Research On The EEG Entropy And Network Characteristics In Interictal And Ictal Periods Of Epilepsy

Epilepsy is a chronic neurological disease caused by abnormal discharge of neurons,and its main clinical symptoms are paroxysmal and recurrent.The suddenness of epilepsy will not only cause harm to oneself,but may also cause danger to the people around;in addition,repeated seizures will cause damage to the neurons in the patient’s brain,as well as abnormal connections and information transmission in various brain regions.However,the current research on the changes in the characteristics of different stages of epilepsy is still insufficient,especially in the aura period before the seizure and the recovery period after the seizure.More in-depth research is required.Therefore,it is particularly important to study the physiological and pathological mechanisms of epilepsy patients in different stages.In this paper,based on the electroencephalogram(EEG)data from 10 minutes before the onset to 10 minutes after the onset,this paper conducted an in-depth study of the non-linear characteristic changes and brain network mechanisms in the interictal and ictal periods of epilepsy patients,aiming to more comprehensively Understand the changes of EEG signals and brain networks in different stages of epilepsy patients,and reveal the physiological and pathological mechanisms of epilepsy from a new perspective,so as to provide more effective means and methods for clinical treatment and intervention.The specific content of this research is as follows:1.Analysis of EEG characteristics in different stages of epilepsy based on Fuzzy Entropy(FE).We use FE to measure brain complexity and flexibility in different stages of epilepsy.The research results show that under the five frequency bands,the FE value in the pre-seizure period is the largest,followed by the post-seizure period,and the FE value in the seizure is the smallest.Subsequently,this study statistically analyzed the differences in FE at different stages,and the results showed that the significant differences in FE between the preictal and postictal periods were mainly concentrated in the low frequency bands,namely the delta frequency band and theta frequency band;The lateictal than mid-ictal relationship was significantly stronger,consistent with the topographic results.Finally,in order to explore the brain damage caused by repeated epileptic seizures,this study further analyzed the changes in FE in patients with multiple epileptic seizures.The results showed that as the number of epileptic seizures increased,the entropy values of both interictal and ictal periods showed a decreasing trend,which indicated that repeated epileptic seizures would have a cumulative effect on brain damage.This study reveals the changes in brain activity during and between seizures in epileptic patients from the perspective of brain complexity and flexibility,which will help provide effective auxiliary means for clinical monitoring,treatment and intervention of epilepsy.2.Research on the brain network mechanism of different stages of epilepsy.In this chapter,the coherence(COH)method is first used to construct the time-varying brain networks of different stages of epilepsy patients,and the statistical analysis of the topological differences of brain networks in different stages is carried out.The results showed that compared with the interictal period,the long-range connections of the brain network were reduced and the local connections were increased.At the same time,the differences in network topology showed that the differences in brain networks at different stages were mainly concentrated in high-frequency bands,specifically manifested in the enhancement of network connections during epileptic seizures,and the weakening of network connections after the seizures ended.Then,the difference of network attributes at different stages was counted,and the results showed that the results were consistent with the differences of network topology.Finally,in order to explore the network mechanism of repeated epileptic seizures,this study observed the changes of network attributes in patients with multiple seizures.The results showed that with the increase of the number of seizures,the length of the characteristic path showed an increasing trend,and the small-world attribute and clustering coefficient,global efficiency and local efficiency show a decreasing trend,indicating that as the number of seizures increases,the efficiency of the brain decreases,and the abnormal connection is further enhanced.This chapter explains the impact of recurrent epilepsy on patients from the perspective of brain network.To sum up,this paper analyzes the nonlinear characteristics and network characteristics of the interictal and ictal EEG data of epileptic patients from the perspective of FE and brain network,which provides a basis for the study of the mechanism of epileptic seizures and the development of new treatment methods.Provides new ideas and directions.