Transdiagnostic differences in the resting-state functional connectivity of the prefrontal cortex in depression and schizophrenia

Abstract

Background: Depression and schizophrenia are two of the most serious psychiatric disorders. They share similar symptoms but the pathology-specific commonalities and differences remain unknown. This study was conducted to acquire a full picture of the functional alterations in schizophrenia and depression patients.

Methods: The resting-state fMRI data from 20 patients with schizophrenia, 20 patients with depression and 20 healthy control subjects were collected. A data-driven approach that included local functional connectivity density (FCD) analysis combined with multivariate pattern analysis (MVPA) was used to compare the three groups.

Results: Based on the results of the MVPA, the local FCD value in the orbitofrontal cortex (OFC) can differentiate depression patients from schizophrenia patients. The patients with depression had a higher local FCD value in the medial and anterior parts of the OFC than the subjects in the other two groups, which suggested altered abstract and reward reinforces processing in depression patients. Subsequent functional connectivity analysis indicated that the connection in the prefrontal cortex was significantly lower in people with schizophrenia compared to people with depression and healthy controls.

Limitation: The systematically different medications for schizophrenia and depression may have different effects on functional connectivity.

Conclusions: These results suggested that the resting-state functional connectivity pattern in the prefrontal cortex may be a transdiagnostic difference between depression and schizophrenia patients.

Keywords: Depression; Functional connectivity; Machine learning; Prefrontal cortex; Schizophrenia.