Both unipolar depression (UD) and bipolar depression (BD) have obvious depression symptoms.Clinically,UD and BD are often misdiagnosed.Recently,MR imaging (MRI) has been used to detect biomarkers distinguishing BD and UD.This study will summarize previous studies on detecting biomarkers to distinguish BD and UD based on structural MRI,diffusion tensor imaging (DTI) and functional MRI.Based on the current issues of previous studies,we further make prospective development of future studies in this field.

A number of studies have indicated that disorders of consciousness result from multifocal injuries as well as from the impaired functional and anatomical connectivity between various anterior forebrain regions. However, the specific causal mechanism linking these regions remains unclear. In this study, we used spectral dynamic causal modeling to assess how the effective connections (ECs) between various regions differ between individuals. Next, we used connectome-based predictive modeling to evaluate the performance of the ECs in predicting the clinical scores of DOC patients. We found increased ECs from the striatum to the globus pallidus as well as from the globus pallidus to the posterior cingulate cortex, and decreased ECs from the globus pallidus to the thalamus and from the medial prefrontal cortex to the striatum in DOC patients as compared to healthy controls. Prediction of the patients' outcome was effective using the negative ECs as features. In summary, the present study highlights a key role of the thalamo-basal ganglia-cortical loop in DOCs and supports the anterior forebrain mesocircuit hypothesis. Furthermore, EC could be potentially used to assess the consciousness level.
Adult ; Bayes Theorem ; Connectome ; Consciousness Disorders ; diagnostic imaging ; physiopathology ; Female ; Humans ; Machine Learning ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Neural Pathways ; diagnostic imaging ; physiopathology ; Prognosis ; Prosencephalon ; diagnostic imaging ; physiopathology ; Young Adult