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Related Experiment Videos

Parallel Processing Response Times and Experimental Determination of the Stopping Rule

Townsend1, Colonius

  • 1Indiana University

Journal of Mathematical Psychology
|February 25, 1998
PubMed
Summary

Exhaustive parallel models struggle to explain self-terminating processing effects. This study proves that non-super capacity parallel models cannot predict these critical effects, supporting self-terminating models.

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Area of Science:

  • Cognitive psychology
  • Computational modeling
  • Information processing

Background:

  • Previous research indicated limitations of serial and some parallel models in predicting self-terminating effects.
  • Self-terminating processing effects are frequently observed in experimental data.

Purpose of the Study:

  • To generalize "impossibility" theorems to a broader class of parallel models.
  • To demonstrate the inability of certain parallel models to account for self-terminating effects.

Main Methods:

  • Theoretical analysis and mathematical proof.
  • Generalization of existing impossibility theorems for computational models.
  • Analysis of constraints on parallel processing models.

Main Results:

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  • Proved that non-super capacity exhaustive parallel models cannot predict self-terminating effects.
  • Established conditions under which parallel models fail to account for these effects (target processing speed relative to non-targets).

Conclusions:

  • The findings strongly support the validity of self-terminating processing models.
  • Limitations of exhaustive parallel models in cognitive psychology are highlighted.
  • Experimental evidence for self-terminating effects is further corroborated.