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Related Experiment Video

Updated: May 16, 2026

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

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

Published on: August 29, 2018

Contingent attentional capture by conceptually relevant images.

Brad Wyble¹, Charles Folk, Mary C Potter

¹Department of Psychology, The Pennsylvania State University, University Park, PA 16802, USA. bwyble@gmail.com

Journal of Experimental Psychology. Human Perception and Performance

|November 21, 2012

Summary

Attentional capture can be influenced by conceptual information, not just basic features. This study shows that understanding the meaning of an image can rapidly guide visual attention.

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Last Updated: May 16, 2026

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Published on: January 23, 2017

Area of Science:

Cognitive Psychology
Neuroscience
Visual Perception

Background:

Attentional capture describes unintentional attention shifts to salient or task-relevant distractors.
Contingent capture occurs when stimuli match task-defined attentional settings.
Previous research focused on low-level features like color and motion.

Purpose of the Study:

To investigate if contingent capture extends to superordinate conceptual information.
To determine the speed and nature of conceptual contingent capture.
To explore how conceptual meaning influences attentional shifts.

Main Methods:

Participants performed a task requiring attention to change on each trial.
Stimuli included natural images with varying conceptual categories (e.g., sports equipment, marine animals).
Reaction times and accuracy were measured to assess attentional shifts.

Main Results:

Contingent capture was observed for superordinate conceptual information.
This effect occurred rapidly, within 200 ms.
The capture was spatial and contingent on trial-by-trial attentional settings.

Conclusions:

Conceptual information can rapidly drive shifts in visuospatial attention.
Natural images are decoded for meaning within a single fixation to guide attention.
This extends the understanding of attentional capture beyond low-level features.