The Structure of Systematicity in the Brain

TL;DR

This paper explores how the human brain achieves systematicity and generativity by separating structural and content information in different cortical pathways, and discusses neural network models and hippocampal roles in this process.

Contribution

It proposes a neural basis for systematicity involving parietal and temporal cortex pathways and relates this to neural network models and hippocampal functions.

Findings

Neural pathways in parietal cortex encode abstract structure.

Temporal cortex pathways encode specific content.

Neural network models demonstrate separation of structure and content.

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 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.