Article

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

MGH/MIT/HMS Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02119, USA.
NeuroImage (Impact Factor: 6.36). 08/2008; 42(1):169-77. DOI: 10.1016/j.neuroimage.2008.04.238
Source: PubMed

ABSTRACT

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.

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    • "These regions were also reported to be activated by the nociceptive responses to heat, capsaicin, or mechanical stimulation applied to the hand or forearm skin by using positron emission tomography and fMRI (Peyron et al., 2000). However, the supplementary motor area and cerebellum were known to be involved in the regulation of sympathetic activity (Beissner et al., 2013), as revealed by significant correlations between fMRI signal and instantaneous high frequency power of heart rate changes (Napadow et al., 2008). "
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    • "The linear regression was used to reduce the effects of physiological processes (e.g., the fluctuations of cardiac and respiratory cycles). Otherwise, the 9 noise covariates were added in the regression analysis, including White Matter (WM), Cerebro-Spinal Fluid (CSF), Global Signal (GS), as well as 6 motion parameters (3 rotations and 3 translations as saved by the 3D motion correction) [39] [40] [41] [42]. We derived the GS/WM/CSF nuisance signals averaging the time courses of the voxels in each subject's whole brain/WM/CSF masks. "

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    • "Unfortunately, resting state EEG recordings do not have the sufficient spatial resolution to enlighten the functional connectivity between brain neural networks generating Rolandic mu rhythms and central autonomic network (CAN) supposed to adapt the activity of visceral organs according to animal data (Arthur and Loewy, 1990; Benarroch, 1993; Friedman and Thayer, 1998; Napadow et al., 2008; Saper, 2002; Ida and Llewellyn-Smith, 2011). It is supposed that CAN receives sensory afferents in medulla and integrate them in pons, thalamus, hypothalamus , amygdala, and insula. "
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