Proceedings of the Annual Meeting of the Cognitive Science Society

Humans demonstrate a remarkable ability to infer physical properties of objects and predict physical events in dynamicscenes. These abilities have been modeled as probabilistic simulations of a mental physics engine akin to 3D physicsengines used in computer simulations and video games (Battaglia, Hamrick & Tenenbaum 2013; Sanborn, Mansinghka &Griffiths 2013), but it is unknown if and how such a physics engine is implemented in the brain. Does the brain representquantities corresponding to the key latent variables of physical objects that contribute to their dynamics? To find out,we used multivariate pattern classification analyses of fMRI data from subjects viewing videos of dynamic objects. Themass of depicted objects could be decoded, across physical scenarios and object materials, from brain regions previouslyimplicated in intuitive physics. This invariant representation of mass may serve as a key variable in a generalized enginefor intuitive physics.