Computational Diversity in a Formal Model of the Insect Olfactory Macroglomerulus

We present a model of the specialist olfactory system of selected moth species and the cockroach. The model is built in a semirandom fashion, constrained by biological (physiological and anatomical) data. We propose a classification of the response patterns of individual neurons, based on the temporal aspects of the observed responses. Among the observations made in our simulations a number relate to data about olfactory information processing reported in the literature; others may serve as predictions and as guidelines for further investigations. We discuss the effect of the stochastic parameters of the model on the observed model behavior and on the ability of the model to extract features of the input stimulation. We conclude that a formal network, built with random connectivity, can suffice to reproduce and to explain many aspects of olfactory information processing at the first level of the specialist olfactory system of insects.

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