worsening cognitive function, and fail to effectively target slow wave sleep. Trazodone, a safe and widely used drug in the older adult population, has shown promise in inducing slow wave sleep in older adults, but requires more rigorous research to understand its effects on sleep and cognition in the prodromal stages of AD. In this review, we present the rationale and study design for our randomized, double-bind, placebo-controlled, crossover trial (NCT05282550) investigating the effects of trazodone on sleep and cognition in 100 older adults with amnestic MCI and sleep complaints.

Little is known about links of circadian rhythm alterations with neuropsychiatric symptoms and cognition in memory impaired older adults. Associations of actigraphic rest/activity rhythms (RAR) with depressive symptoms and cognition are examined using function-on-scalar regression (FOSR). Forty-four older adults with memory impairment (mean: 76.84 ± 8.15 years; 40.9% female) completed 6.37 ± 0.93 days of actigraphy, the Beck depression inventory-II (BDI-II), mini-mental state examination (MMSE) and consortium to establish a registry for Alzheimer's disease (CERAD) delayed word recall. FOSR models with BDI-II, MMSE, or CERAD as individual predictors adjusted for demographics (Models A1-A3) and all three predictors and demographics (Model B). In Model B, higher BDI-II scores are associated with greater activity from 12:00-11:50 a.m., 2:10-5:50 p.m., 8:40-9:40 p.m., 11:20-12:00 a.m., higher CERAD scores with greater activity from 9:20-10:00 p.m., and higher MMSE scores with greater activity from 5:50-10:50 a.m. and 12:40-5:00 p.m. Greater depressive symptomatology is associated with greater activity in midafternoon, evening, and overnight into midday; better delayed recall with greater late evening activity; and higher global cognitive performance with greater morning and afternoon activity (Model B). Time-of-day specific RAR alterations may affect mood and cognitive performance in this population., (© 2023 Wiley-VCH GmbH.)