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.
Saibene et al. (2026) studied this question. Non-invasive methods like EEG, ECG, and PPG can characterize brain-heart interplay, aiding diagnosis and therapy of neurocardiac and autonomic disorders.
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