Computational framework for behavioural modelling of neural subsystems

This paper presents a new approach to the problem of modelling living system dynamics. Our point of view claims the fact that behind the biological apparent complexity, a hidden simplicity may appear when a suitable modelling is developed. The framework is inspired on the computing features of biological systems by involving a set of elementary standard behaviours that can be combined in order to emulate more complex behaviours. The algebraic formalization is based on both a recursive primitive operation defined by a table which models the elementary behaviours and a multilevel operating mode that carries out behaviour combinations. A parametric architecture implements the model, providing a good trade-off between time delay calculation and memory requirements. In this paper, the simulation of neural subsystems is considered as an application. The comparison with other simulation techniques outlines the capabilities of our method to provide an accurate modelling together with a very simple circuit implementation.