ArticleMethodsX2023
Modeling brain-heart interactions from Poincaré plot-derived measures of sympathetic-vagal activity.
Article in MethodsX, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Brain-heart interactions in late-onset major depressive disorder revealed by multimodal HRV-driven fMRI.Communications biology · 2026Article
- Predicting neurological recovery following cardiac arrest based on dynamic brain-heart coupling.Journal of neuroengineering and rehabilitation · 2026Article
- Shared Neurocardiac Pathways Linking Atrial Fibrillation and Depression: A UK Biobank Analysis.medRxiv : the preprint server for health sciences · 2026Article
- Cardiac-vagal rhythm echoes on the heartbeat's mechanosensory imprint in the brain.Communications biology · 2025Article
- Robust and time-resolved estimation of cardiac sympathetic and parasympathetic indices.Royal Society open science · 2025Article
- Robust and time-resolved estimation of cardiac sympathetic and parasympathetic indices.bioRxiv : the preprint server for biology · 2024Article
- Intracortical brain-heart interplay: An EEG model source study of sympathovagal changes.Human brain mapping · 2024Article
- A framework for quantifying the coupling between brain connectivity and heartbeat dynamics: Insights into the disrupted network physiology in Parkinson's disease.Human brain mapping · 2024Article
- Transcutaneous auricular vagus nerve stimulation modulates the processing of interoceptive prediction error signals and their role in allostatic regulation.Human brain mapping · 2024Article
- Measures of the coupling between fluctuating brain network organization and heartbeat dynamics.Network neuroscience (Cambridge, Mass.) · 2024Article
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1 author.
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Abstract
Recent studies suggest that the interaction between the brain and heart plays a key role in cognitive processes, and measuring these interactions is crucial for understanding the interaction between the central and autonomic nervous systems. However, studying this bidirectional interplay presents methodological challenges, and there is still much room for exploration. This paper presents a new computational method called the Poincaré Sympathetic-Vagal Synthetic Data Generation Model (PSV-SDG) for estimating brain-heart interactions. The PSV-SDG combines EEG and cardiac sympathetic-vagal dynamics to provide time-varying and bidirectional estimators of mutual interplay. The method is grounded in the Poincaré plot, a heart rate variability method to estimate sympathetic-vagal activity that can account for potential non-linearities. This algorithm offers a new approach and computational tool for functional assessment of the interplay between EEG and cardiac sympathetic-vagal activity. The method is implemented in MATLAB under an open-source license. • A new brain-heart interaction modeling approach is proposed. • The modeling is based on coupled synthetic data generators of EEG and heart rate series. • Sympathetic and vagal activities are gathered from Poincaré plot geometry.
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