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


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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    • "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. "

    Neural Plasticity 10/2015; · 3.58 Impact Factor
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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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    ABSTRACT: We tested the hypothesis of a relationship between heart rate variability (HRV) and Rolandic mu rhythms in relaxed condition of resting state. Resting state eyes-closed electroencephalographic (EEG) and electrocardiographic (ECG) data were recorded (10-20 system) in 42 healthy adults. EEG rhythms of interest were high-frequency alpha (10.5-13Hz) and low-frequency beta (13-20Hz), which are supposed to form Rolandic mu rhythms. Rolandic and occipital (control) EEG sources were estimated by LORETA software. Results showed a statistically significant (p<0.05, corrected) negative correlation across all subjects between Rolandic cortical sources of low-frequency beta rhythms and the low-frequency band power (LF, 0.04-0.15Hz) of tachogram spectrum as an index of HRV. The lower the amplitude of Rolandic sources of low-frequency beta rhythms (as a putative sign of activity of somatomotor cortex), the higher the LF band power of tachogram spectrum (as a putative sign of sympathetic activity). This effect was specific as there was neither a similar correlation between these EEG rhythms and high-frequency band power of tachogram spectrum (as a putative sign of parasympathetic vagal activity) neither between occipital sources of low-frequency beta rhythms (as a putative sign of activity of visual cortex) and LF band power of tachogram spectrum. These results suggest that Rolandic low-frequency beta rhythms are related to sympathetic activity regulating heart rate, as a dynamic neurophysiologic oscillatory mechanism sub-serving the interaction between brain neural populations involved in somatomotor control and brain neural populations regulating ANS signals to heart for on-going homeostatic adaptations. Copyright © 2015. Published by Elsevier B.V.
    International journal of psychophysiology: official journal of the International Organization of Psychophysiology 02/2015; DOI:10.1016/j.ijpsycho.2015.02.009 · 2.88 Impact Factor
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    • "Central influences on the ANS are well known from neuropsychological studies [13] and from studies showing different visceral responses to regional electric stimulation of the cerebral cortex [14] [15]. Furthermore , mature animal studies using retroviral labeling, as well as adult human brain stimulation and imaging studies, have implicated forebrain structures in the central control of the ANS [14] [15] [16] [17] [18]. Some of these cortical regions exhibit a laterality in which the left regions appear to modulate parasympathetic cardiovascular effects, while the right "
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    ABSTRACT: Objective: Cerebral mapping of central autonomic nervous system (ANS)(1) function in mature animals and humans lateralizes sympathetic and parasympathetic influence predominantly to the right and left cerebral hemispheres, respectively. Spectral analysis of heart rate variability (HRV)(2) is an established measure of ANS function. We examined whether such lateralization is present in the term newborn. Methods: We retrospectively reviewed records of infants >36 weeks of gestation diagnosed with hypoxic ischemic encephalopathy (HIE).(3) We included infants with neonatal EEG and regional injury on brain MRI, which was scored using a schema. We extracted ECG signals from the EEG recording, but excluded periods of electrographic seizure activity to eliminate possible seizure influence on HRV. HRV was evaluated by spectral analysis in the high frequency (HF(4); 0.3-1 Hz) and low frequency (LF(5); 0.05-0.25 Hz) ranges, and the LF/HF ratio was examined to assess sympatho-vagal balance. The relation between the injured brain regions and HRV was studied using multiple linear regression models. Results: We studied 40 neonates with HIE. Injury to the right cerebral cortex (p=0.009) and right cerebellum (p=0.041) predicted a decreased LF/HF ratio. Injury to the left cerebral cortex (p=0.035) and left cerebellum (p=0.041) was associated with an increased LF/HF ratio. The association between brain injury location and the individual LF or HF spectral powers of brain injury did not reach significance. Conclusions: Our data suggest that a functional lateralization for cerebral autonomic influence is established by term gestation.
    Early Human Development 12/2014; 90(12). DOI:10.1016/j.earlhumdev.2014.10.003 · 1.79 Impact Factor
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