Dynamical Field Theory (DFT) offers a framework for thinking about representation-in-the-moment in neural systems and changes in thinking over learning and development. Dynamic Neural Fields are formalizations of how neural populations represent the continuous dimensions that characterize perceptual features, movements, and cognitive decisions. DFT has been used across a variety of contexts including studies of working memory, word learning, executive function, and autonomous robotics. One obstacle for researchers wishing to use DFT has been that the mathematical and technical skills required to make these concepts operational are not part of the standard repertoire of cognitive scientists. The goal of this tutorial is to provide the training and tools to overcome this obstacle. We will provide a systematic introduction to the central concepts of DFT and their grounding in both Dynamical Systems concepts and neurophysiology. We will provide all needed background and give participants hands-on experience using interactive simulators in MATLAB.