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An integrative computational architecture for object-driven cortex

Author(s)
Yildirim, Ilker; Wu, Jiajun; Kanwisher, Nancy; Tenenbaum, Joshua B
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Abstract
Objects in motion activate multiple cortical regions in every lobe of the human brain. Do these regions represent a collection of independent systems, or is there an overarching functional architecture spanning all of object-driven cortex? Inspired by recent work in artificial intelligence (AI), machine learning, and cognitive science, we consider the hypothesis that these regions can be understood as a coherent network implementing an integrative computational system that unifies the functions needed to perceive, predict, reason about, and plan with physical objects—as in the paradigmatic case of using or making tools. Our proposal draws on a modeling framework that combines multiple AI methods, including causal generative models, hybrid symbolic-continuous planning algorithms, and neural recognition networks, with object-centric, physics-based representations. We review evidence relating specific components of our proposal to the specific regions that comprise object-driven cortex, and lay out future research directions with the goal of building a complete functional and mechanistic account of this system. ©2019
Date issued
2019-04
URI
https://hdl.handle.net/1721.1/124676
Department
McGovern Institute for Brain Research at MIT; Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Journal
Current opinion in neurobiology
Publisher
Elsevier BV
Citation
Yildirim, Ilker, Jiajun Wu, Nancy Kanwisher, and Joshua B. Tenenbaum, "An integrative computational architecture for object-driven cortex." Current opinion in neurobiology 55 (April 2019): p. 73-81 doi 10.1016/J.CONB.2019.01.010 ©2019 Author(s)
Version: Author's final manuscript
ISSN
1873-6882
0959-4388

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