Biology subjects

Loock, A.-S.

Publications and source records attributed to Loock, A.-S..

3 recordsLinked to original sources

bioRxiv2026

A single day of natural daylight exposure and physical activity does not conclusively change circadian phase: A Bayesian crossover experiment

Among the environmental signals that shape human physiology, the daily light-dark cycle is the primary zeitgeber of the human circadian system. Physical activity may provide an additional non-photic time cue and frequently co-occurs with daylight in everyday life. However, their independent and combined effects on circadian phase have rarely been disentangled under naturalistic daylight conditions. In a counterbalanced mixed-design experiment, 41 healthy adults (24 women; mean age = 23.7 years, SD = 4.3) participated in up to three 40-h visits on fixed individual sleep-wake schedules. Each visit comprised an 8-h exposure beginning 1.5 h after wake to natural daylight, daylight attenuated by amber-tinted glasses, or indoor electric light (within subjects; mean photopic illuminances: 1196, 460, and 75 lx), with otherwise dim-light conditions. Participants hiked for approximately 4 h or remained sedentary (between subjects; activity indexed by median heart rate reserve [HRR]; group means: 32.7% and 2.7%). Bayesian hierarchical models used individual photopic illuminance (ActTrust 2) and median HRR to predict change in dim-light melatonin onset (DLMO; primary outcome) and exploratory outcomes (daytime and evening sleepiness, mood, and wellbeing, daytime perceived exertion, and evening psychomotor vigilance). Per standard-deviation increase in log-transformed illuminance and median HRR, estimated DLMO changes were -4.22 min (95% HDI [-10.93, 2.22]; BF = 0.70) and -6.48 min (95% HDI [-13.79, 1.27], BF = 1.56), respectively. Evidence remained inconclusive for both predictors and their interaction. Exploratory findings were largely inconclusive, practically negligible, or favoured the absence of effects. The circadian effects of a single day of natural daylight exposure, with or without physical activity, therefore remain unclear. Resolving this question may require larger samples and brighter, repeated, or habitual exposure timed to phases of greater circadian light sensitivity.

neuroscience↗

bioRxiv2026

Associations between habitual light exposure-related behaviors and sleep timing and sleep complaints in an international community sample

Sleep is essential for health and light is an important environmental signal influencing its timing, quality, and regulation. Retinal light exposure reflects the interplay between environmental illumination and behavioral choices, yet it remains unclear which habitual light exposure-related behaviors meaningfully impact sleep outcomes. In this preregistered analysis, we examined associations between these behaviors, sleep timing, and sleep complaints in a large, international community sample (N = 774, Mage = 32.6 {+/-} 14.6 years). Participants completed the Light Exposure Behavior Assessment (LEBA), with four behavioral domains included in the analyses. Sleep timing, sleep disturbances and sleep-related daytime impairment were measured using established questionnaires. Bayesian analyses indicated that time spent outdoors and device use in bed were most strongly associated with sleep outcomes. Greater time outdoors was linked to earlier sleep timing and fewer sleep complaints, whereas more frequent device use in bed was associated with greater sleep disturbance and daytime impairment. Morning and daytime lighting practices and evening light control showed no conclusive evidence. Together, these findings highlight the relevance of everyday light exposure-related behaviors for sleep and support behavioral approaches to promoting healthy sleep in real-world contexts.

neuroscience↗

bioRxiv2021

Validation of the Munich Actimetry Sleep Detection Algorithm for estimating sleep-wake patterns from activity recordings

Periods of sleep and wakefulness can be estimated from wrist-locomotor activity recordings via algorithms that identify periods of relative activity and inactivity. Here, we evaluated the performance of our Munich Actimetry Sleep Detection Algorithm (MASDA). MASDA uses a moving 24-hour-threshold and correlation procedure estimating relatively consolidated periods of sleep and wake. MASDA was validated against sleep logs and polysomnography. Sleep-log validation was performed on 2 field samples collected over 54 and 34 days (median) in 34 adolescents and 28 young adults. Polysomnographic validation was performed on a clinical sample of 23 individuals undergoing 1 night of polysomnography. Epoch-by-epoch analyses were conducted and comparisons of sleep measures via Bland-Altman plots and correlations. Compared with sleep logs, MASDA classified sleep with a median sensitivity of 80% (IQR = 75-86%) and specificity of 91% (87-92%). Mean onset and offset times were highly correlated (r = 0.86-0.91). Compared with polysomnography, MASDA reached a median sensitivity of 92% (85-100%), but low specificity of 33% (10-98%), owing to the low frequency of wake episodes in the nighttime polysomnographic recordings. MASDA overestimated sleep onset (~21 min) and underestimated wake after sleep onset (~26 min), while not performing systematically different from polysomnography in other sleep parameters. These results demonstrate the validity of MASDA to faithfully estimate sleep-wake patterns in field studies. With its good performance across day- and nighttime, it enables analyses of sleep-wake patterns in long recordings performed to assess circadian and sleep regularity and is therefore an excellent objective alternative to sleep logs in field settings.

neuroscience↗