The diagnosis of FND is often a tedious process. Patients undergo multiple consultations for the same symptoms with different physicians until the correct diagnosis is found. This highlights the need to investigate objective biomarkers to support clinicians in their daily clinical routine.
Resting-state functional magnetic resonance imaging (fMRI) has been shown to be a promising tool in the search for biomarkers in neuropsychiatric disorders.
The Resting-state study aims at investigating resting-state functional connectivity as a potential biomarker for FND. By applying a multivariate classification approach on whole-brain resting-state functional connectivity data, we aim at discriminating FND patients from healthy controls.
As a first step towards a clinical application, we aim at validating this method in a multicentre setting, and to confirm that this classification tool can be utilized in clinics worldwide.