Tracking brain arousal fluctuations with fMRI

Abstract

Changes in brain activity accompanying shifts in vigilance and arousal can interfere with the study of other intrinsic and task-evoked characteristics of brain function. However, the difficulty of tracking and modeling the arousal state during functional MRI (fMRI) typically precludes the assessment of arousal-dependent influences on fMRI signals. Here we combine fMRI, electrophysiology, and the monitoring of eyelid behavior to demonstrate an approach for tracking continuous variations in arousal level from fMRI data. We first characterize the spatial distribution of fMRI signal fluctuations that track a measure of behavioral arousal; taking this pattern as a template, and using the local field potential as a simultaneous and independent measure of cortical activity, we observe that the timevarying expression level of this template in fMRI data provides a close approximation of electrophysiological arousal. We discuss the potential benefit of these findings for increasing the sensitivity of fMRI as a cognitive and clinical biomarker.resting-state fMRI | spontaneous fluctuations | arousal | electrophysiology D uring both active task engagement and rest, the human brain exhibits fluctuations in neural activity that can be readily measured using functional MRI (fMRI). In recent years, examining the spatiotemporal organization of these fluctuations has generated novel insight into the functional architecture of the human brain and its changes with development and disease (1). A prominent approach for mapping this architecture is to study interregional correlations in the fMRI signal fluctuations, which, even during rest, appear to be indicative of networks supporting specific functions. However, despite the promise and rapidly increasing application of this technique in the endeavor of brain connectomics (2-4), its sensitivity and specificity are compromised by unexplained variability arising from multiple neural and nonneural sources (e.g., refs. 5-11). As a result, the interpretation of resting-state fMRI data and the efficacy of these data as a biomarker rely critically on understanding and accounting for such sources of variability (11-13).Changes in arousal, mediated by an interaction between the ascending arousal system and the neocortex, may strongly modulate neuronal activity in much of the brain (14-18). Indeed, changes in vigilance and arousal (hereafter described jointly as "arousal"), which can be especially prevalent during the passive and uncontrolled resting state, result in fMRI signal variability that may confound the extraction of functional networks (5, 19). For example, the amplitude and extent of correlations in restingstate fMRI data vary with EEG-and behaviorally defined indicators of drowsiness and light sleep (20)(21)(22)(23)(24)(25) and are altered by sleep deprivation (26-28) and caffeine-induced changes in arousal state (29). Distinct patterns of functional connectivity across multiple networks have been associated with distinct EEG-defined sleep stages (30, 31) with sufficient reliabilit...

Delineating the Macroscale Areal Organization of the Macaque Cortex In Vivo

“…However, unlike prior studies, which largely relied on variations of depth of anesthesia, our comparison of awake states and anesthesia also suggested that the visual networks and their connectivity with default and frontoparietal networks actually showed anesthesia-related increases in connectivity. Overall, these findings echo recent studies of the impact of anesthetics on brain differences in humans, which suggested a loss of complexity in the functional architecture of the brain (Chang et al, 2016; Hutchison et al., 2014; Peltier et al, 2005; Smith et al, 2017; Wu et al, 2016). Further work will be required to rule out other possibilities, such as differences in respiration associated with differing states (awake or anesthesia).…”

Spontaneous eyelid closures link vigilance fluctuation with fMRI dynamic connectivity states

“…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.…”

Altered physiological brain variation in drug‐resistant epilepsy

“…A recent finding regarding the global fMRI signal SD indicates that indeed the arousal of the subjects may have a widespread effect on the fMRI results (Chang et al., 2016; Liu et al., 2018). Subjects with epilepsy have altered sleep homeostasis and present widespread and complex neural and hemodynamic signal changes that are different in deep brain structures compared to cortex (Boly et al., 2017; Peter‐Derex, Magnin, & Bastuji, 2015; Salek‐Haddadi et al., 2003).…”