TRACING ONE NEURON ACTIVITY FROM THE INSIDE OF ITS STRUCTURE

As new areas of neural computing are trying to make at least one step beyond the definition of digital computing, the neural networks field, was developed around the idea of creating models of real neural systems. The key point is based on learning rather than programming. We designed the model we present in this paper, based on the the needs introduced by new trends in neural computing. We created a model for information processing inside neurons. It is constructed, from a neural inside point of view, as a feedback system that controls the flow of information passing through the neuron. Processes of internal neural learning take place. We translated them as processes of learning at a€ moleculara€ level. Our work is disseminated into the construction of an algorithm of learning, that we introduce in the end of this paper.