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A crossed random effects diffusion model for speeded semantic categorization decisions.

Joachim Vandekerckhove1, Steven Verheyen, Francis Tuerlinckx

  • 1Department of Psychology, University of Leuven, Belgium. joachim.vandekerckhove@med.kuleuven.be

Acta Psychologica
|December 8, 2009
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Summary
This summary is machine-generated.

This study uses a novel diffusion model to analyze choice reaction times (RTs) in semantic categorization. Typicality influences information uptake, while lexicographic properties affect encoding time, offering a clearer understanding of cognitive processes.

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Area of Science:

  • Cognitive Psychology
  • Computational Neuroscience
  • Psycholinguistics

Background:

  • Choice reaction times (RTs) are frequently used to measure typicality in semantic categorization.
  • Item properties beyond typicality also influence RTs, necessitating more nuanced analytical approaches.

Purpose of the Study:

  • To deconfound various sources of variability in choice RTs using a tailored process model.
  • To link specific aspects of the cognitive response process to distinct item properties.

Main Methods:

  • Application of a tailored diffusion model to a speeded semantic categorization task.
  • The model incorporates crossed random effects for items and participants, allowing application with limited repeated measures.
  • Analysis of how different item properties predict parameters of the diffusion model.

Main Results:

  • Typicality measures were found to predict the rate of information uptake during decision-making.
  • Lexicographic measures were identified as predictors of stimulus encoding time.
  • Accessibility measures did not reliably predict any component of the decision process.

Conclusions:

  • The diffusion model successfully disentangles cognitive processes underlying choice RTs.
  • Distinct item properties map onto specific stages of information processing, including encoding and evidence accumulation.
  • This framework provides a more precise understanding of semantic categorization beyond simple RT measures.