A coordinated animation (CA) depicts the (internal) operations of a model along with action in the modeled domain. This paper's CA involves neural network models as the internal system to animate. A range of situations, mainly for the movement of objects in a laboratory setting, constitute the modeled domain, effecting a model-domain combination that may be “ideal” for realizing CA in practice. The modeled domain entails human subjects or robots being given a set of assigned tasks that is too large to remember and carry out without an “external” memory aid or strategy; strategies are not given, but rather are to be learned. Animations depict cycles of activity subjects go through during learning. The capabilities of CA for verification and validation, for training in a context of multiple models, multiple studied domains, and in multi-disciplinary research are discussed.