关键词: 脑功能网络, 动态特性, 状态演化, 时间自动机, 血氧依赖水平

Abstract: As a whole system the human brain constantly maintains changing in essence, but the researches about dynamic characteristics of human brain network which is based on functional Magnetic Resonance Imaging（fMRI） reconstruction technology are still in the early stage, and those methods used to describe the brain system discipline are always be qualitative but not quantitative. A modeling method using time automaton theory is discussed for the description of human brain network dynamical characteristics and evolution process in this paper. Firstly the description of all the brain areas at one single time point is presented by analyzing the Blood Oxygen Level Dependent（BOLD） signal, then the unsupervised clustering technology is used to get all the status and the status transformation regular pattern with time changing is observed. Finally a time automation evolution model is given to describe the evolution process of brain network state quantitatively on the basis of all these works. The experimental results show that this method can give a precise description of the state transition and evolution rules of the human brain network. This method is universal to different subjects and able to identify the abnormal evolution process of subjects, and it also provides a theoretical basis for the further study of dynamic characteristics of brain network.

Key words: brain function network, dynamic characteristics, state evolution, timed automata, Blood Oxygen Level Dependent（BOLD）