Association between heart rate variability and fluctuations in resting-state functional connectivity

By Catie Chang, Coraline D. Metzger, Gary H. Glover, Jeff H. Duyn, Hans-Jochen Heinze, Martin Walter. NeuroImage, 2012

341 citations recorded by the source corpus.

Functional connectivity has been observed to fluctuate across the course of a resting state scan, though the origins and functional relevance of this phenomenon remain to be shown. The present study explores the link between endogenous dynamics of functional connectivity and autonomic state in an eyes-closed resting condition. Using a sliding window analysis on resting state fMRI data from 35 young, healthy male subjects, we examined how heart rate variability (HRV) covaries with temporal changes in whole-brain functional connectivity with seed regions previously described to mediate effects of vigilance and arousal (amygdala and dorsal anterior cingulate cortex; dACC). We identified a set of regions, including brainstem, thalamus, putamen, and dorsolateral prefrontal cortex, that became more strongly coupled with the dACC and amygdala seeds during states of elevated HRV. Effects differed between high and low frequency components of HRV, suggesting specific contributions of parasympathetic and sympathetic tone on individual connections. Furthermore, dynamics of functional connectivity could be separated from those primarily related to BOLD signal fluctuations. The present results contribute novel information about the neural basis of transient changes of autonomic nervous system states, and suggest physiological and psychological components of the recently observed non-stationarity in resting state functional connectivity.

Subfields: Cardiology and Cardiovascular Medicine, Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/8706f7ae418570abc72a2fe7545275ddc4494dec

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Citations in the corpus

Time-resolved resting-state brain networks (2014, background): “Confounds include scanner drift, head motion (47), and physiological noise due to variation in respiratory depth/rate (34) and cardiac rate (48).”
Dynamic functional connectivity: Promise, issues, and interpretations (2013, methodology): “…to identify potential correlates of variations in resting-state FC in simultaneously recorded electrophysiological data (Allen et al., 2013; Chang et al., 2013b; Tagliazucchi et al., 2012b) as well as behavior (Thompson et al., in press), suggesting that variations in FC are to some degree…”
Methods for cleaning the BOLD fMRI signal (2016, neutral): “The low and high frequency components of HRV can be extracted by performing a time-frequency analysis using wavelets (Chang et al., 2013) or the Smoothed Pseudo Wigner Ville Distribution (Gil et al., 2010).”
Sources and implications of whole-brain fMRI signals in humans (2016, background): “This phenomenon accords with prior reports that short-term heart rate variability correlates with respiration volume and lowered respiration rate (Chang et al., 2013).”
Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest (2013, background): “Chang et al. (2013b) reported a link between heart rate variability and dynamic FC in some brain regions related to arousal and vigilance, suggesting a neural basis for these fluctuations, and Hutchison et al. (in press) showed that these fluctuations persist in anesthetized monkeys in the absence…”