Regional gray matter volume and structural network strength in somatic vs. non-somatic delusional disorders

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Background:Monothematic delusional disorders are characterized by a single tenacious belief. They provide a great opportunity to study underlying brain structures in the absence of confounding symptoms that accompany delusions in schizophrenia. Delusional beliefs include persecution, jealousy or somatic delusions including infestation. It is unclear whether specific delusional content is associated with distinct neural substrates.Methods:We used magnetic resonance imaging in patients presenting with somatic vs. non-somatic delusional disorders. Patients with delusional infestation (DI, n = 18), and individuals with non-somatic delusional disorders (n = 19) were included, together with healthy volunteers (n = 20). Uni- and multivariate techniques for structural data analysis were applied to provide a comprehensive characterization of abnormal brain volume at both the regional and neural network level.Results:Patients with DI showed lower gray matter volume in thalamic, striatal (putamen), insular and medial prefrontal brain regions in contrast to non-somatic delusional disorders and healthy controls. Importantly, these differences were consistently detected at regional and network level. Compared to healthy controls, patients with delusional disorders other than DI showed lower gray matter volume in temporal cortical regions.Conclusion:The data support the notion that dysfunctional somatosensory and peripersonal networks could mediate somatic delusions in patients with DI in contrast to delusional disorders without somatic content. The data also suggest putative content-specific neural signatures in delusional disorders and in delusion formation per se.HighlightsWe investigate brain structure in patients with and without somatic delusions.Regional brain volume and structural network strength were investigated.The data support the notion of peripersonal space dysfunction in somatic delusions.The data also suggest putative content-specific neural signatures.

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