Differences in the resting-state fMRI global signal amplitude between the eyes open and eyes closed states are related to changes in EEG vigilance

Wong, Chi-Wah; DeYoung, Pamela; Liu, Thomas T.

doi:10.1016/j.neuroimage.2015.08.053

Cited by 115 publications

(109 citation statements)

References 60 publications

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“…The utility of using SEC in the context of fMRI recordings was recently explored in two studies. The first study documented differences in resting-state fMRI global signal amplitude between eyes-open and eyes-closed states to EEG vigilance (50), and the second study documented fMRI BOLD signal fluctuations to eye-closure and invasive electrophysiological recordings in primates (51). Although relevant and buttressing the claims made here, these studies did not specifically address the triune relationship between fMRI DFC, eyelid status, and vigilance behavior documented here.…”

Section: Discussionmentioning

confidence: 78%

Spontaneous eyelid closures link vigilance fluctuation with fMRI dynamic connectivity states

Wang

Ong

Patanaik

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

193

185

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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 reduced withinnetwork functional connectivity of default mode and dorsal/ventral attention networks, as well as reduced anticorrelation between these networks. Conversely, during periods when participants' eyelids were wide open, a second DCS was associated with less decoupling between the visual network and higher-order cognitive networks that included dorsal/ventral attention and default mode networks. In subcortical structures, eyelid closures were associated with increased connectivity between the striatum and thalamus with the ventral attention network, and greater anticorrelation with the dorsal attention network. When applied to task-based fMRI data, these two DCS predicted interindividual differences in frequency of behavioral lapsing and intraindividual temporal fluctuations in response speed. These findings with participants who underwent a night of total sleep deprivation were replicated in an independent dataset involving partially sleep-deprived participants. Fluctuations in functional connectivity thus appear to be clearly associated with changes in arousal. T he existence of large-scale functional brain networks is evidenced by well-defined spatial patterns of correlated bloodoxygenation level-dependent (BOLD) signal fluctuation in fMRI data (1). Recent work has shown that functional connectivity (FC) within and between brain networks is dynamic, corresponding to the observation that even while we are performing a task, our mental focus fluctuates (2). Fluctuation of fMRI-based FC occurs over tens of seconds (3, 4) and exhibits different patterns across conscious and unconscious states (5, 6). Furthermore, just as interindividual differences in stationary FC relate to variation in human behavior and cognition (7-10), it seems likely that recurring patterns (11) of fluctuating FC have behavioral significance.Temporal fluctuations in FC can arise from conscious mental activity (12), episodes of random synchrony (3), or simply timevarying levels of physiological noise (13,14). The association between BOLD signal fluctuation in the default mode network (DMN) and mind-wandering episodes (15-17) has prompted investigations into the behavioral correlates of spontaneous resting-state FC fluctuations (11,18). Although these fluctuations in FC have been shown to correlate with several physiological markers, such as electroencephalogram (EEG) power, magnetoencephalography (MEG) power, and heart rate variability (19-21), their behavioral significance remains unclear.A key obstacle to elucidating clear FC...

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Section: Discussionmentioning

confidence: 78%

Spontaneous eyelid closures link vigilance fluctuation with fMRI dynamic connectivity states

Wang

Ong

Patanaik

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

193

185

View full text Add to dashboard Cite

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“…In a follow-up study, Wong et al (2015) compared measures of global signal amplitude and EEG vigilance in the eyes-open and eyes-closed states and found that changes (eyes-open minus eyes-closed) in the global signal amplitude were negatively correlated with the associated changes in EEG vigilance. Interestingly, the slope of this relation was found to be similar to that of the previously observed association between caffeine-related changes in the global signal amplitude and EEG vigilance, thus providing evidence for a fundamental relation between global signal amplitude and EEG vigilance.…”

Section: Information In the Global Signalmentioning

confidence: 99%

The global signal in fMRI: Nuisance or Information?

2017

Self Cite

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The global signal is widely used as a regressor or normalization factor for removing the effects of global variations in the analysis of functional magnetic resonance imaging (fMRI) studies. However, there is considerable controversy over its use because of the potential bias that can be introduced when it is applied to the analysis of both task-related and resting-state fMRI studies. In this paper we take a closer look at the global signal, examining in detail the various sources that can contribute to the signal. For the most part, the global signal has been treated as a nuisance term, but there is growing evidence that it may also contain valuable information. We also examine the various ways that the global signal has been used in the analysis of fMRI data, including global signal regression, global signal subtraction, and global signal normalization. Furthermore, we describe new ways for understanding the effects of global signal regression and its relation to the other approaches.

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“…For example, more attentive or vigilant (or caffeinated) human subjects exhibit reduced variance in the global fMRI signal (Wong et al, 2016; Wong et al, 2012, 2013). And psychiatric conditions have been characterized by differences in global fMRI signals, for example by altered variance in subjects with schizophrenia (Hahamy et al, 2014; Yang et al, 2014), or by an altered spatial distribution of the global signal in patients with autism spectrum disorder (Gotts et al, 2013; Gotts et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Sources and implications of whole-brain fMRI signals in humans

Power¹,

Plitt²,

Laumann³

et al. 2017

NeuroImage

522

592

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Whole-brain fMRI signals are a subject of intense interest: variance in the global fMRI signal (the spatial mean of all signals in the brain) indexes subject arousal, and psychiatric conditions such as schizophrenia and autism have been characterized by differences in the global fMRI signal. Further, vigorous debates exist on whether global signals ought to be removed from fMRI data. However, surprisingly little research has focused on the empirical properties of whole-brain fMRI signals. Here we map the spatial and temporal properties of the global signal, individually, in 1000+ fMRI scans. Variance in the global fMRI signal is strongly linked to head motion, to hardware artifacts, and to respiratory patterns and their attendant physiologic changes. Many techniques used to prepare fMRI data for analysis fail to remove these uninteresting kinds of global signal fluctuations. Thus, many studies include, at the time of analysis, prominent global effects of yawns, breathing changes, and head motion, among other signals. Such artifacts will mimic dynamic neural activity and will spuriously alter signal covariance throughout the brain. Methods capable of isolating and removing global artifactual variance while preserving putative “neural” variance are needed; this paper adopts no position on the topic of global signal regression.

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Differences in the resting-state fMRI global signal amplitude between the eyes open and eyes closed states are related to changes in EEG vigilance

Cited by 115 publications

References 60 publications

Spontaneous eyelid closures link vigilance fluctuation with fMRI dynamic connectivity states

Spontaneous eyelid closures link vigilance fluctuation with fMRI dynamic connectivity states

The global signal in fMRI: Nuisance or Information?

Sources and implications of whole-brain fMRI signals in humans

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