Identifying Diurnal Variability of Brain Connectivity Patterns Using Graph Theory

Abstract

Significant differences exist in human brain functions affected by time of day and by people’s diurnal preferences (chronotypes) that are rarely considered in brain studies. In the current study, using network neuroscience and resting-state functional MRI (rs-fMRI) data, we examined the effect of both time of day and the individual’s chronotype on whole-brain network organization. In this regard, 62 participants (39 women; mean age: 23.97 ± 3.26 years; half morning- versus half evening-type) were scanned about 1 and 10 h after wake-up time for morning and evening sessions, respectively. We found evidence for a time-of-day effect on connectivity profiles but not for the effect of chronotype. Compared with the morning session, we found relatively higher small-worldness (an index that represents more efficient network organization) in the evening session, which suggests the dominance of sleep inertia over the circadian and homeostatic processes in the first hours after waking. Furthermore, local graph measures were changed, predominantly across the left hemisphere, in areas such as the precentral gyrus, putamen, inferior frontal gyrus (orbital part), inferior temporal gyrus, as well as the bilateral cerebellum. These findings show the variability of the functional neural network architecture during the day and improve our understanding of the role of time of day in resting-state functional networks.

Non-linear Functional Brain Co-activations in Short-Term Memory Distortion Tasks

“…Nevertheless, our result with diurnal variation of responses is consistent with the recent work of Tandoc et al (2021) , which revealed an increased generalization process that leads to increased false memory formation in the morning—an effect explained by lower inhibition at morning hours. Another study on resting-state data suggested the less efficient brain networks organization in the first hours after waking, which could be an effect of sleep inertia ( Farahani et al, 2021 ). The stronger effect for local processing, visible in Figure 5 , reads that in the evening the increased correlation of the whole brain’s activity with encoding stimulus predicts a lower proportion of “no” responses to a positive probe (more correct responses), and similarly, the increased correlation with retrieval stimulus predicts a lower proportion of “no” responses to a lure probe (more incorrect responses).…”

Non-linear functional brain co-activations in short-term memory distortion tasks

“…Nevertheless, our result with diurnal variation of responses is consistent with the recent work of Tandoc and colleagues (2021), which revealed an increased generalization process that leads to increased false memory formation in the morning – an effect explained by lower inhibition at morning hours. Another study on resting-state data suggested the less efficient brain networks organization in the first hours after waking, which could be an effect of sleep inertia (Farahani et al, 2021). The stronger effect for local processing, visible in Figure 4, reads that in the evening the increased correlation of the whole brain’s activity with encoding stimulus predicts a lower proportion of “no” responses to a positive probe (more correct responses), and similarly, the increased correlation with retrieval stimulus predicts a lower proportion of “no” responses to a lure probe (more incorrect responses).…”

Tracing Diurnal Differences in Brain Anatomy with Voxel-Based Morphometry – Associations with Sleep Characteristics

“…Nevertheless, a body of literature shows that other often neglected factors unrelated to the hardware, such as time-of-day (TOD) when the data was collected, may still strongly confound neuroimaging findings. Indeed, previous MRI studies have found widespread TOD-dependent differences in task-related brain activity, resting-state functional connectivity, as well as WM microstructure (Marek et al, 2010;Orban et al, 2020;Fafrowicz et al, 2019;Farahani et al, 2021;Thomas et al, 2018;Voldsbekk et al, 2020). Similarly, several works have reported TOD findings for global brain morphometric features, as well as VBM and SBM; nevertheless, inconsistencies are present in the literature.…”

“…Given the limited number of studies and the presence of inconsistencies in the literature, we aimed to investigate the TOD variation in structural brain data in an extended cohort (N=77) from earlier works showing widespread TOD variation in resting-state functional connectivity (Fafrowicz et al, 2019; Farahani et al, 2021). To the best of our knowledge, it is the largest dataset used to date in the context of the TOD effect in VBM and SBM.…”