Temporal organisation of the brain's intrinsic motor network: The relationship with circadian phenotype and motor performance

Functional Connectivity Between Default Mode and Ventral Attention Networks Mediates the Effects of Chronotype on Daily Physical Activity

Daily physical activity (dPA) is closely related to circadian rhythm and chronotype. The functional connectivity (FC) within or between the default mode (DMN) and ventral attention network (vAN) were associated with dPA and chronotype. DMN-vAN FC was investigated for its role in chronotype and dPA. 153 participants completed the reduced version of the Morningness-Eveningness Questionnaire (rMEQ), dPA was measured via actigraphy (5-day), and then resting-state fMRI scans were performed. rMEQ scores and steps recorded by the actigraphic devices (with each hour as the time window to calculate steps for five consecutive days per hour, subsequently yielding the maximum number of steps and its corresponding time, ie, SM and SMT) represent chronotype and dPA respectively. The results found that the rMEQ scores were significantly negatively correlated with SMT. The positive correlation between the rMEQ scores and the DMN-vAN FC was significant. There were also significant positive correlations between SMT and DMN-vAN FC. Further analysis revealed that DMN-vAN mediates the relationship between chronotype and SMT. The FC of DMN-vAN may be the underlying neural mechanism through which chronotype influences dPA. These findings could support the development of reasonable activity schedules or specific intervention programs to improve physical health.

The correlation between upper body grip strength and resting-state EEG network

Current research in the field of neuroscience primarily focuses on the analysis of electroencephalogram (EEG) activities associated with movement within the central nervous system. However, there is a dearth of studies investigating the impact of prolonged individual strength training on the resting state of the brain. Therefore, it is crucial to examine the correlation between upper body grip strength and resting-state EEG networks. In this study, coherence analysis was utilized to construct resting-state EEG networks using the available datasets. A multiple linear regression model was established to examine the correlation between the brain network properties of individuals and their maximum voluntary contraction (MVC) during gripping tasks. The model was used to predict individual MVC. The beta and gamma frequency bands showed significant correlation between RSN connectivity and MVC (p < 0.05), particularly in left hemisphere frontoparietal and fronto-occipital connectivity. RSN properties were consistently correlated with MVC in both bands, with correlation coefficients greater than 0.60 (p < 0.01). Additionally, predicted MVC positively correlated with actual MVC, with a coefficient of 0.70 and root mean square error of 5.67 (p < 0.01). The results show that the resting-state EEG network is closely related to upper body grip strength, which can indirectly reflect an individual's muscle strength through the resting brain network.

Classification of human chronotype based on fMRI network-based statistics

Chronotype-the relationship between the internal circadian physiology of an individual and the external 24-h light-dark cycle-is increasingly implicated in mental health and cognition. Individuals presenting with a late chronotype have an increased likelihood of developing depression, and can display reduced cognitive performance during the societal 9-5 day. However, the interplay between physiological rhythms and the brain networks that underpin cognition and mental health is not well-understood. To address this issue, we use rs-fMRI collected from 16 people with an early chronotype and 22 people with a late chronotype over three scanning sessions. We develop a classification framework utilizing the Network Based-Statistic methodology, to understand if differentiable information about chronotype is embedded in functional brain networks and how this changes throughout the day. We find evidence of subnetworks throughout the day that differ between extreme chronotypes such that high accuracy can occur, describe rigorous threshold criteria for achieving 97.3% accuracy in the Evening and investigate how the same conditions hinder accuracy for other scanning sessions. Revealing differences in functional brain networks based on extreme chronotype suggests future avenues of research that may ultimately better characterize the relationship between internal physiology, external perturbations, brain networks, and disease.

Distinct neural responses of morningness and eveningness chronotype to homeostatic sleep pressure revealed by resting-state functional magnetic resonance imaging

Background

Chronotype is an appropriate variable to investigate sleep homeostatic and circadian rhythm. Based on functional MRI, the resting‐state functional connectivity (rsFC) of insula‐angular decrease with the increase in homeostatic sleep pressure (HSP). However, the distinct neural response of different chronotype remained to be clarified. Therefore, we investigated how HSP influenced insular‐angular neural interaction of different chronotype.

Methods

64 morningness‐chronotype (MCPs) and 128 eveningness‐chronotype participants (ECPs) received resting‐state functional MRI (rsfMRI) scan. HSP was divided into three levels (Low, Medium, and High) based on the elapsed time awake. Insular‐angular rsFC was calculated for MCPs and ECPs on each HSP.

Results

As the levels of HSP increased, the negative rsFC between right insular and bilateral angular increased in MCPs while decreased in ECPs. Specifically, ECPs compared with MCPs showed lower rsFC at medium levels of HSP, but higher rsFC at high levels of HSP. In addition, ECPs compared with MCPs exhibited lower rsFC between right insular and right angular at low levels of HSP.

Conclusion

The distinct modes of rsFC was found in different chronotype in response to HSP. The results provided the foundation and evidence for investigating the processes of circadian rhythm and sleep homeostatic.

Time-of-day effect on motor coordination in youth

The evaluation of motor coordination is important for diagnosing children and adolescents with motor impairments. However, motor coordination may be affected by time-of-day effects, and thus, the intra-day variation could subsequently influence the assessment accuracy of the standardized test used in the diagnostic process. To the best of our knowledge, no study has been conducted to examine this possibility. Therefore, the purpose of this study was to investigate the time-of-day effect on motor coordination. A convenience sample of 25 youth (17-21 years) were recruited from local high schools and a local university. The Bruininks-Oseretsky Test of Motor Proficiency - Second Edition (Short Form) was administered at three different times (morning, noon, and afternoon) over three days to explore the potential time-of-day effect on motor coordination. The starting time of the test on the first day was counterbalanced. Other factors that could potentially impact motor performance were also measured, including physical activity, chronotype, and time-since-awakening. A statistically significant main effect of time-of-day was found on overall motor coordination (p< .01) and the domain of Manual Coordination (p< .01). The time-of-day effect on the domain of Strength & Agility (p = .055) was just above the threshold of statistical significance. Further analysis showed that overall motor coordination was better at noon (p< .01) and in the afternoon (p= .052) than in the morning, whereas manual coordination was the worst in the morning (p's < .01). Strength and agility were also significantly better at noon than in the morning (p< .01). In addition, poor motor coordination in the morning was also related to longer time-since-awakening. Overall, this study identifies the time-of-day effect on motor coordination that could lead to the inconsistent classification of motor performance. Therefore, in order to avoid the potential misclassification of motor coordination, health professionals should take into account the time-of-day effect on motor coordination and the possible impact of time-since-awakening while administering the assessment in the morning.