ABSTRACT
Taste buds endure extreme changes in temperature, pH, osmolarity, so on. Even though taste bud cells are replaced in a short span, they contribute to consistent taste reception. Each taste bud consists of about 50 cells whose networks are assumed to process taste information, at least preliminarily. In this article, we describe a neural network model inspired by the taste bud cells of mice. It consists of two layers. In the first layer, the chemical stimulus is transduced into an irregular spike train. The synchronization of the output impulses is induced by the irregular spike train at the second layer. These results show that the intensity of the chemical stimulus is encoded as the degree of the synchronization of output impulses. The present algorithms for signal processing result in a robust chemical-sensing system.
