Brain-heart coupling in tourette syndrome: a precision functional mapping study of discordant siblings

Tourette syndrome (TS) is a neurodevelopmental disorder characterized by motor and vocal tics that are modulated by internal physiological state and interoceptive state, including premonitory urges and associated changes in short-timescale parasympathetic variability. Since tic expression is thought to be linked to fluctuations in autonomic state, understanding how brain networks integrate physiological signals may provide insight into the neural mechanisms contributing to tic generation and suppression. In recent years, there has been increasing interest in understanding interactions between the brain and autonomic physiology, given their shared central role in shaping cognition, emotion, and behavior. Methodological advances have enabled the study of brain-heart coupling, yet much of this work has focused on static or region-based approaches, limiting insight into how autonomic fluctuations are integrated within dynamic, large-scale brain networks. Here, we examined time-resolved brain-heart interactions using densely sampled resting-state fMRI data and concurrent pulse oximetry in two sibling pairs (n = 4) discordant for Tourette syndrome (TS). Using two targeted network analyses organized around interoceptive/urge awareness and inhibitory control/action regulation processes, we quantified coupling between pulse-derived RMSSD and between-network functional connectivity using sliding-window analyses and Bayesian linear mixed-effects models. We observed marked individual variability in functional network organization and autonomic measures. The most consistent observation was a pattern of opposing coupling directions between individuals with and without TS: those with TS showed positive associations between pulse-derived RMSSD with connectivity between internal-state and attentional networks, as well as among action-related systems, while unaffected siblings showed positive associations along broader integrative pathways linking internal-state and action-control networks. These preliminary findings generate hypotheses regarding individualized patterns of brain-heart coupling in TS and illustrate the potential value of integrating individualized network mapping with time-resolved physiological measures in clinical populations.