ArticleFrontiers in physiology2017
Baroreflex Coupling Assessed by Cross-Compression Entropy.
Article in Frontiers in physiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Estimating Resting HRV during fMRI: A Comparison between Laboratory and Scanner Environment.Sensors (Basel, Switzerland) · 2021Article
- The Influence of Heart Rate Variability Biofeedback on Cardiac Regulation and Functional Brain Connectivity.Frontiers in neuroscience · 2021Article
- Sympathetic and Parasympathetic Modulation of Pupillary Unrest.Frontiers in neuroscience · 2020Article
- Multiscale Information Decomposition Dissects Control Mechanisms of Heart Rate Variability at Rest and During Physiological Stress.Entropy (Basel, Switzerland) · 2019Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Estimating interactions between physiological systems is an important challenge in modern biomedical research. Here, we explore a new concept for quantifying information common in two time series by cross-compressibility. Cross-compression entropy (CCE) exploits the ZIP data compression algorithm extended to bivariate data analysis. First, time series are transformed into symbol vectors. Symbols of the target time series are coded by the symbols of the source series. Uncoupled and linearly coupled surrogates were derived from cardiovascular recordings of 36 healthy controls obtained during rest to demonstrate suitability of this method for assessing physiological coupling. CCE at rest was compared to that of isometric handgrip exercise. Finally, spontaneous baroreflex interaction assessed by CCE
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