Using diffusion models to understand clinical disorders

Corey N. White, Roger Ratcliff, Michael W. Vasey, Gail McKoon

Research output: Contribution to journalArticlepeer-review

173 Scopus citations

Abstract

Sequential sampling models provide an alternative to traditional analyses of reaction times and accuracy in two-choice tasks. These models are reviewed with particular focus on the diffusion model (Ratcliff, 1978) and how its application can aid research on clinical disorders. The advantages of a diffusion model analysis over traditional comparisons are shown through simulations and a simple lexical decision experiment. Application of the diffusion model to a clinically relevant topic is demonstrated through an analysis of data from nonclinical participants with high- and low-trait anxiety in a recognition memory task. The model showed that after committing an error, participants with high-trait anxiety responded more cautiously by increasing their boundary separation, whereas participants with low-trait anxiety did not. The article concludes with suggestions for ways to improve and broaden the application of these models to studies of clinical disorders.

Original languageEnglish (US)
Pages (from-to)39-52
Number of pages14
JournalJournal of Mathematical Psychology
Volume54
Issue number1
DOIs
StatePublished - Feb 2010

Keywords

  • Anxiety
  • Depression
  • Diffusion model
  • Errors
  • Lexical decision
  • Psychopathology
  • Reaction time
  • Recognition memory
  • Sequential sampling models
  • Two-choice tasks

ASJC Scopus subject areas

  • General Psychology
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Using diffusion models to understand clinical disorders'. Together they form a unique fingerprint.

Cite this