Abstract
Abstract Introduction Resting-state functional connectivity is coherent brain activity in a task-free state that strongly correlates to task-evoked sensory, motor, and higher-order cognitive systems. Certain networks show decreased functional connectivity with aging. Aging is associated with changes in circadian rhythms and sleep-wake cycles. Limited research has been conducted on how circadian activity and sleep are related to markers of functional brain aging. The purpose of this study was to explore whether rest-activity patterns and shorter sleep duration are related to functional connectivity of specific resting-state networks in older adults. Methods A total of 124 cognitively normal participants (mean age (SD) = 67.2 (5.7), 42% men) underwent 3.0 T MRI and week-long wrist actigraphy protocols. Rest-activity pattern was analyzed using an extended cosine model calculating acrophase (time of peak activity) and pseudo-F statistics of goodness-of-fit (a measure of overall rhythmicity). We used resting-state fMRI scans to measure functional connectivity in association and sensory networks as defined by the Schaefer 17 network functional atlas. Multiple linear regression analysis was used to investigate how rest-activity pattern parameters and sleep duration are associated with resting-state functional connectivity, adjusting for age, sex, and sleep apnea. Results We found that the average acrophase was 2:30 PM (SD = 54 min), and delayed acrophase (average vs. delayed [+1SD]) was associated with lower functional connectivity of the right-lateralized default mode network A (p=0.02), and higher pseudo-F statistics was associated with higher functional connectivity in networks including left dorsal attention B (p=0.001), right somatomotor A (p = 0.05), and somatomotor B (both p=0.02). Longer sleep duration was associated with higher right executive control B (p=0.03). Conclusion The overall rhythmicity of diurnal rest-activity patterns and longer sleep duration are associated with some resting-state functional networks. Further investigation is needed to understand the mechanisms between circadian rhythm and brain function. Support National Institute of Health, U of Iowa Aging Mind Brain Initiative, Center on Aging
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