An Analysis of Heart Rate Variability

Luczak, Holger; Laurig, Wolfgang

doi:10.1080/00140137308924484

Cited by 178 publications

(46 citation statements)

References 5 publications

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“…Tachycardic response is mediated via sympathetic outflow from the rVLM (Dampney et al 2002). Interestingly, these efferent outflows can be estimated non-invasively by analysis of heart rate variability (HRV) (Luczak et al 1973;Sayers 1973;Akselrod et al 1981;Malik et al 1996). This method typically involves deriving the frequency spectrum of a continuous estimate of heart rate (HR).…”

Section: Introductionmentioning

confidence: 99%

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

Napadow¹,

Dhond²,

Conti³

et al. 2008

NeuroImage

304

229

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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 et al. 1998). 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 HF timeseries resampled at 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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Section: Introductionmentioning

confidence: 99%

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

Napadow¹,

Dhond²,

Conti³

et al. 2008

NeuroImage

304

229

View full text Add to dashboard Cite

show abstract

“…This tool has been validated, and it is now widely used in cardiology. [3][4][5] It provides qualitative, quantitative, and noninvasive analysis of global autonomic function.…”

mentioning

confidence: 99%

Characteristics of Autonomic Nervous System Activity in Men With Lower Urinary Tract Symptoms (LUTS): Analysis of Heart Rate Variability in Men With LUTS

Choi

Lee

Kim

2010

Urology

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“…Results on heart rate variability are also not consistent. In some studies certain measures of heart rate variability proved to be valid indicators of cognitive workload (Luczak and Laurig, 1973;Strasser, 1981;Mulder and Mulder, 1987;Wilson and O´Donnel, 1988;Kramer, 1991) whereas in other experiments they were less sensitive Schick and Radtke, 1979).…”

Section: Validity Of the Methodsmentioning

confidence: 99%