An information geometrical method is developed for characterizing or classifying neurons in cortical areas, whose spike rates fluctuate in time. When the interspike intervals of a spike sequence of a neuron obey a gamma process with a time-variant spike rate and a fixed shape parameter, the information geometry for semiparametric estimation has given the optimal method from the statistical viewpoint. Recently a more suitable statistical model for interspike intervals is proposed, which have an absolute refractory period. This work extends the information geometrical method and derives the optimal method for the new model. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Komazawa, D., Ikeda, K., & Funaya, H. (2009). Information geometry of interspike intervals in spiking neurons with refractories. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5506 LNCS, pp. 731–736). https://doi.org/10.1007/978-3-642-02490-0_89
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