The course provides an introduction to artificial neural networks in cognitive science, and the application of vector-space-modelling as a way to explore the information captured by such networks. The class will focus both on the theoretical foundations and the methodological implications of the presented approaches. Practice sessions, using toolboxes and functions in R, will be dedicated to the training and testing of neural networks, and the interrogation of pre-trained vector spaces. Examples of applications in the domains of memory, perception, language, attention, and social cognition will be provided.