Differential Analysis Of Cognitive Impairment Based On EEG Plateau Hypoxia

In recent years,due to the support of national policies and the improvement of quality of life,more and more people go to the plateau area for work,tourism,mountain climbing,scientific experiments,etc..However,high altitude areas with high altitude,low pressure and low oxygen,and extremely harsh environment bring great challenges to the people living in Tibet.Even after overcoming the temporary high-altitude stress response,long residency can damage the cognitive functions of the human brain,such as short-term memory and executive control functions.Therefore,it is important to study the brain damage caused by hypoxia in long-term migrants at high altitude.EEG records the changes of brain waves during brain activity with high temporal resolution,which can capture the process of instantaneous dynamic changes in the brain.Moreover,EEG acquisition equipment is portable and easy to operate,which is an important technique for studying people at high altitude,and numerous studies have also commonly observed EEG abnormalities in subjects under hypoxic environments.However,existing highaltitude EEG studies have used traditional analysis methods to extract the power spectrum of EEG signals,energy values,etc.These traditional analysis methods only discuss the simple characteristics of EEG signals,and do not probe deeply into the internal coordination of the brain,nor do they give full play to the advantages of high temporal resolution of EEG.Therefore,it is meaningful to use EEG technique to analyze brain dynamics changes in the temporal dimension during brain cognition and to explore the impairment of brain cognitive function at high altitude.In this paper,we improved the edge probability update rule of the original network prediction model based on the existing functional brain network reorganization prediction model for high altitude EEG data.The network reorganization prediction model was used to simulate the evolution of functional brain networks in high-altitude subjects,to compare and analyze the differences of brain network reorganization models between different altitudes,and to reveal the basis of changes in brain network dynamics in high-altitude subjects.In addition,in order to further analyze the differences of functional brain networks in high altitude sedentary subjects,four microstate types of EEG in high altitude subjects were calculated,and then the four microstates were fitted back to the original data to calculate the differences of microstate familiarity between different altitudes,to analyze the kinetic changes in the brains of high altitude sedentary subjects,to further explore the differences in the cognitive processes of high and low altitude subjects,and to provide a reference for future high altitude injury rehabilitation treatment is provided as a reference.The specific contents include.(1)The raw EEG data of high-altitude subjects were preprocessed to calculate the dynamic changes of the mean phase-locked value PLV between electrodes at different frequency bands,and the differences in PLV values between each altitude were comparatively analyzed.It was found that the strongest functional connectivity of the brain functional network was reached at about 300 ms after stimulation in the alpha frequency band,and the brain network at this time was most distinctly different between altitudes,which is consistent with the previous This is consistent with the P300 effect studied previously.(2)Using a combination of sliding window technique and complex networks,dynamic brain networks were constructed for EEG data in alpha band with electrodes as nodes and phaselocked values(PLV)between electrodes as edges,and the feature path length,clustering coefficients,graph density,and global efficiency properties of brain networks were extracted for analysis,and it was found that as the altitude increased,the integration separation properties of brain network properties all relatively The integration separation properties of brain network attributes decreased with increasing altitude.(3)Based on the iteration of the brain functional network before 200 ms of stimulation,the evolution process of brain network in the cognitive process was simulated,and the brain network reorganization prediction model was improved according to the characteristics of high-altitude EEG data,and the accuracy of the network reorganization prediction model was proved to reach 98.95%.The network abnormalities caused by high altitude exposure were revealed.(4)Four basic microstate types were extracted from the EEG data of high-altitude subjects,and the microstates were fitted back to the original data,and the properties of duration,frequency of occurrence,coverage,and transition rate between microstates were analyzed for the four microstate types at three different altitudes.The differences in the cognitive process at high altitude were further analyzed under the perspective of microstates.