Emotion effects on spatiotemporal brain–heart interactions with convergent cross mapping

Interactions linking the heart to changes in brain organization offer insights into how central and peripheral systems jointly contribute to affective processing. Conventional approaches to brain-heart interaction, which rely primarily on EEG rhythms and heart rate variability, fail to capture the heartbeat-resolved dynamics that characterize the bidirectional interaction between cortical and cardiac activity. We apply Convergent Cross Mapping (CCM), a nonlinear causality framework, to 32-channel EEG and single-lead ECG signals recorded during validated virtual reality (VR) videos designed to elicit positive or negative affect. By modeling heartbeat-evoked potentials (HEPs) and full cardiac waveforms as evolving dynamical systems, we observed pronounced directional asymmetry in emotion-related brain-heart interactions: descending coupling patterns were stronger, more sustained, and spatially focused than ascending effects. Positive and negative emotional conditions were associated with differential bidirectional coupling patterns, with preferential enhancement of descending cortical-to-cardiac interactions. Spatially, modulation was left-lateralized, with a concentration in frontal and central electrodes. These findings advance embodied models of affect by demonstrating that such interactions are both directionally asymmetric and hemispherically organized, positioning cardiac dynamics as an actively involved component of emotion-related brain-heart coordination.