On how the computational paradigm can help us to model and interpret the neural function

Virtually from its origins, with Alan Turing and W.S. McCulloch’s formulations, the use of the computational paradigm (CP) as a conceptual and theoretical framework to help to explain Neurophysiology and Cognition has aroused controversy. Some of the objections raised, relating to its constitutive and formal limitations, still prevail. We believe that others stem from the assumption that its objectives are different from those of a methodological approach to the problem of neural modeling.In this work we start from the hypothesis that it is useful to look at the neuronal circuits assuming that they are the neurophysiological support of a calculus, whose full description requires considering, at least, three levels of organization: circuits and mechanisms, neurophysiological symbols and knowledge and emerging behavior. We also stress the figure of the external observer and the need to distinguish between two description domains in each level: the level’s own domain and the domain of the external observer. Finally, we describe a procedure for using the computational paradigm qualitatively in order to try to do “reverse neurophysiology”, drawing on two abstraction processes that link the calculus at signal level with cognition. We end by considering the real limitations (constitutive) and apparent (wrong objectives) of the CP and its integrating and non-exclusive nature.