@article {4178, title = {An integrative computational architecture for object-driven cortex}, journal = {Current Opinion in Neurobiology}, volume = {55}, year = {2019}, month = {01/2019}, pages = {73 - 81}, abstract = {

Computational architecture for object-driven cortex

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{\textemdash}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.

}, issn = {09594388}, doi = {10.1016/j.conb.2019.01.010}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0959438818301995}, author = {Ilker Yildirim and Jiajun Wu and Nancy Kanwisher and Joshua B. Tenenbaum} }