Modeling higher level processing functions inherent to the human brain

The most significant feature of the information processing in the brain might be the autonomy based on the motivation and self reward (MSR) to form a processor sequence intending to find out the solution to a problem one is facing. In this paper, we show some preliminary ideas to incorporate the concept of MSR in designing brain-like information processing means, based on physiological and engineering points of view. We propose a hybrid neural network model as an extension of Hebb´s rule, to be hypothesized for the function of association areas in the cerebral cortex. The generated neural network model is tested on the problem of segmentation of brain magnetic resonance images