Magnetoencephalogram Analysis Based On Entropy And Phase Slope Index

As an affective disorder,depression is becoming more and more common in modern society.It has caused great harm to human body and mind,and has attracted extensive attention.However,according to the existing research results,we can not thoroughly explain the mechanism of depression.At the same time,there is no reliable quantitative index for the diagnosis of depression.In view of the above situation,this paper analyzes depression by using a variety of nonlinear dynamic methods.This paper selects magnetoencephalogram as the research data.Because magnetoencephalogram has the advantages of non-invasive,high temporal and spatial resolution and easy detection,it is very suitable for the analysis of depression.Therefore,this paper will use magnetoencephalogram as the experimental data and use a variety of nonlinear dynamic methods to analyze the differences between depression patients and normal people,trying to find the effective quantitative indicators of depression.The content of the paper can be roughly divided into the following parts:(1)Magnetoencephalogram analysis of depression based on symbolic relative entropyThis chapter first introduces the basic principle of symbolic relative entropy,including the basic principle of symbolic principle and relative entropy.Then,in order to find the appropriate data length and coding length,experiments are carried out in this chapter,and the data is set as1500 and the coding length is set as 5.Then this chapter calculates the symbolic relative entropy of each magnetoencephalogram channel through the forward probability and backward probability of the calculation process,and finds the mean value of the symbolic relative entropy of the whole channel,which reflects the average level of the subject’s symbolic relative entropy in the whole brain region.Through the comparison of the symbolic relative entropy of the whole brain region between the patients with depression and the healthy subjects,we find that there are significant differences between the two groups,Moreover,the symbolic relative entropy of patients with depression is greater than that of normal people,and the symbolic relative entropy reflects the average energy dissipation level of subjects,which shows that on the whole,the energy dissipation of patients with depression is significantly higher than that of healthy subjects,which also shows that the symbolic relative entropy can effectively distinguish the average energy dissipation degree of physiological processes of patients with depression and healthy people.Finally,this chapter compares the two groups of subjects from the perspective of the difference of symbolic relative entropy between brain regions,and finds that there are still significant differences between the two groups in five brain regions,which proves the effectiveness of the algorithm,but there is no significant relationship between the difference of brain regions between the two groups,that is,it is impossible to find the prominent brain regions of the difference of symbolic relative entropy between patients with depression and healthy subjects,This also shows that there is little difference in the average energy dissipation level of each brain region between the two groups.(2)Magnetoencephalogram analysis of depression based on multi-scale cross model entropyThis chapter discusses the characteristics of multi-scale cross model entropy between patients with depression and healthy people.The results show that there are significant differences in multi-scale cross model entropy between patients with depression and healthy people.The entropy of patients with depression is always lower than that of normal people,indicating that the activity of brain physiological activities in patients with depression is low;Moreover,by analyzing the relative difference of entropy between patients with depression and normal people in different brain regions,we found that the relative difference between the two groups was the largest in frontal region.(3)Magnetoencephalogram analysis of depression based on phase slope indexThis chapter explores the differences in phase slope index between patients with depression and healthy people.The experimental results show that there is a significant difference in the phase slope index between patients with depression and healthy people in the flow directions of FP,CP and Op.Moreover,in order to describe the information flow of each brain region as a whole,the net flux of information flow in each brain region is calculated.The results show that there are significant differences between the two groups in area C,area F and area p of the five brain regions.