Networks are found throughout nature. They are studied in numerous areas of science and are used in the design and implementation of technology. Because of finite processing speeds and transmission of signals over distances, the dynamics of such networks are inherently time-delayed. In this talk we consider the global stability of dynamical networks with distributed and non-distributed delays. In the case of non-distributed delays we show that the problem simplifies to considering networks without time-delays. By extending this technique we further describe how one can reduce the dimension of a network (dynamical system) to gain improved estimates of the network´s (system´s) global stability. This approach of "restricting" a network is illustrated by applications to various classes of Cohen-Grossberg neural networks.