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Mao T, Guo B, Quan P, Deng Y, Chai Y, Xu J, Jiang C, Zhang Q, Lu Y, Goel N, Basner M, Dinges DF, Rao H. Morning resting hypothalamus-dorsal striatum connectivity predicts individual differences in diurnal sleepiness accumulation. Neuroimage 2024; 299:120833. [PMID: 39233125 DOI: 10.1016/j.neuroimage.2024.120833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2024] [Revised: 08/26/2024] [Accepted: 09/02/2024] [Indexed: 09/06/2024] Open
Abstract
While the significance of obtaining restful sleep at night and maintaining daytime alertness is well recognized for human performance and overall well-being, substantial variations exist in the development of sleepiness during diurnal waking periods. Despite the established roles of the hypothalamus and striatum in sleep-wake regulation, the specific contributions of this neural circuit in regulating individual sleep homeostasis remain elusive. This study utilized resting-state functional magnetic resonance imaging (fMRI) and mathematical modeling to investigate the role of hypothalamus-striatum connectivity in subjective sleepiness variation in a cohort of 71 healthy adults under strictly controlled in-laboratory conditions. Mathematical modeling results revealed remarkable individual differences in subjective sleepiness accumulation patterns measured by the Karolinska Sleepiness Scale (KSS). Brain imaging data demonstrated that morning hypothalamic connectivity to the dorsal striatum significantly predicts the individual accumulation of subjective sleepiness from morning to evening, while no such correlation was observed for the hypothalamus-ventral striatum connectivity. These findings underscore the distinct roles of hypothalamic connectivity to the dorsal and ventral striatum in individual sleep homeostasis, suggesting that hypothalamus-dorsal striatum circuit may be a promising target for interventions mitigating excessive sleepiness and promoting alertness.
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Affiliation(s)
- Tianxin Mao
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Bowen Guo
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Peng Quan
- Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Research Center for Quality of Life and Applied Psychology, Guangdong Medical University, Dongguan, China
| | - Yao Deng
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China; Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Ya Chai
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China; Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Jing Xu
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China; Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Caihong Jiang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Qingyun Zhang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Yingjie Lu
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Namni Goel
- Biological Rhythms Research Laboratory, Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Mathias Basner
- Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - David F Dinges
- Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Hengyi Rao
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China; Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
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McCauley ME, McCauley P, Kalachev LV, Riedy SM, Banks S, Ecker AJ, Dinges DF, Van Dongen HPA. Biomathematical modeling of fatigue due to sleep inertia. J Theor Biol 2024; 590:111851. [PMID: 38782198 PMCID: PMC11179995 DOI: 10.1016/j.jtbi.2024.111851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Revised: 04/13/2024] [Accepted: 05/12/2024] [Indexed: 05/25/2024]
Abstract
Biomathematical models of fatigue capture the physiology of sleep/wake regulation and circadian rhythmicity to predict changes in neurobehavioral functioning over time. We used a biomathematical model of fatigue linked to the adenosinergic neuromodulator/receptor system in the brain as a framework to predict sleep inertia, that is, the transient neurobehavioral impairment experienced immediately after awakening. Based on evidence of an adenosinergic basis for sleep inertia, we expanded the biomathematical model with novel differential equations to predict the propensity for sleep inertia during sleep and its manifestation after awakening. Using datasets from large laboratory studies of sleep loss and circadian misalignment, we calibrated the model by fitting just two new parameters and then validated the model's predictions against independent data. The expanded model was found to predict the magnitude and time course of sleep inertia with generally high accuracy. Analysis of the model's dynamics revealed a bifurcation in the predicted manifestation of sleep inertia in sustained sleep restriction paradigms, which reflects the observed escalation of the magnitude of sleep inertia in scenarios with sleep restriction to less than ∼ 4 h per day. Another emergent property of the model involves a rapid increase in the predicted propensity for sleep inertia in the early part of sleep followed by a gradual decline in the later part of the sleep period, which matches what would be expected based on the adenosinergic regulation of non-rapid eye movement (NREM) sleep and its known influence on sleep inertia. These dynamic behaviors provide confidence in the validity of our approach and underscore the predictive potential of the model. The expanded model provides a useful tool for predicting sleep inertia and managing impairment in 24/7 settings where people may need to perform critical tasks immediately after awakening, such as on-demand operations in safety and security, emergency response, and health care.
