The application of complexity algorithm to brain function image

YANG Yuxuan; XUE Li; TAO Ling; QIAN Zhiyu; YU Yun

doi:10.19529/j.cnki.1672-6278.2018.02.10

Abstract：To use the complexity analysis to extract and analyze the functional information of the brain.The complexity analysis was used to extract and analyze the function information of normal human brain fMRI images,and was compared with the common anal-ysis methods.First, based on the sample entropy and the Hearst exponential calculation,complexity analysis was validated in the measure of the functional activity of the brain.Then regional homogeneity method and complexity algorithm were used to calculate the brain activity in resting state,and the results were compared and analyzed.Finally, the cognitive differences for the whole brain and de-fault network between men and women were analyzed based on complexity algorithm.There was a significant negative correlation be-tween the sample entropy and the Hurst index,it was believed that the sample entropy could represent the change of brain neural func-tion activity.The brain activation areas extracted by complexity algorithm and regional homogeneity method tended to be consistent. There were obvious gender differences for functional cognition in default network based on complexity analysis,which was consistent with the results of the related literature.The complexity analysis can be applied to the processing of brain function,and analyze the characteristics of brain neural function.