title: Convergent and divergent functional connectivity patterns in schizophrenia and depression.
abstract: Major depression and schizophrenia are two of the most serious psychiatric disorders and share similar behavioral symptoms. Whether these similar behavioral symptoms underlie any convergent psychiatric pathological mechanisms is not yet clear. To address this issue, this study sought to investigate the whole-brain resting-state functional magnetic resonance imaging (MRI) of major depression and schizophrenia by using multivariate pattern analysis. Thirty-two schizophrenic patients, 19 major depressive disorder patients and 38 healthy controls underwent resting-state functional MRI scanning. A support vector machine in conjunction with intrinsic discriminant analysis was used to solve the multi-classification problem, resulting in a correct classification rate of 80.9% via leave-one-out cross-validation. The depression and schizophrenia groups both showed altered functional connections associated with the medial prefrontal cortex, anterior cingulate cortex, thalamus, hippocampus, and cerebellum. However, the prefrontal cortex, amygdala, and temporal poles were found to be affected differently by major depression and schizophrenia. Our preliminary study suggests that altered connections within or across the default mode network and the cerebellum may account for the common behavioral symptoms between major depression and schizophrenia. In addition, connections associated with the prefrontal cortex and the affective network showed promise as biomarkers for discriminating between the two disorders.
authors.affiliation: College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Yu
authors.forename: Hui
authors.initials: H
authors.lastname: Shen
authors.forename: Ling-Li
authors.initials: LL
authors.lastname: Zeng
authors.forename: Qiongmin
authors.initials: Q
authors.lastname: Ma
authors.forename: Dewen
authors.initials: D
authors.lastname: Hu
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000473:pathology / Q000503:physiopathology*; D001931:Brain Mapping; D002531:Cerebellum / Q000473:pathology / Q000503:physiopathology; D003865:Major Depressive Disorder / Q000473:pathology / Q000503:physiopathology*; D016002:Discriminant Analysis; D005260:Female; D006179:Gyrus Cinguli / Q000473:pathology / Q000503:physiopathology; D006624:Hippocampus / Q000473:pathology / Q000503:physiopathology; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008959:Models, Neurological; D015999:Multivariate Analysis; D009434:Neural Pathways / Q000502:physiology; D017397:Prefrontal Cortex / Q000473:pathology / Q000503:physiopathology; D012559:Schizophrenia / Q000473:pathology / Q000503:physiopathology*; D060388:Support Vector Machine; D013788:Thalamus / Q000473:pathology / Q000503:physiopathology; D055815:Young Adult