a voxel-wise meta-analysis of the volumetric changes in functional neurological disorders

Context: functional neurological disorder (fnd) is common in neurology outpatient clinics, affecting approximately 6% of neurology patients. functional neurological disorder is characterized by motor and sensory symptoms that cannot be explained by organic or structural neurological issues. these symptoms often mimic those of recognized neurological conditions, making diagnosis and treatment complex. evidence acquisition: this study presents a comprehensive voxel-wise meta-analysis of structural brain changes in fnd to explore potential quantitative measurements that could serve as biomarkers for different fnd types. in this investigation, we systematically queried prominent academic databases using specific keywords: fnd, somatization disorder, and voxel-based morphometry (vbm) . additionally, we employed the brainmap database to identify vbm data pertaining to fnd. our meta-analysis, performed using es-sdm software, examined grey matter (gm) changes in fnd patients. we also assessed the robustness of the results via jackknife analysis and investigated unexplained variability using heterogeneity analysis. results: our meta-analysis revealed both positive and negative gm volumetric changes in different brain areas across various fnd types. the robustness of the results was confirmed, and the assessment of bias and publication bias yielded no significant concerns. conclusions: these findings offer valuable insights into the neuroanatomical basis of diverse functional disorders, providing potential biomarkers. moreover, the identified regions are associated with pain modulation, emotional processing, and cognitive functions, contributing to a better understanding of fnd pathophysiology.