This chapter introduces the reader to studying psychological dynamics operating on network models. The chapter will illustrate such dynamics using the Ising model, an undirected network model for binary variables in which nodes mutually influence one-another. First, the chapter discusses the basics of the Ising model. Second, the chapter introduces the reader to dynamics emerging from the Ising model, such as polarization and hysteresis. These dynamics will be illustrated using the example of attitude networks. Third, the chapter will illustrate how the Ising model can be used to model cross-sectional phenomena as an alternative to latent trait theories. General intelligence will be used as an example for this illustration to show how the positive manifold and block structures in correlation matrices can arise from a network implemented in the Ising model.