The modulation of learning state in a biological associative memory: an in vitro, in vivo, and in computo study of object recognition in mammalian olfactory cortex

James M. Bower

Research output: Contribution to journalArticlepeer-review

Abstract

During learning of overlapping input patterns in an associative memory, recall of previously stored patterns can interfere with the learning of new patterns. Most associative memory models avoid this difficulty by ignoring the effect of previously modified connections during learning, by clamping network activity to the patterns to be learned. Through the interaction of experimental and modeling techniques, we now have evidence to suggest that a somewhat analogous approach may have been taken by biology within the olfactory cerebral cortex. Specifically we have recently discovered that the naturally occurring neuromodulator acetylcholine produces a variety of effects on cortical cells and circuits which, when taken together, can prevent memory interference in a biologically realistic memory model. Further, it has been demonstrated that these biological mechanisms can actually improve the memory storage performance of previously published abstract "neural network" associative memory models.

Original languageEnglish (US)
Pages (from-to)261-269
Number of pages9
JournalArtificial Intelligence Review
Volume7
Issue number5
DOIs
StatePublished - Oct 1 1993

Keywords

  • associative memory
  • modeling
  • neurobiology
  • olfaction
  • simulations

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence

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