A new classification of neuron models for random inputs on bifurcation structures

Cortical regularly spiking neurons are classified into two classes, Class I and Class II, by their firing frequencies. We investigated the statistical characteristics of spike sequences of Class I and II neurons stimulated by uncorrelated fluctuations by two interspike interval statistics; coefficient of variation and coefficient of skewness. As a result, the interspike interval statistics of Class I and II neurons are different. Moreover, even if the neurons belong to the same class, if the precise bifurcation structures of the neurons are different, the statistics exhibit different characteristics. The results indicate insufficiency to classify neurons by the firing frequencies and necessity to classify neurons by the precise bifurcation structures