1.	Chen, I. Y., Radom-Aizik, S., Stehli, A., Palmer, J. R., Lui, K. K., Dave, A., Chappel-Farley, M. G., Vinces, K. G., Gealer, D., Lim, A., Mander, B. A., Benca, R. M., Neikrug, A. B. (2024). Cardiorespiratory fitness and circadian rhythms in adolescents: A pilot study. Journal of Applied Physiology (Bethesda, Md.: 1985), 136(2), 372-384. https://doi.org/10.1152/japplphysiol.00291.2023 
2.	Desai, S.*, Chen, I. Y.*, Hom, C., Doran, E., Nguyen, D. D., Benca, R. M., Lott, I., Mander, B. A. (2024). Insomnia symptoms are associated with dementia and functional deterioration in adults with Down syndrome at High Risk for Alzheimer’s Disease. Journal of Alzheimer’s Disease: JAD, 100(2), 613-629. http://doi.org/10.3233/JAD-220750 
*Authors contributed equally to this work. 
3.	Neikrug, A. B., Mander, B. A., Radom-Aizik, S., Chen, I. Y., Stehli, A., Lui, K. K., Chappel-Farley, M. G., Abhishek, D., Benca, R. M. (2021). Aerobic fitness and the sleeping brain of adolescents – A pilot study. SLEEP Advances: A Journal of the Sleep Research Society, 2(1), zpab005. http://doi.org/10.1093/sleepadvances/zpab005  
4.	Neikrug, A. B., Chen, I. Y., Palmer, J. R., McCurry, S. M., Von Korff, M., Perlis, M., Vitiello, M. V. (2020). Characterizing behavioral activity rhythms in older adults using actigraphy. Sensors (Basel, Switzerland), 20(2), 549. http://doi.org/10/3390/s20020549
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              Introduction: Adolescence is marked by biologically driven shifts in sleep timing, reduced duration, and increased circadian variability—factors linked to mood, cognitive, and metabolic outcomes. Actigraphy provides a non-invasive, objective, and scalable method for assessing these patterns in naturalistic settings. This presentation focuses on the application of actigraphy, highlighting methodological approaches for analyzing longitudinal data from the Interacting Mechanisms of SLeep and Endurance Exercise in Pediatrics (iSLEEP) study, an ancillary project of the UC Irvine pediatric arm of the Molecular Transducers of Physical Activity Consortium (MoTrPAC). We discuss how these methods support robust characterization of sleep timing, regularity, and circadian rhythmicity across a diverse pediatric cohort, while accounting for contextual influences such as seasonality and school schedules, which are essential for ensuring data quality and interpretability. 
Methods: Seventy-seven healthy children and adolescents (Mage=15.0±2.3 yrs, 62.3% females) who completed the iSLEEP Pediatric MoTrPAC ancillary study underwent 7–14 days of actigraphy (Actiwatch), alongside daily sleep diaries. Assessed sleep parameters included sleep onset and offset times, midsleep time, total sleep time (TST), and sleep efficiency (SE). Circadian rhythm variables were estimated from log-transformed, minute-by-minute wrist activity counts using two methods: a cosinor model and a graphical approach based on Shape Language Modeling (SLM). The cosinor model yielded traditional rhythm parameters, including the midline estimated statistic of rhythm (MESOR), amplitude, and acrophase, while the SLM approach provided UP and DOWN times and their corresponding slopes, capturing habitual patterns and transitions in daily activity rhythms.  
Results: Participants exhibited substantial interindividual variability in sleep timing and duration, with later midsleep times and reduced TST observed in older adolescents. Circadian metrics derived from both cosinor and SLM approaches reflected expected developmental and contextual patterns. Significant seasonal and contextual variability was observed in sleep offset, midsleep, and UP times, with later timing during summer and no-school periods compared to spring and school periods (p’s < 0.05). In contrast, no significant variations were found in sleep onset time, TST, SE, or DOWN time and slope. Consistent findings were observed across subjective and objective methods, further supporting the reliability of the data. 
Conclusion: The iSLEEP study demonstrates the utility of actigraphy in characterizing detailed, ecologically valid sleep and circadian metrics in healthy children and adolescents. The integration of multiple modeling approaches, combined with contextual data, provides a more nuanced understanding of sleep and circadian patterns across adolescence. These findings highlight the need for context-specific adjustments in pediatric sleep and circadian research. Actigraphy, particularly when integrated into large-scale efforts like MoTrPAC, offers a scalable approach to advancing the study of sleep-circadian dynamics. These methods may inform future pediatric research aiming to link behavioral rhythms with health outcomes.
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