Abstract: The exponential synchronization of stochastic fuzzy Cohen-Grossberg neural networks with reaction diffusion term and impulsive effect is investigated. Using Lyapunov functional theory, stochastic differential equation theory, \rm It\hato^'formula and inequality methods, some new sufficient conditions for the addressed neural network model is obtained based on the p-norm. It is also found that the existence of the stochastic perturbation term can restrain the synchronization of the addressed neural network model. However, the existence of the reaction diffusion term can promote the synchronization of the addressed neural network model.