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Related Experiment Video

Updated: May 22, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

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

Published on: January 23, 2017

Feature-based attention enhances performance by increasing response gain.

Katrin Herrmann1, David J Heeger, Marisa Carrasco

  • 1Department of Psychology, New York University, United States.

Vision Research
|May 15, 2012
PubMed
Summary
This summary is machine-generated.

Feature-based attention enhances visual performance through response gain changes, regardless of attention field size. This finding contrasts with spatial attention and supports the normalization model of attention.

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Artificial Intelligence-Based System for Detecting Attention Levels in Students
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Last Updated: May 22, 2026

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

Published on: January 23, 2017

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Area of Science:

  • Cognitive Neuroscience
  • Visual Perception
  • Computational Neuroscience

Background:

  • Covert spatial attention modulates contrast sensitivity via contrast or response gain changes, influenced by attention and stimulus size.
  • The normalization model of attention predicts feature-based attention solely alters response gain, irrespective of attention field extent.

Purpose of the Study:

  • To investigate the contrast dependence of feature-based attention.
  • To test the normalization model's prediction that feature-based attention exclusively modifies response gain.

Main Methods:

  • Observers performed an orientation-discrimination task on grating patches with randomized spatial locations.
  • Feature-based attention was manipulated using valid/invalid pre-cues, and attention field extent varied with orientation uncertainty.

Main Results:

  • Performance accuracy improved with valid pre-cues compared to invalid ones.
  • This improvement, consistent with response gain changes, occurred across both small and large featural extents of the attention field.

Conclusions:

  • Results for feature-based attention differ from spatial attention findings.
  • Both spatial and feature-based attention results support the normalization model of attention's predictions.