Cortico-hippocampal interaction and adaptive stimulus representation: A neurocomputational theory of associative learning and memory

Mark Gluck, Catherine Myers, Martijn Meeter

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Computational models of the hippocampal region link psychological theories of associative learning with their underlying physiological and anatomical substrates. Our approach to theory development began with a broad description of the computations that depend on the hippocampal region in classical conditioning (Gluck & Myers, 1993, 2001). In this initial model, the hippocampal region was treated as an Information-processing system that transformed stimulus representations, compressing (making more similar) representations of inputs that co-occur or are otherwise redundant, while differentiating (or making less similar) representations of inputs that predict different future events. This model led to novel predictions for the behavioral consequences of hippocampal-region lesions in rodents and of brain damage in humans who have amnesia or are in the earliest stages of Alzheimer's disease. Many of these predictions have, since been confirmed by our lab and others. Functional brain imaging studies have provided further supporting evidence. In more recent computational modeling, we have shown how some aspects of this proposed information-processing function could emerge from known anatomical and physiological characteristics of the hippocampal region, including the entorhinal cortex and the septo-hippocampal cholinergic system. The modeling to date lays the groundwork for future directions that increase the depth of detail of the biological modeling, as well as the breadth of behavioral phenomena addressed. In particular, we are working now to reconcile these kinds of incremental associative learning models with other models of the hippocampal region that account for the rapid formation of declarative memories.

Original languageEnglish (US)
Pages (from-to)1265-1279
Number of pages15
JournalNeural Networks
Volume18
Issue number9
DOIs
StatePublished - Jan 1 2005

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Automatic Data Processing
Learning
Psychological Theory
Data storage equipment
Entorhinal Cortex
Functional Neuroimaging
Classical Conditioning
Amnesia
Information Systems
Cholinergic Agents
Rodentia
Alzheimer Disease
Brain
Imaging techniques
Substrates
Direction compound

All Science Journal Classification (ASJC) codes

  • Cognitive Neuroscience
  • Artificial Intelligence

Cite this

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Cortico-hippocampal interaction and adaptive stimulus representation : A neurocomputational theory of associative learning and memory. / Gluck, Mark; Myers, Catherine; Meeter, Martijn.

In: Neural Networks, Vol. 18, No. 9, 01.01.2005, p. 1265-1279.

Research output: Contribution to journalArticle

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