Functional Connectivity Gradients Reveal Altered Hierarchical Cortical Organization in Functional Neurological Disorder.

BACKGROUND

Neuroimaging studies of functional neurological disorder (FND), a core neuropsychiatric condition, often rely on discrete connections or parcellations that may obscure the brain's functional network architecture. In this study, we applied a gradient-based approach to examine macroscale cortical organization in FND.

METHODS

We analyzed resting-state functional magnetic resonance imaging data from 64 patients with mixed FND (FND-mixed), 61 age- and sex-matched healthy control participants (HCs), and 62 psychiatric control participants (PCs) matched on age, sex, depression, anxiety, and posttraumatic stress disorder (PTSD) severity. Functional connectivity gradients were computed to capture dominant axes of cortical organization. Between-group comparisons were conducted for the top 3 gradients, and associations with symptom severity were investigated. Subtype-specific patterns in functional motor disorder (n = 49) and functional seizure (n = 24) were also examined. Analyses controlled for age, sex, antidepressant use, and head motion and were post hoc adjusted for depression, anxiety, and PTSD severity, as well as for childhood maltreatment.

RESULTS

The FND-mixed group showed alterations across all 3 gradients compared with HCs and PCs. Gradient 1 revealed increased values in sensorimotor regions, reflecting a shift toward more association-like connectivity. Gradient 2 showed altered differentiation between sensory systems. Gradient 3 exhibited reduced functional separation between representational and modulatory regions, with prominent shifts in the anterior cingulate cortex. Several regions displaying between-group differences also showed correlations with FND and somatic symptom severity. Exploratory analyses revealed overlapping and distinct patterns across subtypes versus control groups.

CONCLUSIONS

We provide novel evidence of atypical hierarchical brain organization in FND, highlighting gradient-based approaches for identifying mechanistically relevant altered functional brain organization.