`Physiological´ time in the analysis and modelling of real and artificial neural nets

It is proposed that existing neurobiological data on the properties of single nerve cells and of the systems formed by them will allow, when reproduced in models, a new paradigm of the functioning of neuronal nets, based on the inner time scale concept to be introduced. The concept of inner (physiological) time provides a new approach to modeling processes in neuronal networks. Different inner time scales may be associated with different coordinate systems, and decomposition into coordinates may allow one to extract various invariant measures from the input information. It is noted that in the case of the description of neuronal network behavior in terms of phase packages the time variable is not explicitly present at all, whereas in the case of using stability theory techniques, it is interesting to analyze the process dynamics on a large time scale