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Contour features predict valence and threat judgements in scenes
Quickly scanning an environment to determine relative threat is an essential part of survival. Scene gist extracted rapidly from the environment may help people detect threats. Here, we probed this link between emotional judgements and features of visual scenes. We first extracted curvature, length,...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484627/ https://www.ncbi.nlm.nih.gov/pubmed/34593933 http://dx.doi.org/10.1038/s41598-021-99044-y |
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author | Damiano, Claudia Walther, Dirk B. Cunningham, William A. |
author_facet | Damiano, Claudia Walther, Dirk B. Cunningham, William A. |
author_sort | Damiano, Claudia |
collection | PubMed |
description | Quickly scanning an environment to determine relative threat is an essential part of survival. Scene gist extracted rapidly from the environment may help people detect threats. Here, we probed this link between emotional judgements and features of visual scenes. We first extracted curvature, length, and orientation statistics of all images in the International Affective Picture System image set and related them to emotional valence scores. Images containing angular contours were rated as negative, and images containing long contours as positive. We then composed new abstract line drawings with specific combinations of length, angularity, and orientation values and asked participants to rate them as positive or negative, and as safe or threatening. Smooth, long, horizontal contour scenes were rated as positive/safe, while short angular contour scenes were rated as negative/threatening. Our work shows that particular combinations of image features help people make judgements about potential threat in the environment. |
format | Online Article Text |
id | pubmed-8484627 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-84846272021-10-04 Contour features predict valence and threat judgements in scenes Damiano, Claudia Walther, Dirk B. Cunningham, William A. Sci Rep Article Quickly scanning an environment to determine relative threat is an essential part of survival. Scene gist extracted rapidly from the environment may help people detect threats. Here, we probed this link between emotional judgements and features of visual scenes. We first extracted curvature, length, and orientation statistics of all images in the International Affective Picture System image set and related them to emotional valence scores. Images containing angular contours were rated as negative, and images containing long contours as positive. We then composed new abstract line drawings with specific combinations of length, angularity, and orientation values and asked participants to rate them as positive or negative, and as safe or threatening. Smooth, long, horizontal contour scenes were rated as positive/safe, while short angular contour scenes were rated as negative/threatening. Our work shows that particular combinations of image features help people make judgements about potential threat in the environment. Nature Publishing Group UK 2021-09-30 /pmc/articles/PMC8484627/ /pubmed/34593933 http://dx.doi.org/10.1038/s41598-021-99044-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Damiano, Claudia Walther, Dirk B. Cunningham, William A. Contour features predict valence and threat judgements in scenes |
title | Contour features predict valence and threat judgements in scenes |
title_full | Contour features predict valence and threat judgements in scenes |
title_fullStr | Contour features predict valence and threat judgements in scenes |
title_full_unstemmed | Contour features predict valence and threat judgements in scenes |
title_short | Contour features predict valence and threat judgements in scenes |
title_sort | contour features predict valence and threat judgements in scenes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484627/ https://www.ncbi.nlm.nih.gov/pubmed/34593933 http://dx.doi.org/10.1038/s41598-021-99044-y |
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