Information communication in brain based on memory loop neural circuit

We have developed a time-shift map of the brain, which shows/ visualizes signal such as EEG and MEG etc. is transmitted/ propagated at each brain part where in each frequency band action potential information of time-to-time is transmitted to and processed at exact remote portion. Assuming the memory is composed of loop neural circuit in the cerebral cortex, we have also shown a feasibility of self organization of loop neural circuit for memory, association, and abstraction, which is algorithmically realizable and able to account well the time-shift map. 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. We give in this paper how a memory content expressed by loop circuit shape is copied to blank area of cerebral cortex etc. using simulation of small scale loop circuit model with four neuron cells and back-propagation learning algorithm. 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 unifledly the information processing function of the brain.