Imaging biomarkers in functional neurological disorders
TL;DR
It is argued for a multi-modal approach integrating neuroimaging, genetics and computational methods to advance both the diagnosis and treatment of FND, highlighting alterations in brain regions involved in motor control, self-agency and emotion regulation.
Abstract
Abstract Recent advances in neuroimaging have significantly reshaped our understanding of functional neurological disorder (FND), shifting the focus from structural damage to dysfunctional brain networks. Building on Charcot's early intuition of a ‘functional lesion’, this review traces the evolution of neuroimaging research in FND, from its historical roots to current developments. We synthesize findings from structural and functional imaging studies, highlighting alterations in brain regions involved in motor control, self-agency and emotion regulation. Task-based fMRI studies have shown atypical activation in areas such as the supplementary motor area, dorsolateral prefrontal cortex and temporo-parietal junction, supporting the notion of impaired voluntary motor control. Additionally, changes in the amygdala and periaqueductal grey point to the role of emotional dysregulation. Structural imaging reveals grey and white matter alterations, while machine learning applied to resting-state connectivity shows promise for biomarker development. Emerging evidence also suggests that genetic and epigenetic factors—particularly within oxytocinergic and serotonergic systems—may contribute to individual vulnerability. We argue for a multi-modal approach integrating neuroimaging, genetics and computational methods to advance both the diagnosis and treatment of FND. This article is part of the discussion meeting issue ‘Digital healthcare for the management of functional neurological disorders’.