Research On Dynamic Low-frequency Amplitude Fluctuation And Structural Network Based On Patients With Bipolar Disorder And Major Depression

Due to the extremely high similarity between the clinical manifestations of patients with major depression and patients with bipolar disorder,it is difficult to distinguish between patients with two diseases.More and more studies are exploring the clinical and cognitive characteristics of depressed patients and the activity characteristics of specific regions of the brain And the close relationship of anatomy.The purpose of this study was to use the resting state fMRI of patients with major depression and bipolar disorder to detect whether there is a correlation between the depression characteristics and the local characteristics and structural connections of the dynamic low-frequency oscillation of the BOLD signal.In the study of depression characterization and dynamic low-frequency fluctuation(dALFF),we found that the value of dALFF in MDD and BD increased compared with normal subjects.The areas where rumination and self were positively correlated with dALFF occurred in patients with MDD.The right anterior ventral prefrontal cortex part,this result provides another effective evidence for supporting the prefrontal cortex activity involving self and ruminant emotional processing.The dALFF value was found to increase significantly in the left caudate nucleus of BD patients.For the reward perception dimension,the amplitude of the dynamic low-frequency oscillation of the BOLD signal of the left caudate nucleus of a BD patient can predict the reward perception score.Since the caudate nucleus is an important node of the brain reward network,this finding shows that the activity of the reward network can be used to predict the reward perception characteristics of individual differences,implying that the brain regions with emotional processing and processing functions will perceive negative self and reward perception.When using functional image data to analyze spontaneous local time-varying neuronal activity,the biological model of brain structure network connection a nd depression characterization has aroused great interest of researchers in revealing its neurobiological basis.In the study of depression characterization and brain structure network connection,we found that the structured networks of the three groups o f subjects all exhibited the characteristics of the small world network.Besides this,the structured network of the patient group,the small-world topological attribute indicators,the global efficiency,and the global assortativity showed differences in MDD and BD when compared with normal subjects.Among them,the global assortativity of MDD and BD is lower than that of healthy controls.This means that the stability of the structural network of MDD and BD patients is destroyed,and the internal structure may be damaged.In addition,we also calculate the local topological attributes of the network.We found that the two groups of patient showed longer shortest path length and weaker node efficiency in the default mode network and frontal cortex relative to the healthy controls.Moreover,the shortest path length of the fusiform gyrus,right anterior cingulate gyrus has a significant correlation with the clinical Hamilton depression score.These results imply that there is a loss of fibers which derive from these brain regions,which lead to a reduction in the efficiency of information processing and these loss could reflect depression.Our results are sufficient to show that there are differences on instrinsic brain activity and structural connection between MDD and BD and the characterization of depression is closely related to spontaneous local time-varying neuronal activity and structural connection,and provide further evidence for finding the neurophysiological mechanism of depression.