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Related Experiment Video

Updated: Jun 15, 2026

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking
05:58

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

Published on: August 29, 2018

The problem state: a cognitive bottleneck in multitasking.

Jelmer P Borst1, Niels A Taatgen, Hedderik van Rijn

  • 1Department of Artificial Intelligence, University of Groningen, Postbus 407, 9700 AK Groningen, the Netherlands. jpborst@ai.rug.nl

Journal of Experimental Psychology. Learning, Memory, and Cognition
|March 3, 2010
PubMed
Summary
This summary is machine-generated.

Multitasking interference occurs when tasks share a problem state, a task’s intermediate representation. Computational models using threaded cognition confirm this problem state bottleneck, not cognitive load or phonological loop limitations.

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Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

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Area of Science:

  • Cognitive Psychology
  • Human-Computer Interaction
  • Computational Neuroscience

Background:

  • Theories of multitasking face challenges in predicting task interference.
  • Interference is often linked to shared cognitive resources.
  • The problem state, an intermediate task representation, is a key factor.

Purpose of the Study:

  • To investigate task interference specifically related to the problem state.
  • To test the prediction that interference is maximal when multiple tasks require a problem state.
  • To differentiate problem state bottleneck from other potential interference sources like cognitive load or phonological loop limitations.

Main Methods:

  • Three experiments were conducted involving concurrent subtraction and text entry tasks.
  • Tasks were manipulated to require or not require maintaining a problem state.
  • Computational cognitive models based on threaded cognition and ACT-R were developed.

Main Results:

  • A significant overadditive interaction demonstrated maximal interference when both concurrent tasks required a problem state.
  • Experiments 2 and 3 ruled out cognitive load and phonological loop bottlenecks as primary causes of interference.
  • Computational models successfully replicated the observed interference patterns, supporting the problem state bottleneck hypothesis.

Conclusions:

  • Task interference during multitasking is significantly influenced by the demand on the problem state.
  • A dedicated problem state bottleneck, rather than general cognitive load or phonological limitations, explains observed interference.
  • Threaded cognition theory provides a robust framework for modeling multitasking behavior and interference.