ArticleBrain sciences2025
Identifying Cardiovascular Risk by Nonlinear Heart Rate Dynamics Analysis: Translational Biomarker from Mice to Humans.
Article in Brain sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Mindfulness-based intervention alters nonlinear heart rate variability in a pilot study.Discover mental health · 2026Article
- Relationship between the autonomic nervous system and cerebral autoregulation during controlled breathing.European journal of applied physiology · 2026Article
- Heart rate variability findings in neurological decompression sickness: an exploratory case series.Frontiers in physiology · 2026Article
- Autonomic-Immunoinflammatory-Cardiac Interplay during Lipopolysaccharide-Induced Systemic Inflammation.Neuroimmunomodulation · 2026Article
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4 authors.
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Abstract
backgroundThe beat-by-beat fluctuation of heart rate (HR) in its temporal sequence (HR dynamics) provides information on HR regulation by the autonomic nervous system (ANS) and its dysregulation in pathological states. Commonly, linear analyses of HR and its variability (HRV) are used to draw conclusions about pathological states despite clear statistical and translational limitations.
objectiveThe main aim of this study was to compare linear and nonlinear HR measures, including detrended fluctuation analysis (DFA), based on ECG recordings by radiotelemetry in C57BL/6N mice to identify pathological HR dynamics.
methodsWe investigated different behavioral and a wide range of pharmacological interventions which alter ANS regulation through various peripheral and/or central mechanisms including receptors implicated in psychiatric disorders. This spectrum of interventions served as a reference system for comparison of linear and nonlinear HR measures to identify pathological states.
resultsPhysiological HR dynamics constitute a self-similar, scale-invariant, fractal process with persistent intrinsic long-range correlations resulting in physiological DFA scaling coefficients of α~1. Strongly altered DFA scaling coefficients (α ≠ 1) indicate pathological states of HR dynamics as elicited by (1) parasympathetic blockade, (2) parasympathetic overactivation and (3) sympathetic overactivation but not inhibition. The DFA scaling coefficients are identical in mice and humans under physiological conditions with identical pathological states by defined pharmacological interventions.
conclusionsHere, we show the importance of tonic vagal function for physiological HR dynamics in mice, as reported in humans. Unlike linear measures, DFA provides an important translational measure that reliably identifies pathological HR dynamics based on altered ANS control by pharmacological interventions. Central ANS dysregulation represents a likely mechanism of increased cardiac mortality in psychiatric disorders.
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