抄録
The Brain is recognized as a very large-scale network system in which the basic element is a neuron. To investigate this mechanism, we performed a simulation of typically 9x9 2D mesh arrayed neural network with Hebbian leaning. Synaptic weight of each neuron is more activated, which optimize the path of spike propagation, when the stimulated neuron or frequency of stimulation is increased. We found that there is a difference in the necessary number of learnings of weights to reach spike to goal neuron by increasing the number of stimulated neuron and frequency of stimulation.
