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Deciphering human decision rules in motion discrimination
We investigated the eight decision rules for a same-different task, as summarized in Petrov (Psychonomic Bulletin & Review, 16(6), 1011–1025, 2009). These rules, including the differencing (DF) rule and the optimal independence rule, are all based on the standard model in signal detection theory...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8550297/ https://www.ncbi.nlm.nih.gov/pubmed/34240340 http://dx.doi.org/10.3758/s13414-021-02327-9 |
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author | Huang, Jinfeng Yu, Alexander Zhou, Yifeng Liu, Zili |
author_facet | Huang, Jinfeng Yu, Alexander Zhou, Yifeng Liu, Zili |
author_sort | Huang, Jinfeng |
collection | PubMed |
description | We investigated the eight decision rules for a same-different task, as summarized in Petrov (Psychonomic Bulletin & Review, 16(6), 1011–1025, 2009). These rules, including the differencing (DF) rule and the optimal independence rule, are all based on the standard model in signal detection theory. Each rule receives two stimulus values as inputs and uses one or two decision criteria. We proved that the false alarm rate p(F) ≤ 1/2 for four of the rules. We also conducted a same-different rating experiment on motion discrimination (n = 54), with 4(∘) or 8(∘) directional difference. We found that the human receiver operating characteristic (ROC) spanned its full range [0,1] in p(F), thus rejecting these four rules. The slope of the human Z-ROC was also < 1, further confirming that the independence rule was not used. We subsequently fitted in the four-dimensional (p(AA), p(AB), p(BA), p(BB)) space the human data to the remaining four rules—DF and likelihood ratio rules, each with one or two criteria, where p(XY) = p(responding “different” given stimulus sequence XY). We found that, using residual distribution analysis, only the two criteria DF rule (DF2) could account for the human data. |
format | Online Article Text |
id | pubmed-8550297 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-85502972021-10-29 Deciphering human decision rules in motion discrimination Huang, Jinfeng Yu, Alexander Zhou, Yifeng Liu, Zili Atten Percept Psychophys Article We investigated the eight decision rules for a same-different task, as summarized in Petrov (Psychonomic Bulletin & Review, 16(6), 1011–1025, 2009). These rules, including the differencing (DF) rule and the optimal independence rule, are all based on the standard model in signal detection theory. Each rule receives two stimulus values as inputs and uses one or two decision criteria. We proved that the false alarm rate p(F) ≤ 1/2 for four of the rules. We also conducted a same-different rating experiment on motion discrimination (n = 54), with 4(∘) or 8(∘) directional difference. We found that the human receiver operating characteristic (ROC) spanned its full range [0,1] in p(F), thus rejecting these four rules. The slope of the human Z-ROC was also < 1, further confirming that the independence rule was not used. We subsequently fitted in the four-dimensional (p(AA), p(AB), p(BA), p(BB)) space the human data to the remaining four rules—DF and likelihood ratio rules, each with one or two criteria, where p(XY) = p(responding “different” given stimulus sequence XY). We found that, using residual distribution analysis, only the two criteria DF rule (DF2) could account for the human data. Springer US 2021-07-08 2021 /pmc/articles/PMC8550297/ /pubmed/34240340 http://dx.doi.org/10.3758/s13414-021-02327-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Huang, Jinfeng Yu, Alexander Zhou, Yifeng Liu, Zili Deciphering human decision rules in motion discrimination |
title | Deciphering human decision rules in motion discrimination |
title_full | Deciphering human decision rules in motion discrimination |
title_fullStr | Deciphering human decision rules in motion discrimination |
title_full_unstemmed | Deciphering human decision rules in motion discrimination |
title_short | Deciphering human decision rules in motion discrimination |
title_sort | deciphering human decision rules in motion discrimination |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8550297/ https://www.ncbi.nlm.nih.gov/pubmed/34240340 http://dx.doi.org/10.3758/s13414-021-02327-9 |
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