On wakefulness fluctuations as a source of BOLD functional connectivity dynamics

Abstract

Human brain dynamics and functional connectivity fluctuate over a range of temporal scales in coordination with internal states and environmental demands. However, the neurobiological significance and consequences of functional connectivity dynamics during rest have not yet been established. We show that the coarse-grained clustering of whole-brain dynamic connectivity measured with magnetic resonance imaging reveals discrete patterns (dynamic connectivity states) associated with wakefulness and sleep. We validate this using EEG in healthy subjects and patients with narcolepsy and by matching our results with previous findings in a large collaborative database. We also show that drowsiness may account for previous reports of metastable connectivity states associated with different levels of functional integration. This implies that future studies of transient functional connectivity must independently monitor wakefulness. We conclude that a possible neurobiological significance of dynamic connectivity states, computed at a sufficiently coarse temporal scale, is that of fluctuations in wakefulness.

Functional brain network reconfiguration during learning in a dynamic environment

“…We and others have previously shown that surprise and uncertainty induce changes in arousal, as indexed by pupil responses 2,5,35 . The increases in integration between the fronto-parietal and other systems that we observed in this study in response to surprise and uncertainty are consistent with previous studies of the relationship between arousal (e.g., wake/sleep, heart rate and pupil size) and the dynamics of functional connectivity in large-scale brain networks 33,36,37,38,39,40 . Specifically, high arousal states are associated with changes in connectivity in regions in the fronto-parietal, dorsal attention, ventral attention, salience and default mode networks 36,39 , and particularly to increases in integration in the fronto-parietal and default mode networks 33 .…”

Cognitive vulnerability to sleep deprivation is robustly associated with two dynamic connectivity states

“…There is now some evidence that DCSs contain information that is of behavioural significance. For instance, on a coarse level, certain DCS have been associated with wakefulness and sleep (Haimovici et al 2017, Damaraju et al 2018, motivating a more detailed search for states related to other cognitive domains.…”

Dynamic functional connectivity states characterize NREM sleep and wakefulness

“…It has also been reported that clustering or hierarchical approaches can reveal dynamic connectivity states that could be linked with ongoing cognitive fluctuations and functional connectivity changes when people shift between sleep and wakefulness (Laumann et al, 2017). Haimovici and colleagues demonstrated that coarse dynamic connectivity states matched wakefulness and sleep stages by setting the number of clusters equal to the number of stages in the human NREM sleep cycle (Haimovici et al, 2017). In our study, we set a varying k-value (k ranges from 2 to 8) and found similar dynamic connectivity patterns that characterized wakefulness and NREM sleep across different k-values during clustering.…”

“…The association of DFC with neural oscillations, such as alpha and beta power, quantified using simultaneous electroencephalography (EEG) (Chang, Liu, et al, 2013;Laufs et al, 2003;Tagliazucchi, von Wegner, Morzelewski, Brodbeck, & Laufs, 2012) supports a neurobiological origin of DFC during the resting state. One recent study showed that DFC states could capture variability across brain states during resting wakefulness to stages of sleep (Haimovici, Tagliazucchi, Balenzuela, & Laufs, 2017). One recent study showed that DFC states could capture variability across brain states during resting wakefulness to stages of sleep (Haimovici, Tagliazucchi, Balenzuela, & Laufs, 2017).…”

“…Similar to the transient quasi-stable patterns detected in EEG data (microstates), DFC can be clustered into recurring patterns, that is, DFC states. One recent study showed that DFC states could capture variability across brain states during resting wakefulness to stages of sleep (Haimovici, Tagliazucchi, Balenzuela, & Laufs, 2017).…”