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On the control of automatic processes: a parallel distributed processing account of the Stroop effect.

J D Cohen1, K Dunbar, J L McClelland

  • 1Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213.

Psychological Review
|July 1, 1990
PubMed
Summary

Automatic processes are continuous and influenced by attention, challenging traditional views. A computational model demonstrates how practice strengthens processing pathways, affecting automaticity and performance, particularly in tasks like the Stroop effect.

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Area of Science:

  • Cognitive Psychology
  • Computational Neuroscience
  • Human Attention Studies

Background:

  • Traditional theories view automaticity as an all-or-none phenomenon, independent of attention.
  • Recent empirical data suggest automatic processes are continuous and subject to attentional control.

Purpose of the Study:

  • To revise traditional views of automaticity by presenting a new model of attention.
  • To propose that attributes of automaticity depend on processing pathway strength, which increases with training.

Main Methods:

  • Developed a computational model within a parallel distributed processing framework.
  • Combined the cascade mechanism with the backpropagation learning algorithm to simulate the Stroop task.
  • Modeled the time course of processing and effects of learning, including practice variations.

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Main Results:

  • Demonstrated that automatic processes are continuous and emerge gradually with practice.
  • The computational model successfully simulated performance in the standard Stroop task and its variants.
  • Showcased how stimulus-onset asynchrony, response set, and practice influence performance.

Conclusions:

  • Automaticity is not an all-or-none phenomenon but a continuous process influenced by attentional control.
  • Processing pathway strength, enhanced through training, is crucial for automaticity.
  • The presented model offers a framework for understanding attention, automaticity, and interference.