Does computation provide a model for creativity? An epistemological perspective in neuroscience.

In 1939 Alan Turing, a major scholar in the field of mechanical computation, described a system whose computational power was beyond that of a discrete, finite state machine (Turing Machine). The composition of this system was likely the first example of what is now called an hybrid computational system. Since then, development of neural networks and brain automata has made aware that forms of computation might exist that are likely to go beyond Turing's limits. Natural systems, like the central nervous system in Mammals and man, are likely to use such a type of computation, especially to perform highly integrating activities, like feedback controls and mental creative processes. The latter are usually understood as processes that involve infinitary procedures, ending up in a complex information network, the computational maps, in which both digital, Turing-like computation and continuous, analog forms of calculus are expected to occur. Pictorial representation may be a fruitful example, mostly metaphorical, to analyze the use of this hybrid forms of computation by higher order computational maps, and the possible role of these types of computational processes in painting creativity is briefly analyzed in comparing 15th vs 16th century Renaissance Art. An open challenge for neuroscience in the 21st century is to clarify whether a hybrid neural learning network might represent a reasonable clue to scientifically interpret the theme of "creativity".