Journal
NEUROPSYCHOPHARMACOLOGY
Volume 46, Issue 1, Pages 197-208Publisher
SPRINGERNATURE
DOI: 10.1038/s41386-020-00830-5
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Funding
- Intramural Research Program of the National Institute of Mental Health [ZIA MH002954-02]
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Mobile technologies have provided valuable insights into the circadian system, sleep patterns, and motor activity in individuals with bipolar disorder (BD). The use of real-time monitoring has revealed diverse sleep disturbances, variability in motor activity, and evening orientation among BD patients. Future research should focus on identifying common biological pathways that influence the interrelations between sleep, physical activity, and circadian patterns. Collaborative efforts in applying multimodal sensor technology will enhance our understanding of the mechanisms and dynamics of BD.
Rapidly accumulating data from mobile assessments are facilitating our ability to track patterns of emotions, behaviors, biologic rhythms, and their contextual influences in real time. These approaches have been widely applied to study the core features, traits, changes in states, and the impact of treatments in bipolar disorder (BD). This paper reviews recent evidence on the application of both passive and active mobile technologies to gain insight into the role of the circadian system and patterns of sleep and motor activity in people with BD. Findings of more than two dozen studies converge in demonstrating a broad range of sleep disturbances, particularly longer duration and variability of sleep patterns, lower average and greater variability of motor activity, and a shift to later peak activity and sleep midpoint, indicative of greater evening orientation among people with BD. The strong associations across the domains tapped by real-time monitoring suggest that future research should shift focus on sleep, physical/motor activity, or circadian patterns to identify common biologic pathways that influence their interrelations. The development of novel data-driven functional analytic tools has enabled the derivation of individualized multilevel dynamic representations of rhythms of multiple homeostatic regulatory systems. These multimodal tools can inform clinical research through identifying heterogeneity of the manifestations of BD and provide more objective indices of treatment response in real-world settings. Collaborative efforts with common protocols for the application of multimodal sensor technology will facilitate our ability to gain deeper insight into mechanisms and multisystem dynamics, as well as environmental, physiologic, and genetic correlates of BD.
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