Modeling memory: what do we learn from attractor neural networks?

C R Acad Sci III. 1998 Feb-Mar;321(2-3):249-52. doi: 10.1016/s0764-4469(97)89830-7.

Abstract

In this paper we summarize some of the main contributions of models of recurrent neural networks with associative memory properties. We compare the behavior of these attractor neural networks with empirical data from both physiology and psychology. This type of network could be used in models with more complex functions.

Publication types

  • Review

MeSH terms

  • Humans
  • Learning / physiology*
  • Memory / physiology*
  • Models, Neurological*
  • Models, Psychological*
  • Nerve Net / physiology*
  • Neuronal Plasticity / physiology