Complementary Learning Systems
Article first published online: 5 DEC 2011
Copyright © 2011 Cognitive Science Society, Inc.
Special Issue: 2010 Rumelhart Prize Special Issue Honoring James L. McClelland
Volume 38, Issue 6, pages 1229–1248, August 2014
How to Cite
O’Reilly, R. C., Bhattacharyya, R., Howard, M. D. and Ketz, N. (2014), Complementary Learning Systems. Cognitive Science, 38: 1229–1248. doi: 10.1111/j.1551-6709.2011.01214.x
- Issue published online: 19 AUG 2014
- Article first published online: 5 DEC 2011
- Received 21 November 2010; received in revised form 5 April 2011; accepted 6 April 2011
- Neural network models
This paper reviews the fate of the central ideas behind the complementary learning systems (CLS) framework as originally articulated in McClelland, McNaughton, and O’Reilly (1995). This framework explains why the brain requires two differentially specialized learning and memory systems, and it nicely specifies their central properties (i.e., the hippocampus as a sparse, pattern-separated system for rapidly learning episodic memories, and the neocortex as a distributed, overlapping system for gradually integrating across episodes to extract latent semantic structure). We review the application of the CLS framework to a range of important topics, including the following: the basic neural processes of hippocampal memory encoding and recall, conjunctive encoding, human recognition memory, consolidation of initial hippocampal learning in cortex, dynamic modulation of encoding versus recall, and the synergistic interactions between hippocampus and neocortex. Overall, the CLS framework remains a vital theoretical force in the field, with the empirical data over the past 15 years generally confirming its key principles.