Translational perspectives on brain-heart interplay: From methodologies to clinical applications.

The nervous and cardiovascular systems are intricately interconnected in both healthy and diseased conditions. The field of Neurocardiology, which focuses on the complex interaction between the nervous and cardiovascular systems, has grown rapidly over the past years. In addition, growing evidence shows that alterations in Brain-Heart Interplay (BHI) may contribute to neurological and cardiovascular disorders. BHI has great potential as a valuable biomarker to detect autonomic dysfunction, and reveal the mechanisms underlying conditions including sleep-related autonomic disorders and neurodegenerative diseases. However, the physiological characterization of linear or non-linear brain-heart relationships remains unclear. This review presents a comprehensive analysis of the current methods used to characterize BHI across multiple domains, with an emphasis on Electroencephalogram (EEG), Electrocardiogram (ECG), or Photoplethysmogram (PPG). Such non-invasive modalities allow for long-term and time-varying assessment of cortical and autonomic activity. In this work, we review how BHI modulates across various physiological and pathological states and highlight key findings from recent studies. In addition, we review potential data-driven methods to examine complex BHI, including measures of synchronization, directionality, and information transfer. As a result, studying BHI using these strategies offers a new angle on the complex and dynamic interaction of cortical and autonomic processes. This provides an opportunity to understand the intricate interplay between brain and heart functions, and has the potential to advance diagnosis, monitoring, and therapeutic interventions in neurocardiac conditions.

• Publication year

  2026

• Venue

  Computers in Biology and Medicine

• Publication date

  2026-02-05

• Fields of study

  Medicine

• Identifiers
  DOI 10.1016/j.compbiomed.2026.111522PMID 41650802
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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