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动作电位是神经系统传递信息的主要方式之一,神经信息的相互传递和整合通常通过若干动作电位组成的放电序列来实现。获取神经元的放电信号(即锋电位信号)并且对其进行分类和分析对神经系统深层研究具有重要的意义。总结了神经元锋电位分类的常用方法,以及该项目所采用的主成分分析法的原理。阐述了利用虚拟仪器进行锋电位分类的主要思想,介绍了在LabVIEW软件环境下开发锋电位分类的虚拟仪器系统的原理,讲述了阈值分析、PCA分析、聚类、PCA分析显示等系统模块的开发过程。该系统具有锋电位信号的输入、显示、分类、分析、结果输出等功能。实验表明,该系统结果可靠、结构简洁、经济性好,能够用于科学研究。
Action potential is one of the main ways of transmitting information in the nervous system. The mutual transmission and integration of neural information is usually achieved through the discharge sequence of several action potentials. Obtaining the discharge signal of the neuron (ie, the spike signal) and classifying and analyzing it is of great significance to the deep study of the nervous system. Summarized the common method of neuron front potential classification, and the principle of principal component analysis used in this project. The main idea of using the virtual instrument to classify the front voltage is introduced. The principle of developing the virtual instrument system of the front potential classification in the LabVIEW software environment is introduced. The development of system modules such as threshold analysis, PCA analysis, clustering and PCA analysis is described process. The system has the front signal input, display, classification, analysis, the results of output and other functions. Experiments show that the system is reliable, simple and economical, and can be used for scientific research.