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

Abstract:

: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.

journal_name

Trends Cogn Sci

authors

O'Reilly RC,Norman KA

doi

10.1016/s1364-6613(02)02005-3

subject

Has Abstract

pub_date

2002-12-01 00:00:00

pages

505-510

issue

12

eissn

1364-6613

issn

1879-307X

pii

S1364661302020053

journal_volume

6

pub_type

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