ArticleEuropean heart journal. Imaging methods and practice2026
Listeners' baseline autonomic states associated with distinct music-physiology response patterns.
Article in European heart journal. Imaging methods and practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Aims: Personalizing music-based interventions requires an understanding of how individuals' physiology responds to expressive music events. Although music can modulate autonomic function, variability across listeners has limited its therapeutic use. We introduce a change-point-driven framework that links music features to cardiovascular responses and test whether baseline autonomic balance is associated with group- and individual-level response patterns. Methods and results: Physiological signals from 112 participants (63 females, 21-79 years, including 25 with elevated resting blood pressure) collected whilst they listened to nine expressive versions of eight pieces of Western classical music were analysed using canonical correlation analysis. Listeners were stratified by their baseline sympathetic-parasympathetic balance. The first two canonical variates identified the dominant links between music and physiologic change points. We developed a new method for visually representing these couplings, termed change point connectivity graphs. Listeners with high parasympathetic tone showed greater vagal engagement in response to novel melodies and increased acoustic intensity, whereas those with elevated sympathetic drive exhibited amplified sympathetic responses. Novelty was the most consistent musical driver of autonomic change. Conclusion: These findings demonstrate that baseline autonomic activity might determine whether expressive music changes elicit parasympathetic engagement or sympathetic activation. The change point connectivity graphs open new pathways to selecting or controlling expressive music structures to support the achievement of targeted physiologic effects. Our framework is a step towards precision music therapeutics by enabling the selection or modulation of music features to produce autonomic effects for cardiovascular prevention, rehabilitation, and practice, including applications via wearable technologies.
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