Relationships Between Brain Functional Connectivity and Resting Cardiac Autonomic Profiles in Functional Neurological Disorder: A Pilot Study

BackgroundFunctional neurological disorder (FND) is associated with alterations in functional brain networks, yet relationships between peripheral autonomic physiology and brain architecture remain poorly characterized. This pilot study examined associations between cardiac autonomic metrics and resting-state functional connectivity (rsFC) in FND. MethodsTwenty females with FND and 23 age-matched female psychiatric controls (PCs) completed questionnaires, 10-min resting photoplethysmography recordings, and same-day resting-state fMRI. Interbeat interval (IBI) and heart rate variability (HRV) metrics were extracted. Whole-brain rsFC was quantified using weighted-degree [centrality]. Within-group analyses tested associations between cardiac autonomic metrics and weighted-degree rsFC separately in FND and PC cohorts, adjusting for age, head motion, and antidepressant/{beta}-blocker use - while applying a cluster-wise correction. ResultsCardiac (IBI and HRV) metrics did not differ between FND and PC cohorts, and these metrics did not correlate with FND symptom severity, somatic symptom burden, affective symptoms, or childhood trauma. In FND, shorter IBI (i.e., faster resting heart rate) correlated with increased weighted-degree rsFC in bilateral supplementary motor area (SMA) and right precentral/superior frontal regions, whereas higher HRV primarily correlated with decreased weighted-degree rsFC in the bilateral SMA, mid-cingulate cortex, and right amygdala, anterior insula, and lateral orbitofrontal cortex. In PCs, autonomic-rsFC associations were more spatially restricted to the anterior/mid-cingulate and SMA. ConclusionIn FND, individual differences in resting autonomic physiology related to the centrality of brain areas that are part of the central autonomic, salience, and allostatic-interoceptive networks. These findings suggest that the relationship between autonomic physiology and network architecture may be important in FND.