Abstract：Neural population encoding and analysis of spike train play an important role in the field of neural inforamtion processing. In this study, a classification method of spike train is proposed based on high-order multiple Possion model, and a mathematic deduction is made in the spike instensity distribution, accuracy of matching and integration strategy, respectively. Finally, 20 trails, as a traing set, are applied to experiment of U maze of mouse. The result demonstrates that the accuracy rate of the classification method is about 97%.
樊一娜, 郎波, 危辉. 基于贝叶斯原理的多维Spike Train分类预测模型[J]. 电子与信息学报, 2013, 35(7): 1619-1623.
Fan Yi-Na, Lang Bo, Wei Hui. A Classification and Prediction Model of Multi Spike Train Based on Bayes Theory. , 2013, 35(7): 1619-1623.
2013, Vol. 35 
