2021/08/07 by Randall C. O’Reilly, Charan Ranganath, O'Reilly, Randall C. +3 · 1 citation
Neuroscience · #FOS: Biological sciences #Memory and Neural Mechanisms #Neurons and Cognition (q-bio.NC)
paper · pdf · doi:10.48550/arxiv.2108.03387
openalex publication_date 2021/08/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.