Functional neuroanatomy of intuitive physical inference
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PNAS-2016-Fischer-E5072-81.pdf
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1.52 MB
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Author(s)
Fischer, Jason T.
Mikhael, John G.
Tenenbaum, Joshua B
Kanwisher, Nancy
Date Issued
August 2016
Journal
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences (U.S.)
Citation
Fischer, Jason et al. “Functional Neuroanatomy of Intuitive Physical Inference.” Proceedings of the National Academy of Sciences 113, 34 (August 2016): E5072–E5081. © 2016 National Academy of Sciences
Version
Final published version
Abstract
To engage with the world - to understand the scene in front of us, plan actions, and predict what will happen next - we must have an intuitive grasp of the world's physical structure and dynamics. How do the objects in front of us rest on and support each other, how much force would be required to move them, and how will they behave when they fall, roll, or collide? Despite the centrality of physical inferences in daily life, little is known about the brain mechanisms recruited to interpret the physical structure of a scene and predict how physical events will unfold. Here, in a series of fMRI experiments, we identified a set of cortical regions that are selectively engaged when people watch and predict the unfolding of physical events - a "physics engine" in the brain. These brain regions are selective to physical inferences relative to nonphysical but otherwise highly similar scenes and tasks. However, these regions are not exclusively engaged in physical inferences per se or, indeed, even in scene understanding; they overlap with the domain-general "multiple demand" system, especially the parts of that system involved in action planning and tool use, pointing to a close relationship between the cognitive and neural mechanisms involved in parsing the physical content of a scene and preparing an appropriate action.
MIT Department
Center for Brains, Minds, and Machines
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
McGovern Institute for Brain Research at MIT
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1073/PNAS.1610344113
