Brain correlates of autonomic modulation: Combining heart rate variability with fMRI

By Vitaly Napadow, R. Dhond, Giulia Conti, Nikos Makris, Emery N. Brown, Riccardo Barbieri. NeuroImage, 2008

368 citations recorded by the source corpus.

The central autonomic network (CAN) has been described in animal models but has been difficult to elucidate in humans. Potential confounds include physiological noise artifacts affecting brainstem neuroimaging data, and difficulty in deriving non-invasive continuous assessments of autonomic modulation. We have developed and implemented a new method which relates cardiac-gated fMRI timeseries with continuous-time heart rate variability (HRV) to estimate central autonomic processing. As many autonomic structures of interest are in brain regions strongly affected by cardiogenic pulsatility, we chose to cardiac-gate our fMRI acquisition to increase sensitivity. Cardiac-gating introduces T1-variability, which was corrected by transforming fMRI data to a fixed TR using a previously published method [Guimaraes, A.R., Melcher, J.R., et al., 1998. Imaging subcortical auditory activity in humans. Hum. Brain Mapp. 6(1), 33-41]. The electrocardiogram was analyzed with a novel point process adaptive-filter algorithm for computation of the high-frequency (HF) index, reflecting the time-varying dynamics of efferent cardiovagal modulation. Central command of cardiovagal outflow was inferred by using the resample HF timeseries as a regressor to the fMRI data. A grip task was used to perturb the autonomic nervous system. Our combined HRV-fMRI approach demonstrated HF correlation with fMRI activity in the hypothalamus, cerebellum, parabrachial nucleus/locus ceruleus, periaqueductal gray, amygdala, hippocampus, thalamus, and dorsomedial/dorsolateral prefrontal, posterior insular, and middle temporal cortices. While some regions consistent with central cardiovagal control in animal models gave corroborative evidence for our methodology, other mostly higher cortical or limbic-related brain regions may be unique to humans. Our approach should be optimized and applied to study the human brain correlates of autonomic modulation for various stimuli in both physiological and pathological states.

Subfields: Cardiology and Cardiovascular Medicine, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/f726670287ba8fca55689b74fb5a9c849acbd7f8

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Citations in the corpus

Being Left Out: Neurobiological Correlates of Social Rejection and their Developmental Trajectory (2011, neutral): “Indeed, studies have demonstrated correlations between heart rate changes and brain activity in areas of this network (e.g., Critchley et al., 2003; Gianaros et al., 2004; Napadow et al., 2008).”
Functional connectivity of the insula in the resting brain (2011, neutral): “Several nuisance covariates were included in the analyses to reduce the effects of physiological processes such as fluctuations related to cardiac and respiratory cycles (Bandettini and Bullmore, 2008; Napadow et al., 2008), or to motion.”
Association between heart rate variability and fluctuations in resting-state functional connectivity (2012, background): “Previous fMRI and PET studies have examined theneural basis of HRV changes by measuring BOLD activity (Critchley et al., 2003; Napadow et al., 2008) and regional cerebral blood flow (rCBF; Gianaros et al., 2004; Lane et al., 2009) in relation to task-induced emotional, physical, and cognitive…”
Neuroimaging of the Periaqueductal Gray: State of the Field (2011, methodology): “…et al., 2006b; Guimaraes et al., 1998; Mainero et al., 2007; Napadow et al., 2008), midbrain optimized imaging sequences (Fairhurst et al., 2007; Napadow et al., 2008, 2009; Pattinson et al., 2009; Topolovec et al., 2004; Tracey et al., 2002a), physiological noise modeling (Brooks et al.,…”
A meta-analysis of heart rate variability and neuroimaging studies: implications for heart rate variability as a marker of stress and health. (2012, neutral): “t Napadow, 2008 (Napadow et al., 2008) (3♀ 4♂) fMRI Lane, 2009 (12♀) PET Ahs, 2009 (Åhs et al.”