| Paper: | PS-2A.1 |
| Session: | Poster Session 2A |
| Location: | Symphony/Overture |
| Session Time: | Friday, September 7, 17:15 - 19:15 |
| Presentation Time: | Friday, September 7, 17:15 - 19:15 |
| Presentation: |
Poster
|
| Publication: |
2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvania |
| Paper Title: |
Evidence for an Intuitive Physics Engine in the Human Brain |
| Manuscript: |
Click here to view manuscript |
| DOI: |
https://doi.org/10.32470/CCN.2018.1132-0 |
| Authors: |
Sarah Schwettmann, Josh Tenenbaum, Nancy Kanwisher, MIT, United States |
| Abstract: |
Humans demonstrate a remarkable ability to infer physical properties of objects and predict physical events in dynamic scenes. These abilities have been modeled as probabilistic simulations of a mental physics engine akin to 3D physics engines 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 represent quantities 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. The masses of depicted objects could be decoded from parietal and frontal brain regions previously implicated in intuitive physics (Fischer et al., 2016). Crucially, this decoding was invariant to the scenario revealing the object’s mass, as well as the the material, friction, and amount of motion of the object. These regions may support a generalized engine for intuitive physics where this invariant representation of mass serves as a key variable. |
