Learning and Memory: Computational Models

P. B. Sederberg, K. A. Norman

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations

Abstract

The goal of learning and memory research is to understand how we store and retrieve information based on our experiences. Computational models provide formal implementations of memory theories that attempt to predict both behavior and neural data. This article describes computational models of declarative memory, including episodic memory (memory for specific events) and semantic memory (memory for meanings), with a particular focus on the role of context in supporting both types of memory.

Original languageEnglish (US)
Title of host publicationEncyclopedia of Behavioral Neuroscience
PublisherElsevier Inc.
Pages145-153
Number of pages9
ISBN (Electronic)9780080914558
ISBN (Print)9780080453965
DOIs
StatePublished - Jan 1 2010

All Science Journal Classification (ASJC) codes

  • Medicine(all)
  • Neuroscience(all)

Keywords

  • Computational models
  • Context
  • Cortex
  • Episodic memory
  • Hippocampus
  • Learning
  • Memory
  • Neural networks
  • Recall
  • Recognition
  • Semantic memory
  • Synaptic plasticity

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