2016
DOI: 10.1073/pnas.1523980113
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Spontaneous eyelid closures link vigilance fluctuation with fMRI dynamic connectivity states

Abstract: Fluctuations in resting-state functional connectivity occur but their behavioral significance remains unclear, largely because correlating behavioral state with dynamic functional connectivity states (DCS) engages probes that disrupt the very behavioral state we seek to observe. Observing spontaneous eyelid closures following sleep deprivation permits nonintrusive arousal monitoring. During periods of low arousal dominated by eyelid closures, sliding-window correlation analysis uncovered a DCS associated with … Show more

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Cited by 193 publications
(205 citation statements)
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“…Thus, the relative portion of a resting-state scan that is spent engaging in cognitive processes that are accompanied by negative interactions between the two networks, compared with that spent in processes that do not result in anti-correlations may be an additional factor (beyond preprocessing and seed location) in determining whether salient anti-correlation can be observed across a single scan session. Moreover, since the antagonistic relationship between DMN and TPN weakens under increased drowsiness, as evidenced by research on sleep deprivation and vigilance fluctuation (Chang et al, 2013a; De Havas et al, 2012; Wang et al, 2016; Yeo et al, 2015), the overall levels of arousal across scans and subjects ought to be considered as well. As such, mechanisms underlying inconsistent reports on DMN anti-correlations are not yet conclusive – subjects’ on-going cognitive process, arousal levels, as well as the de-noising steps in data analyses, all affect DMN anti-correlations, but we can conclude that different seed locations contribute at least partly to those observations.…”
Section: Discussionmentioning
confidence: 99%
“…Thus, the relative portion of a resting-state scan that is spent engaging in cognitive processes that are accompanied by negative interactions between the two networks, compared with that spent in processes that do not result in anti-correlations may be an additional factor (beyond preprocessing and seed location) in determining whether salient anti-correlation can be observed across a single scan session. Moreover, since the antagonistic relationship between DMN and TPN weakens under increased drowsiness, as evidenced by research on sleep deprivation and vigilance fluctuation (Chang et al, 2013a; De Havas et al, 2012; Wang et al, 2016; Yeo et al, 2015), the overall levels of arousal across scans and subjects ought to be considered as well. As such, mechanisms underlying inconsistent reports on DMN anti-correlations are not yet conclusive – subjects’ on-going cognitive process, arousal levels, as well as the de-noising steps in data analyses, all affect DMN anti-correlations, but we can conclude that different seed locations contribute at least partly to those observations.…”
Section: Discussionmentioning
confidence: 99%
“…Although analysis methods in this relatively new research area are still evolving, many studies use some type of correction for global signal effects (e.g. either GSR or global signal subtraction for ICA-based approches) (Laumann et al, 2016; Shine et al, 2016; Wang et al, 2016), although there are exceptions (Gonzalez-Castillo et al, 2015; Demirtaş et al, 2016). In a study that did not use GSR, Demirtaş et al (2016) found that the relative magnitude of the global signal (e.g.…”
Section: The Role Of the Global Signal In Fmri Analysismentioning
confidence: 99%
“…Going forward, monitoring of the relevant behavior(s) (Fig. 8 and (Guipponi et al, 2014; Chang et al, 2016; McGinley et al, 2015; O’Connor et al, 2010; Yang et al, 2016)) in animals is likely to play an important role in animal fMRI experiments, just as it has in human experiments (Richlan et al, 2014; Wang et al, 2016). The development of new techniques for analyzing behavioral data in other paradigms have undergone enormous advances in recent years (Gomez-Marin et al 2014), and it is likely that some of these approaches can be applied to the studies of more subtle behaviors.…”
Section: Introductionmentioning
confidence: 99%