Association and Abstraction on Neural Circuit Loop and Coding

We show in this paper a feasibility of self organization of loop neural circuit for memory, association, and abstraction, which is algorithmically realizable. First we assume the memory is composed of loop neural circuit in the cerebral cortex. Then, we give how a memory content expressed by loop circuit shape is copied to blank area of cerebral cortex as well as how a path between memory loops with the same shape is found by broadcasting based on the classical Hebbian law. The generated sequence from the transmitting loop corresponding to the memory is a code by pseudo random sequence which is now popular in spread spectrum communication or mobile CDMA. Further, we show how the association and abstraction of the memory can be realized by the neural circuit. The loop circuit self-organizing model seems to be reasonable in the sense of hardware realizable, having large number of codes corresponding to various memory contents, and able to access to other memories associatively. Thus, the model seems able to account well unifiedly the information processing function of the brain.