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Updated: Jul 15, 2025

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Entropy-Based Multifractal Testing of Heart Rate Variability during Cognitive-Autonomic Interplay.

Laurent M Arsac1

  • 1Univ. Bordeaux, CNRS, Laboratoire IMS, UMR 5218 Talence, France.

Entropy (Basel, Switzerland)
|September 28, 2023
PubMed
Summary
This summary is machine-generated.

New heart rate variability (HRV) complexity markers were identified during cognitive tasks. The Stroop task showed a unique multifractal (MF) signature, while the go/no-go task highlighted large-scale fluctuations (MFlarge).

Keywords:
DFAautonomic controlcardiovascularcentral autonomic networkcognitive taskheart–brainmultifractality

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Area of Science:

  • Cardiovascular Physiology
  • Cognitive Neuroscience
  • Complexity Science

Background:

  • Heart rate variability (HRV) complexity analysis offers insights into cardiovascular dynamics.
  • Traditional multifractal analysis (MFA) using detrended fluctuation analysis (DFA) explores fractal scaling.
  • Shannon entropy provides an alternative method for assessing multifractal structures.

Purpose of the Study:

  • To reanalyze HRV during cognitive tasks using entropy-based multifractal spectra.
  • To derive novel HRV complexity markers based on the Chhabra-Jensen method.
  • To investigate the cognitive-autonomic interplay through new HRV estimators.

Main Methods:

  • Collected inter-beat interval (RR) time series from 28 students during baseline and cognitive tasks (Stroop, stop-signal, go/no-go).
  • Applied the Chhabra-Jensen method to extract entropy-based multifractal spectra (f/α singularity spectrum) from RR magnitude increment series.
  • Calculated novel HRV estimators: whole spectrum width (MF), large-fluctuation width (MFlarge), and small-fluctuation width (MFsmall).

Main Results:

  • The Stroop color and word task exhibited a distinct multifractal (MF) signature.
  • The go/no-go task was specifically associated with large-sized fluctuations (MFlarge).
  • New HRV markers potentially reflect different facets of cognitive-autonomic interactions.

Conclusions:

  • Entropy-based multifractal spectra provide novel insights into HRV complexity during cognitive load.
  • Specific MF signatures may differentiate cognitive task demands on cardiovascular control.
  • These findings contribute to understanding the cognitive-autonomic interplay and cardiovascular complexity.