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 journalArticle

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 1993
Externally publishedYes

Fingerprint

Object recognition
Modulation
Data storage equipment
learning
neural network
Cortex
Associative
Object Recognition
biology
interference
Neural networks
Memory Model
Networks (circuits)
interaction
performance
evidence

Keywords

  • associative memory
  • modeling
  • neurobiology
  • olfaction
  • simulations

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence

Cite this

@article{a7ab36b0693a4eac955307062e02056d,
title = "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",
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.",
keywords = "associative memory, modeling, neurobiology, olfaction, simulations",
author = "Bower, {James M.}",
year = "1993",
month = "10",
doi = "10.1007/BF00849054",
language = "English (US)",
volume = "7",
pages = "261--269",
journal = "Artificial Intelligence Review",
issn = "0269-2821",
publisher = "Springer Netherlands",
number = "5",

}

TY - JOUR

T1 - The modulation of learning state in a biological associative memory

T2 - an in vitro, in vivo, and in computo study of object recognition in mammalian olfactory cortex

AU - Bower, James M.

PY - 1993/10

Y1 - 1993/10

N2 - 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.

AB - 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.

KW - associative memory

KW - modeling

KW - neurobiology

KW - olfaction

KW - simulations

UR - http://www.scopus.com/inward/record.url?scp=0027678674&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0027678674&partnerID=8YFLogxK

U2 - 10.1007/BF00849054

DO - 10.1007/BF00849054

M3 - Article

AN - SCOPUS:0027678674

VL - 7

SP - 261

EP - 269

JO - Artificial Intelligence Review

JF - Artificial Intelligence Review

SN - 0269-2821

IS - 5

ER -