Introduction to the Special Section on Theory and Data in Categorization: Integrating Computational, Behavioral, and Cognitive Neuroscience Approaches

Stephan Lewandowsky*, Thomas J. Palmeri, Michael R. Waldmann

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

6 Citations (Scopus)

Abstract

This special section brings together behavioral, computational, mathematical, and neuroimaging approaches to understand the processes underlying category learning. Over the past decade, there has been growing convergence in research on categorization, with computational mathematical models influencing the interpretation of brain imaging and neuropsychological data, and with cognitive neuroscience findings influencing the development and refinement of models. Classic debates between single-system and multiple-memory-system theories have become more nuanced and focused. Multiple brain areas and cognitive processes contribute to categorization, but theories differ markedly in whether and when those neurocognitive components are recruited for different aspects of categorization. The articles in this special section approach this issue from several diverse angles.

Original languageEnglish
Pages (from-to)803-806
Number of pages4
JournalJournal of Experimental Psychology: Learning, Memory, and Cognition
Volume38
Issue number4
DOIs
Publication statusPublished - Jul 2012

Research Groups and Themes

  • Memory

Keywords

  • category learning
  • computational models
  • cognitive neuroscience
  • single versus multiple memory systems
  • MEMORY-SYSTEMS
  • TASK INTERFERENCE
  • CATEGORY
  • MODELS
  • CLASSIFICATION
  • RECOGNITION
  • WORKING
  • PERFORMANCE
  • SIMILARITY
  • EXCEPTION

Fingerprint

Dive into the research topics of 'Introduction to the Special Section on Theory and Data in Categorization: Integrating Computational, Behavioral, and Cognitive Neuroscience Approaches'. Together they form a unique fingerprint.

Cite this