An integrative computational architecture for object-driven cortex

• Main Authors: Yildirim, Ilker (Author), Wu, Jiajun (Author), Kanwisher, Nancy (Author), Tenenbaum, Joshua B (Author)
• Other Authors: McGovern Institute for Brain Research at MIT (Contributor), Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences (Contributor)
• Format: Article
• Language: English
• Published: Elsevier BV, 2020-04-15T20:02:28Z.
• Subjects: Article
• Online Access: Get fulltext

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
NSF STC (award no.: CCF-1231216)
ONR MURI (no. N00014-13-1-0333)
NIH (no. DP1HD091947)