Cargando…
Information-optimal local features automatically attract covert and overt attention
In fast vision, local spatial properties of the visual scene can automatically capture the observer’s attention. We used specific local features, predicted by a constrained maximum-entropy model to be optimal information-carriers, as candidate “salient features''. Previous studies showed t...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9200825/ https://www.ncbi.nlm.nih.gov/pubmed/35705616 http://dx.doi.org/10.1038/s41598-022-14262-2 |
_version_ | 1784728151219240960 |
---|---|
author | Castellotti, Serena Montagnini, Anna Del Viva, Maria Michela |
author_facet | Castellotti, Serena Montagnini, Anna Del Viva, Maria Michela |
author_sort | Castellotti, Serena |
collection | PubMed |
description | In fast vision, local spatial properties of the visual scene can automatically capture the observer’s attention. We used specific local features, predicted by a constrained maximum-entropy model to be optimal information-carriers, as candidate “salient features''. Previous studies showed that participants choose these optimal features as “more salient” if explicitly asked. Here, we investigated the implicit saliency of these optimal features in two attentional tasks. In a covert-attention experiment, we measured the luminance-contrast threshold for discriminating the orientation of a peripheral gabor. In a gaze-orienting experiment, we analyzed latency and direction of saccades towards a peripheral target. In both tasks, two brief peripheral cues, differing in saliency according to the model, preceded the target, presented on the same (valid trials) or the opposite side (invalid trials) of the optimal cue. Results showed reduced contrast thresholds, saccadic latencies, and direction errors in valid trials, and the opposite in invalid trials, compared to baseline values obtained with equally salient cues. Also, optimal features triggered more anticipatory saccades. Similar effects emerged in a luminance-control condition. Overall, in fast vision, optimal features automatically attract covert and overt attention, suggesting that saliency is determined by information maximization criteria coupled with computational limitations. |
format | Online Article Text |
id | pubmed-9200825 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92008252022-06-17 Information-optimal local features automatically attract covert and overt attention Castellotti, Serena Montagnini, Anna Del Viva, Maria Michela Sci Rep Article In fast vision, local spatial properties of the visual scene can automatically capture the observer’s attention. We used specific local features, predicted by a constrained maximum-entropy model to be optimal information-carriers, as candidate “salient features''. Previous studies showed that participants choose these optimal features as “more salient” if explicitly asked. Here, we investigated the implicit saliency of these optimal features in two attentional tasks. In a covert-attention experiment, we measured the luminance-contrast threshold for discriminating the orientation of a peripheral gabor. In a gaze-orienting experiment, we analyzed latency and direction of saccades towards a peripheral target. In both tasks, two brief peripheral cues, differing in saliency according to the model, preceded the target, presented on the same (valid trials) or the opposite side (invalid trials) of the optimal cue. Results showed reduced contrast thresholds, saccadic latencies, and direction errors in valid trials, and the opposite in invalid trials, compared to baseline values obtained with equally salient cues. Also, optimal features triggered more anticipatory saccades. Similar effects emerged in a luminance-control condition. Overall, in fast vision, optimal features automatically attract covert and overt attention, suggesting that saliency is determined by information maximization criteria coupled with computational limitations. Nature Publishing Group UK 2022-06-15 /pmc/articles/PMC9200825/ /pubmed/35705616 http://dx.doi.org/10.1038/s41598-022-14262-2 Text en © The Author(s) 2022 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 Castellotti, Serena Montagnini, Anna Del Viva, Maria Michela Information-optimal local features automatically attract covert and overt attention |
title | Information-optimal local features automatically attract covert and overt attention |
title_full | Information-optimal local features automatically attract covert and overt attention |
title_fullStr | Information-optimal local features automatically attract covert and overt attention |
title_full_unstemmed | Information-optimal local features automatically attract covert and overt attention |
title_short | Information-optimal local features automatically attract covert and overt attention |
title_sort | information-optimal local features automatically attract covert and overt attention |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9200825/ https://www.ncbi.nlm.nih.gov/pubmed/35705616 http://dx.doi.org/10.1038/s41598-022-14262-2 |
work_keys_str_mv | AT castellottiserena informationoptimallocalfeaturesautomaticallyattractcovertandovertattention AT montagninianna informationoptimallocalfeaturesautomaticallyattractcovertandovertattention AT delvivamariamichela informationoptimallocalfeaturesautomaticallyattractcovertandovertattention |