Independent component analysis of the resting-state brain functional MRI study in adults with bipolar depression

Bipolar depression is a common psychiatric diagnosis that describes a category of mood disorders. This disease threatens human's life and quality of life with its high morbidity and mortality. Bipolar depression is characterized by the diversity of clinical symptoms (manic symptoms, depressive symptoms and psychotic symptoms) and courses of complex and is easily confused with schizophrenia, major depression, so the treatment is very difficult. We aimed to examine the abnormality in resting-state brain activity in the default-mode network (DMN) in adults with depression episodes of bipolar disorder (BD) by using independent component analysis (ICA) method. ICA is a statistical technique which linearly decomposes a multidimensional data vector into components that are as statistically independent as possible. Twenty-two patients with BD depression and the same amount of the healthy subjects participated in the functional magnetic resonance imaging (fMRI) scans. Our results showed that resting-state middle temporal gyrus, middle frontal gyrus, precuneus, and caudate in DMN were significantly greater in the BD compared to the control group (NC). They also had superior temporal gyrus, inferior parietal lobule, cingulated gyrus, fusiform and postcentral gyrus in DMN that were greater in NC compared to BD. These results were consistent with a model of BD that involves dysfunction in the prefrontal-limbic networks and the associated striatal systems.