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Related Concept Videos

Factors Influencing Heart Rate01:30

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The heart rate, or pulse rate, is a vital indicator of cardiovascular health. It reflects the number of times the heart beats per minute. Various physiological and environmental factors influence heart rate, increasing or decreasing cardiac output. Understanding these factors is crucial for assessing heart function and identifying potential health issues.
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The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
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The regulation of heart rate is a complex process controlled by the autonomic nervous system (ANS), hormonal influences, and intrinsic cardiac mechanisms. The ANS has two main components: the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS).
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Cardiac Output
Cardiac output (CO) refers to the total amount of blood ejected by one of the ventricles in liters per minute (L/min). In a resting adult, CO ranges from 5 to 6 L/min, adjusting according to the body's metabolic requirements.
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An electrocardiogram (ECG)graphically represents the heart's electrical activity on ECG paper or a monitor.
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The normal cardiac rhythm is a synchronized electrical activity that facilitates the regular and coordinated contraction of the heart muscle. This process is essential for efficient blood circulation throughout the body. The fundamental elements involved in establishing and maintaining this rhythm include the unique electrical properties of cardiac muscle cells, the sinoatrial (SA) node's pacemaker function, the specialized conducting system, and the ionic mechanisms underlying each phase...
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Related Experiment Video

Updated: Mar 29, 2026

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
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Decoding brain-heart dynamics: Effective connectivity predictors of heart rate variability.

Maria Di Bello1, Roger C McIntosh1

  • 1Department of Psychology, Divisions of Health, Cognitive and Behavioral Neuroscience, University of Miami, 5051 San Amaro Drive, Coral Gables, FL 33146, United States.

Neuroimage
|March 27, 2026
PubMed
Summary

Effective connectivity within extended brain networks predicts heart rate variability (HRV) dynamics. This study reveals complex brain-heart interactions beyond the Central Autonomic Network (CAN), highlighting HRV

Keywords:
AutonomicEffective connectivityEntropyHeart rate variabilityMachine learningRegression dynamic causal modeling

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Area of Science:

  • Neuroscience
  • Cardiovascular Physiology
  • Autonomic Nervous System Research

Background:

  • Autonomic dysregulation is a hallmark of many neuropsychiatric and somatic disorders.
  • The Central Autonomic Network (CAN) mediates brain-heart communication, crucial for autonomic balance.
  • Heart rate variability (HRV) reflects CAN regulation, but its causal brain interactions are unclear.

Purpose of the Study:

  • To investigate effective connectivity (EC) within core, extended, and non-canonical CAN regions.
  • To characterize bidirectional brain-heart dynamics at rest using resting-state fMRI and photoplethysmography.
  • To model HRV as a driving input to understand its influence on brain activity.

Main Methods:

  • Acquired resting-state fMRI and photoplethysmography from 232 adults.
  • Extracted time, frequency, and entropy-based HRV metrics.
  • Estimated EC using regression dynamic causal modeling across 100 brain regions, including 42 C-CAN nodes, and employed cross-validated ridge regression for predictive modeling.

Main Results:

  • Extended CAN EC models best predicted entropy metrics (ApEn: r=0.22, SampEn: r=0.21).
  • Core CAN EC models further improved predictive performance (SampEn: r=0.27, ApEn: r=0.23).
  • HRV-driven influences were observed on distributed cortical and subcortical regions, indicating bottom-up cardio-autonomic signaling impacts on brain function.

Conclusions:

  • Effective connectivity predicts HRV through integrative brain networks extending beyond canonical CAN nodes.
  • Entropy-based HRV measures are sensitive indicators of central autonomic influence on heart dynamics.
  • Causal brain-heart interactions, reflected in HRV, mirror connectivity patterns across canonical and extended CAN parcellations, underscoring neurovisceral integration complexity.