In 1970, an eminent Japanese roboticist, Masahiro Mori, proposed the "uncanny valley" curve to describe the emotional response of humans to nonhuman agents. His hypothesis was that as an agent is made more humanlike, the observer's familiarity does not increase as one would intuit, but falls into a ``valley of eeriness,'' when the agent closely yet imperfectly impersonates a human being. With progress in computer graphics allowing increasingly realistic rendering of forms and motion, the uncanny valley has become a high-stakes concern of the entertainment industry. The uncanny valley hypothesis also poses a fundamental scientific question: What do people perceive when they view human motion and how are those perceptions affected by realistic, nearly realistic, or caricatured human motion? With the growing accuracy of functional magnetic resonance imaging (fMRI) measurement and analysis techniques, there is a new tool with which to answer these questions. The PIs are using fMRI, eye tracking, and traditional perceptual metrics to explore the existence of and causes of the uncanny valley. Motion capture data (including skin and muscle deformation), keyframed animations, high speed video, and clips from feature films are used to construct a set of stimuli with which to answer these questions. The outcomes of this research is a greater understanding of the perception of animated human motion which will inform practitioners and researchers in computer graphics and allow them to focus on the aspects of human animation that will have the greatest impact. The research has broad impacts on science and society. For example, the work conducted here has applicability to the scientific understanding of autism, a devastating neurodevelopmental disorder that effects social functioning in multiple domains including the perception of other people's actions and intentions.