Gordon Bower Lecture- Intuitive Physical Reasoning in the Human Brain

Nancy Kanwisher · May 29, 2026

Visual scene understand requires more than a list of the objects present in the scene and their locations. To understanding a scene, plan action on it, and predict what will happen next we must extract the relationships between objects (e.g., support and attachment), their physical properties (e.g., mass and material), and the forces acting upon them. One view from Tenenbaum and his students is that we do this with the use of a mental “physics engine” that represents this information and runs forward simulations to predict what will happen next. Over the last several years we have been testing this idea using fMRI and intracranial recordings. I will review evidence that certain brain regions in the parietal and frontal lobes (but not the ventral visual pathway) behave as expected if they implement a mental physics engine: they respond more strongly when deciding about physical than visual properties and when viewing video clips depicting physical versus social events (Fischer et al, 2016), and they contain scenario-invariant information about object mass inferred from motion trajectories (Schwettmann et al, 2019), the stability of a configuration of objects (Pramod et al, 2022), and whether two objects are in contact with each other (Pramod et al 2025). Perhaps most tellingly, these regions produce a similar pattern of response when a collision event is predicted, as when a collision event is actually observed, as expected if these brain regions run forward simulations of what will happen next (Pramod et al 2025). Most recently, in a collaboration with Richard Andersen’s lab at Caltech, we have had the opportunity to record individual neurons in posterior parietal cortex of human participants who are paralyzed and have volunteered for BMI research. This work has revealed that the same individual neurons exhibit each of the key signatures of intuitive physical reasoning that we have observed with fMRI: selective engagement by physical versus perceptual tasks, selective engagement by physical versus social videos, and a lack of increased response with working memory demands. We are hopeful that the increased spatial and temporal resolution of these recordings will enable us in future to test computational models of intuitive physical reasoning in the human brain.