The brain as a symbol-processing machine

The knowledge accumulated about the biochemistry of the synapsis in the last decades completely changes the notion of brain processing founded exclusively over an electrical mechanism, toward that supported by a complex chemical message exchange occurring both locally, at the synaptic site, as well as at other localities, depending on the solubility of the involved chemical substances in the extracellular compartment. These biochemical transactions support a rich symbolic processing of the information both encoded by the genes and provided by actual data collected from the surrounding environment, by means of either special molecular or cellular receptor systems. In this processing, molecules play the role of symbols and chemical affinity shared by them specifies the syntax for symbol manipulation in order to process and to produce chemical messages. In this context, neurons are conceived as message-exchanging agents. Chemical strings are produced and stored at defined places, and ionic currents are used to speed up message delivery. Synaptic transactions can no longer be assumed to correspond to a simple process of propagating numbers powered by a factor measuring the presynaptic capacity to influence the postsynaptic electrical activity, but they must be modeled by more powerful formal tools supporting both numerical and symbolic calculations. It is proposed here that formal language theory is the adequate mathematical tool to handle such symbolic processing. The purpose of the present review is therefore: (a) to discuss the relevant and recent literature about trophic factors, signal transduction mechanisms, neuromodulators and neurotransmitters in order (b) to point out the common features of these correlated processes; and (c) to show how they may be organized into a formal model supported by the theory of fuzzy formal languages (d) to model the brain as a distributed intelligent problem solver.