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Updated: Jun 13, 2025

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Published on: February 4, 2022
Functional Connectivity Gradients Reveal Altered Hierarchical Cortical Organization in Functional Neurological
Background:
Neuroimaging studies of functional neurological disorder (FND), a condition at the intersection of psychiatry and neurology, often rely on discrete connections or parcellations that may obscure the brain's functional network architecture. This study applied a gradient-based approach to examine macroscale cortical organization in FND.
Methods:
We analyzed resting-state functional magnetic resonance imaging (fMRI) data from 64 patients with mixed FND (FND-mixed), 61 age- and sex-matched healthy controls (HCs), and 62 psychiatric controls (PCs) matched on age, sex, depression, anxiety, and post-traumatic stress disorder (PTSD) severity. Functional connectivity gradients were computed to capture dominant axes of cortical organization. Between-group comparisons were conducted for the top three 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, and antidepressant use, and were post-hoc adjusted for depression, anxiety, and PTSD-severity, and for childhood maltreatment.
Results:
The FND-mixed group showed alterations across all three gradients relative to 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. Analyses revealed overlapping and distinct patterns across subtypes.
Conclusions:
We provide novel evidence of atypical hierarchical brain organization in FND, highlighting gradient-based approaches for identifying mechanistically-relevant altered functional brain organization.
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