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Related Experiment Video

Updated: Jul 14, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Top-down-driven grouping overrules the central attentional bias.

Karina J Linnell¹, Glyn W Humphreys

¹Department of Psychology, Goldsmiths College, University of London, London, UK. k.j.linnell@gold.ac.uk

Journal of Experimental Psychology. Human Perception and Performance

|June 15, 2007

Summary

Top-down knowledge of target features can override spatial selection biases in visual search. This finding suggests that knowing what to look for helps guide attention, even when distractors are closer to the center.

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Last Updated: Jul 14, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

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Published on: January 23, 2017

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Published on: July 5, 2015

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Published on: August 29, 2018

Area of Science:

Cognitive Psychology
Visual Perception
Attention

Background:

A central bias in spatial selection is hypothesized to explain reduced search efficiency as targets move further from fixation.
This bias occurs when distractors are closer to the fixation point than the target.

Purpose of the Study:

To investigate the role of top-down knowledge in visual search efficiency.
To determine if feature-based grouping can influence spatial selection biases.

Main Methods:

An odd-man-out visual search task was employed.
Search efficiency was measured with varying target eccentricities and distractor positions.
The experiment compared conditions where target identity was known versus unknown in advance.

Main Results:

Evidence for a central bias in spatial selection was found in conjunction search.
This bias disappeared when the target's identity was known beforehand.
Top-down knowledge of a target feature facilitated detection by enabling feature-based grouping.

Conclusions:

Top-down feature knowledge can drive feature-based grouping.
This grouping mechanism can overcome the central bias in spatial selection.
These effects are independent of bottom-up priming.