A Comparative Study on Line Bisection and Landmark Task Performance Using a Hybrid Online Setting

Bisection tasks are commonly used to assess biases and asymmetries in visuospatial attention in both patients and neurologically intact individuals. In these tasks, participants are usually asked to identify the midpoint and manually bisect a horizontal line. Typically, healthy individuals tend to s...

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Published in:Symmetry (Basel) 2023-03, Vol.15 (3), p.729
Main Authors: Strappini, Francesca, Ben-Nun, Amihai, Pecchinenda, Anna
Format: Article
Language:English
Subjects:
attention bias
Attentional bias
Bias
Comparative analysis
Comparative studies
Experiments
lateralization
online testing
perceptual asymmetries
pseudoneglect
Technology application
Visual fields
visual neglect
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description Bisection tasks are commonly used to assess biases and asymmetries in visuospatial attention in both patients and neurologically intact individuals. In these tasks, participants are usually asked to identify the midpoint and manually bisect a horizontal line. Typically, healthy individuals tend to show an attention processing advantage for the left visual field, known as “pseudoneglect.” Here, performance at two computerized versions of the task was compared to assess pseudoneglect in neurologically intact individuals. Specifically, we used a hybrid online setting in which subjects (n = 35) performed the online tasks under the video guidance of the experimenter. We measured attentional biases in the line bisection and landmark tasks. We found pseudoneglect in both tasks, although the bias was larger in the line bisection task. Overall, these findings show that hybrid online tasks may provide a valid setting to assess attentional biases and suggest their feasibility in the clinical setting.
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subjects attention bias
Attentional bias
Bias
Comparative analysis
Comparative studies
Experiments
lateralization
online testing
perceptual asymmetries
pseudoneglect
Technology application
Visual fields
visual neglect
title A Comparative Study on Line Bisection and Landmark Task Performance Using a Hybrid Online Setting
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