Abstract
Gamma oscillations have been not only found in many biology experiments but also regenerated in many small neural network models. However, whether gamma oscillations can be regenerated in large-scale neural network with complicated structure is still an open problem. In order to deal with this problem, this paper constructs a large-scale neural network model with multi-layer columns. Based on the existing CUDA parallel algorithm and a synapse optimization algorithm, we design a novel parallel algorithm for simulation of the large-scale complicated neural network with multi-layer column structure. The simulation results verify that gamma oscillations can be regenerated in large-scale neural network with complicated structure.
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