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Related Experiment Video

Updated: May 11, 2026

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

Published on: April 11, 2025

Visual search and location probability learning from variable perspectives.

Yuhong V Jiang¹, Khena M Swallow, Christian G Capistrano

¹Department of Psychology & Center for Cognitive Sciences, University of Minnesota, Minneapolis, MN, USA. jiang166@umn.edu

Journal of Vision

|May 30, 2013

Summary

This summary is machine-generated.

Moving observers use viewer-centered spatial biases for incidental learning, but goal-driven attention prioritizes environmental regions. Perspective shifts prevent incidental learning of target locations.

Keywords:

attention incidental learning spatial reference frame visual search

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Area of Science:

Cognitive psychology
Neuroscience
Visual perception

Background:

Understanding how observers represent spatial information during movement is crucial for cognitive science.
Previous research suggests spatial coding can be viewer-centered or world-centered.

Purpose of the Study:

To investigate whether moving observers code attended locations relative to themselves or the external environment.
To determine the mechanisms underlying spatial biases in visual search during locomotion.

Main Methods:

Participants performed visual search tasks on a tabletop with varying target probabilities.
Observer's perspective changed across trials due to locomotion around the table.
Experiments manipulated awareness of high-probability locations and tested incidental learning.

Main Results:

Probability cuing enhanced search speed when participants were aware of high-probability locations.
Incidental learning of spatial biases was impaired by changing perspectives during locomotion.
Locomotion itself did not hinder incidental learning, but lack of consistent viewpoint did.

Conclusions:

Spatial biases are governed by both incidental learning (viewer-centered, static) and goal-driven attention (environment-centered, dynamic).
Incidental learning of spatial regularities is viewer-centered and not updated with movement.
Goal-driven attention allows for flexible prioritization of environment-based regions.