Regeneration of Gamma Oscillations in Large-scale Neural Network with Complicated Structure Based on CUDA

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.