Interspike interval statistics of the neurons that exhibit the supercritical Hopf bifurcation

概要

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We evaluated statistical characteristics of spike trains of neurons that exhibit a supercritical Hopf bifurcation by higher order statistical coefficients, a coefficient of variation and a coefficient of skewness, and showed that the estimated statistical coefficients are different from those of neurons that exhibit a subcritical Hopf bifurcation. Then, we compared the statistical coefficients of spike trains observed from cortical neurons, and showed that the neurons that exhibit the supercritical Hopf bifurcation require temporally correlated inputs to reproduce the statistical characteristics of the cortical neurons. The results indicate that it is necessary to introduce a detailed classification of neurons based on the bifurcation types of neurons. In engineering application, artificial neural networks often show high ability to solve several real life problems, for example, the pattern recognition and the combinatorial optimization problems. Although the classification or the bifurcation structure of the neurons have not been brought into the artificial neural network, an appropriate choice of an element neuron with such concept might give much advantages to solve the engineering problems with high efficiency.