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Location probability learning in 3-dimensional virtual search environments
When a visual search target frequently appears in one target-rich region of space, participants learn to search there first, resulting in faster reaction time when the target appears there than when it appears elsewhere. Most research on this location probability learning (LPL) effect uses 2-dimensi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7988261/ https://www.ncbi.nlm.nih.gov/pubmed/33761042 http://dx.doi.org/10.1186/s41235-021-00284-3 |
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author | Sisk, Caitlin A. Interrante, Victoria Jiang, Yuhong V. |
author_facet | Sisk, Caitlin A. Interrante, Victoria Jiang, Yuhong V. |
author_sort | Sisk, Caitlin A. |
collection | PubMed |
description | When a visual search target frequently appears in one target-rich region of space, participants learn to search there first, resulting in faster reaction time when the target appears there than when it appears elsewhere. Most research on this location probability learning (LPL) effect uses 2-dimensional (2D) search environments that are distinct from real-world search contexts, and the few studies on LPL in 3-dimensional (3D) contexts include complex visual cues or foraging tasks and therefore may not tap into the same habit-like learning mechanism as 2D LPL. The present study aimed to establish a baseline evaluation of LPL in controlled 3D search environments using virtual reality. The use of a virtual 3D search environment allowed us to compare LPL for information within a participant’s initial field of view to LPL for information behind participants, outside of the initial field of view. Participants searched for a letter T on the ground among letter Ls in a large virtual space that was devoid of complex visual cues or landmarks. The T appeared in one target-rich quadrant of the floor space on half of the trials during the training phase. The target-rich quadrant appeared in front of half of the participants and behind the other half. LPL was considerably greater in the former condition than in the latter. This reveals an important constraint on LPL in real-world environments and indicates that consistent search patterns and consistent egocentric spatial coding are essential for this form of visual statistical learning in 3D environments. |
format | Online Article Text |
id | pubmed-7988261 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-79882612021-03-24 Location probability learning in 3-dimensional virtual search environments Sisk, Caitlin A. Interrante, Victoria Jiang, Yuhong V. Cogn Res Princ Implic Original Article When a visual search target frequently appears in one target-rich region of space, participants learn to search there first, resulting in faster reaction time when the target appears there than when it appears elsewhere. Most research on this location probability learning (LPL) effect uses 2-dimensional (2D) search environments that are distinct from real-world search contexts, and the few studies on LPL in 3-dimensional (3D) contexts include complex visual cues or foraging tasks and therefore may not tap into the same habit-like learning mechanism as 2D LPL. The present study aimed to establish a baseline evaluation of LPL in controlled 3D search environments using virtual reality. The use of a virtual 3D search environment allowed us to compare LPL for information within a participant’s initial field of view to LPL for information behind participants, outside of the initial field of view. Participants searched for a letter T on the ground among letter Ls in a large virtual space that was devoid of complex visual cues or landmarks. The T appeared in one target-rich quadrant of the floor space on half of the trials during the training phase. The target-rich quadrant appeared in front of half of the participants and behind the other half. LPL was considerably greater in the former condition than in the latter. This reveals an important constraint on LPL in real-world environments and indicates that consistent search patterns and consistent egocentric spatial coding are essential for this form of visual statistical learning in 3D environments. Springer International Publishing 2021-03-24 /pmc/articles/PMC7988261/ /pubmed/33761042 http://dx.doi.org/10.1186/s41235-021-00284-3 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Article Sisk, Caitlin A. Interrante, Victoria Jiang, Yuhong V. Location probability learning in 3-dimensional virtual search environments |
title | Location probability learning in 3-dimensional virtual search environments |
title_full | Location probability learning in 3-dimensional virtual search environments |
title_fullStr | Location probability learning in 3-dimensional virtual search environments |
title_full_unstemmed | Location probability learning in 3-dimensional virtual search environments |
title_short | Location probability learning in 3-dimensional virtual search environments |
title_sort | location probability learning in 3-dimensional virtual search environments |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7988261/ https://www.ncbi.nlm.nih.gov/pubmed/33761042 http://dx.doi.org/10.1186/s41235-021-00284-3 |
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