Bidirectional intrinsic modulation of EEG band power time series and spectral components of heart rate variability

Pardo-Rodriguez, MariNieves; Bojorges-Valdez, Erik; Yáñez-Suárez, Oscar

doi:10.1016/j.autneu.2021.102776

Cited by 11 publications

(3 citation statements)

References 36 publications

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“…Several previous studies have employed Granger causality or similar methods to examine directional interactions between EEG and heart rate, raw EKG, or HRV power time series. Contrary to results of the present study, the majority of these studies have reported stronger brain-to-heart than heart-to-brain effects (Abdalbari et al, 2022; Greco et al, 2019; Lin et al, 2016; Pardo-Rodriguez et al, 2021). However, one study showed that HF-HRV power changes preceded changes in the delta band during sleep (Jurysta et al, 2003), and another showed stronger heart-to-brain interactions during an emotion elicitation paradigm (Candia-Rivera et al, 2022).…”

Section: Discussioncontrasting

confidence: 99%

Oscillatory Coupling Between Neural and Cardiac Rhythms

Sargent,

Martinez,

Reed

et al. 2024

Psychol Sci

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Oscillations serve a critical role in organizing biological systems. In the brain, oscillatory coupling is a fundamental mechanism of communication. The possibility that neural oscillations interact directly with slower physiological rhythms (e.g., heart rate, respiration) is largely unexplored and may have important implications for psychological functioning. Oscillations in heart rate, an aspect of heart rate variability (HRV), show remarkably robust associations with psychological health. Mather and Thayer proposed coupling between high-frequency HRV (HF-HRV) and neural oscillations as a mechanism that partially accounts for such relationships. We tested this hypothesis by measuring phase-amplitude coupling between HF-HRV and neural oscillations in 37 healthy adults at rest. Robust coupling was detected in all frequency bands. Granger causality analyses indicated stronger heart-to-brain than brain-to-heart effects in all frequency bands except gamma. These findings suggest that cardiac rhythms play a causal role in modulating neural oscillations, which may have important implications for mental health.

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Section: Discussioncontrasting

confidence: 99%

Oscillatory Coupling Between Neural and Cardiac Rhythms

Sargent,

Martinez,

Reed

et al. 2024

Psychol Sci

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“…[18,32] In a pilot study, Zhan, et al [5] showed that the time and frequency parameters of HRV facilitate the assessment of anesthesia across a wide ranges of levels. So far, the level of concordance of EEG and HRV has been tested on awake patients [19][20][21], under experimental conditions [22] or performed during the induction of general anesthesia. [17,18] But it has not been adequately studied throughout general anesthesia.…”

Section: Discussionmentioning

confidence: 99%

“…[15] Since HRV can serve as an indicator of brainstem activity and thus ANS function, a promising method has become available to complement EEG measurements with the goal of maintaining autonomic homeostasis during general anesthesia. [16-18] However, the pioneering studies of the level of concordance between EEG and HRV have mostly been performed on awake patients [19][20][21], under experimental conditions [22] or have been performed during induction of general anesthesia. [17,18] To our knowledge, the level of concordance between EEG and HRV during general anesthesia has not been adequately studied yet.…”

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confidence: 99%

Heart rate variability as a predictor of intraoperative autonomic nervous system homeostasis

Keim,

Bolwin,

Feldmann

et al. 2023

Preprint

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Purpose The aim of the proof-of-concept study is to investigate the level of concordance between the heart rate variability (HRV), the EEG-based Narcotrend Index as a surrogate marker for the depth of anesthesia, and the minimal alveolar concentration (MAC) of the inhalation anesthetic sevoflurane across the entire course of a surgical procedure. Methods This non-blinded cross-sectional study recorded intraoperative HRV, Narcotrend Index, and MAC in 31 male patients during radical prostatectomy using the Da-Vinci robotic-assisted surgical system at Mannheim University Medical Center. The degree of concordance was calculated using repeated measures correlation with the R package (rmcorr) and presented using the rmcorr coefficient (rrm). Results The Narcotrend Index correlates significantly across all measures with the time-dependent parameter of HRV, the standard deviation of the means of RR intervals (SDNN) (rrm = 0.2; p < 0.001), the frequency-dependent parameters low frequency (LF) (rrm = 0.09; p = 0.04) and the low frequency/high frequency ratio (LF/HF ratio) (rrm = 0.11; p = 0.002). MAC correlated significantly negatively with the time-dependent parameter of heart rate variability, SDNN (rrm = -0.28; p < 0.001), the frequency-dependent parameter LF (rrm = -0.06; p < 0.001) and the LF/HF ratio (rrm = -0.18; p < 0.001) and the Narcotrend Index (rrm = -0.49; p < 0.001) across all measures. Conclusion HRV mirrors the trend of the Narcotrend Index used to monitor depth of anesthesia and the inhibitory influence of the anesthetic sevoflurane on the autonomic nervous system. Therefore, HRV can provide essential information about the homeostasis of the autonomic nervous system during general anesthesia. Trial registration number: DRKS00024696, March 9th, 2021

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BHI Estimation Methodology

Catrambone

Valenza

2021

Functional Brain-Heart Interplay

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Bidirectional intrinsic modulation of EEG band power time series and spectral components of heart rate variability

Cited by 11 publications

References 36 publications

Oscillatory Coupling Between Neural and Cardiac Rhythms

Oscillatory Coupling Between Neural and Cardiac Rhythms

Heart rate variability as a predictor of intraoperative autonomic nervous system homeostasis

BHI Estimation Methodology

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