大脑局部电位信号与呼吸的关系模型研究

由于脑电波信号由无数神经放电构成，使得研究大脑与生理动作刺激之间的关系极具挑战性。根据脑电波与呼吸之间的机理特征，该文采用小波变换分解并重构了局部电位信号的主要成分，采用主成份方法分析了与呼吸相关的脑电波主要成分，分析了子波段与呼吸的强弱关联关系与周期性关系。引入径向基函数神经网络方法辨识了脑系统的呼吸与局部电位信号关系模型。

Research on Respiratory and Local Field Potential of Brain

Electroencephalogram (EEG) signals are made up of innumerable nerve discharges, so it is full of challenges to study the relationship between brain and physiological stimulus. According to the mechanism characteristics of EEG signals and breathing, the theory of wavelet transformation is used in this paper to decompose and reconstruct the main components of local potential signals. This paper analyzes the major component of EEG signals related to breathing by the application of main composition analytic means, and shows the associated relationships and the periodic relationship between sub-bands and breathing. The radial basis function (RBF) neural networks method is introduced to identify the relational models of the breathing of brain system and local potential signals.