A Classification and Prediction Model of Multi Spike Train Based on Bayes Theory

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%.