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Related Experiment Videos

Connectionist and diffusion models of reaction time.

R Ratcliff1, T Van Zandt, G McKoon

  • 1Psychology Department, Northwestern University, Evanston, Illinois 60208, USA.

Psychological Review
|June 23, 1999
PubMed
Summary

The diffusion model accurately explains signal detection data, including error reaction times. Connectionist models showed limitations, highlighting the diffusion model

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Area of Science:

  • Cognitive Psychology
  • Computational Neuroscience

Background:

  • Connectionist models like GRAIN and brain-state-in-a-box are influential in cognitive modeling.
  • Reaction time research traditionally focuses on decision processes over time.

Purpose of the Study:

  • To evaluate the explanatory power of two connectionist frameworks and a diffusion model.
  • To assess model performance on signal detection task data, including reaction times and response probabilities.

Main Methods:

  • Signal detection task data analysis.
  • Comparison of GRAIN, brain-state-in-a-box, and diffusion models.
  • Analysis of response probabilities, reaction times (correct and error), and reaction time distributions.

Main Results:

  • The diffusion model successfully accounted for all data aspects, notably error reaction times.
  • Connectionist models demonstrated adequacy in some areas but had significant limitations.
  • One connectionist model showed similarity to the diffusion model.

Conclusions:

  • The diffusion model is advanced by these findings, offering a robust explanation for signal detection data.
  • The study validates reaction time research as a critical area for testing computational models of decision-making.
  • Connectionist assumptions regarding decision generation over time require further refinement and testing.

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