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Affiliation(s)
- Mark E McCauley
- Sleep and Performance Research Center, Washington State University, 412 E. Spokane Falls Blvd., Spokane, WA 99202-2131, USA; Department of Translational Medicine and Physiology, Washington State University Health Sciences Spokane, 412 E. Spokane Falls Blvd., Spokane, WA 99202, USA.
| | - Peter McCauley
- Sleep and Performance Research Center, Washington State University, 412 E. Spokane Falls Blvd., Spokane, WA 99202-2131, USA
| | - Leonid V Kalachev
- Department of Mathematical Sciences, University of Montana, Mathematics Building, Missoula, MT 59812, USA.
| | - Samantha M Riedy
- Sleep and Performance Research Center, Washington State University, 412 E. Spokane Falls Blvd., Spokane, WA 99202-2131, USA
| | - Siobhan Banks
- Behaviour-Brain-Body Research Centre, University of South Australia, Adelaide, SA 5048, Australia.
| | - Adrian J Ecker
- Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, University of Pennsylvania Perelman School of Medicine, 1013 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104, USA.
| | - David F Dinges
- Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, University of Pennsylvania Perelman School of Medicine, 1013 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104, USA.
| | - Hans P A Van Dongen
- Sleep and Performance Research Center, Washington State University, 412 E. Spokane Falls Blvd., Spokane, WA 99202-2131, USA; Department of Translational Medicine and Physiology, Washington State University Health Sciences Spokane, 412 E. Spokane Falls Blvd., Spokane, WA 99202, USA.
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Easton DF, Gupta CC, Vincent GE, Ferguson SA. Move the night way: how can physical activity facilitate adaptation to shift work? Commun Biol 2024; 7:259. [PMID: 38431743 PMCID: PMC10908783 DOI: 10.1038/s42003-024-05962-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 02/22/2024] [Indexed: 03/05/2024] Open
Abstract
Shift work, involving night work, leads to impaired sleep, cognition, health and wellbeing, and an increased risk of occupational incidents. Current countermeasures include circadian adaptation to phase shift circadian biomarkers. However, evidence of real-world circadian adaptation is found primarily in occupations where light exposure is readily controlled. Despite this, non-photic adaptation to shift work remains under researched. Other markers of shift work adaptation exist (e.g., improvements in cognition and wellbeing outcomes) but are relatively unexplored. Timeframes for shift work adaptation involve changes which occur over a block of shifts, or over a shift working career. We propose an additional shift work adaptation timeframe exists which encompasses acute within shift changes in markers of adaptation. We also propose that physical activity might be an accessible and cost-effective countermeasure that could influence multiple markers of adaptation across three timeframes (Within Shift, Within Block, Within Work-span). Finally, practical considerations for shift workers, shift work industries and future research are identified.
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Affiliation(s)
- Dayna F Easton
- Appleton Institute, School of Health, Medical and Applied Sciences, Central Queensland University, Wayville, SA, Australia.
| | - Charlotte C Gupta
- Appleton Institute, School of Health, Medical and Applied Sciences, Central Queensland University, Wayville, SA, Australia
| | - Grace E Vincent
- Appleton Institute, School of Health, Medical and Applied Sciences, Central Queensland University, Wayville, SA, Australia
| | - Sally A Ferguson
- Appleton Institute, Central Queensland University, Wayville, SA, Australia
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Dijk DJ, Skeldon AC. On the need for mathematical models for integration of sleep, circadian, and environmental science for sleep health policies. Sleep Health 2024; 10:S22-S24. [PMID: 38290876 DOI: 10.1016/j.sleh.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Affiliation(s)
- Derk-Jan Dijk
- Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK; UK Dementia Research Institute, Care Research and Technology Centre at Imperial College London, London, UK and the University of Surrey, Guildford, UK.
| | - Anne C Skeldon
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College London, London, UK and the University of Surrey, Guildford, UK; School of Mathematics and Physics, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, UK
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Demareva V, Zayceva I, Viakhireva V, Zhukova M, Selezneva E, Tikhomirova E. Home-Based Dynamics of Sleepiness-Related Conditions Starting at Biological Evening and Later (Beyond Working). INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6641. [PMID: 37681781 PMCID: PMC10487394 DOI: 10.3390/ijerph20176641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Revised: 08/17/2023] [Accepted: 08/22/2023] [Indexed: 09/09/2023]
Abstract
Shift work requires round-the-clock readiness to perform professional duties, and the workers' performance highly depends on their sleepiness level, which can be underestimated during a shift. Various factors, including the time of day, can influence sleepiness in shift workers. The objective of this study was to explore the dynamics of sleepiness-related conditions assessed through heart rate variability analysis, starting from the biological evening and continuing in vivo (at home), without the need for artificial alertness support. The participants solely performed regular evening household duties. A total of 32 recordings were collected from the Subjective Sleepiness Dynamics Dataset for analysis. At 8:00 p.m. and every 30 min thereafter, the participants completed cyclic sleepiness scales (the KSS and the SSS) until the time they went to bed, while their heart rate was recorded. The results of the study indicated that during the biological evening, high sleepiness is associated with a 'stressed' condition characterized by higher sympathetic activation. Later on, it is associated with a 'drowsy' condition characterized by higher parasympathetic activation and a decline in heart rate variability. Our findings provide evidence that the type of condition experienced during high sleepiness depends on the biological time. This should be taken into account when managing work regimes in shift work and developing alertness detectors.
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Affiliation(s)
- Valeriia Demareva
- Faculty of Social Sciences, Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia
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