Hippocampal and neocortical contributions to memory: Advances in the complementary learning systems framework

Randall C. O'Reilly, Kenneth A. Norman

Research output: Contribution to journalReview articlepeer-review

249 Scopus citations


The complementary learning systems framework provides a simple set of principles, derived from converging biological, psychological and computational constraints, for understanding the differential contributions of the neocortex and hippocampus to learning and memory. The central principles are that the neocortex has a low learning rate and uses overlapping distributed representations to extract the general statistical structure of the environment, whereas the hippocampus learns rapidly using separated representations to encode the details of specific events while minimizing interference. In recent years, we have instantiated these principles in working computational models, and have used these models to address human and animal learning and memory findings, across a wide range of domains and paradigms. Here, we review a few representative applications of our models, focusing on two domains: recognition memory and animal learning in the fear-conditioning paradigm. In both domains, the models have generated novel predictions that have been tested and confirmed.

Original languageEnglish (US)
Pages (from-to)505-510
Number of pages6
JournalTrends in Cognitive Sciences
Issue number12
StatePublished - Dec 1 2002
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Neuropsychology and Physiological Psychology
  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience


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