Modeling event-related heart period responses

Cardiac rhythm is generated locally in the sinoatrial node, but modulated by central neural input. This may provide a possibility to infer central processes from observed phasic heart period responses (HPR). Currently, operational methods are used for HPR analysis. These methods embody implicit assumptions on how central states influence heart period. Here, we build an explicit psychophysiological model (PsPM) for event-related HPR. This phenomenological PsPM is based on three experiments involving white noise sounds, an auditory oddball task, and emotional picture viewing. The model is optimized with respect to predictive validity—the ability to separate experimental conditions from each other. To validate the PsPM, an independent sample of participants is presented with auditory stimuli of varying intensity and emotional pictures of negative and positive valence, at short intertrial intervals. Our model discriminates these experimental conditions from each other better than operational approaches. We conclude that our PsPM is more sensitive to distinguish experimental manipulations based on heart period data than operational methods, and furnishes a principled approach to analysis of HPR