The Structure of Systematicity in the Brain

Abstract

A hallmark of human intelligence is the ability to adapt to new situations by applying learned rules to new content (systematicity) and thereby enabling an open-ended number of inferences and actions (generativity). Here, we propose that the human brain accomplishes these feats through pathways in the parietal cortex that encode the abstract structure of space, events, and tasks and pathways in the temporal cortex that encode information about specific people, places, and things (content). Recent neural network models show how the separation of structure and content might emerge through a combination of architectural biases and learning, and these networks show dramatic improvements over previous models in the ability to capture systematic, generative behavior. We close by considering how the hippocampal formation may form integrative memories that enable rapid learning of new structure and content representations.

Document Details

Document Type
Pub Defense Publication
Publication Date
Mar 24, 2022
Source ID
10.1177/09637214211049233

Entities

People

  • Charan Ranganath
  • Jacob L. Russin
  • Randall C. O'Reilly

Organizations

  • Department of Computer Science, University of Oxford
  • National Institute of Mental Health
  • Office of Naval Research
  • University of California

Tags

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Neural Network Machine Learning.
  • Neuroscience

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Space