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Duration discrimination: A diffusion decision modeling approach

The human ability to discriminate the duration of two subsequently presented stimuli is often studied with tasks that involve a comparison between a standard stimulus (with fixed duration) and comparison stimuli (with varying durations). The performance in such tasks is influenced by the presentatio...

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Autores principales: Schumacher, Lukas, Voss, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9935725/
https://www.ncbi.nlm.nih.gov/pubmed/36690915
http://dx.doi.org/10.3758/s13414-022-02604-1
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author Schumacher, Lukas
Voss, Andreas
author_facet Schumacher, Lukas
Voss, Andreas
author_sort Schumacher, Lukas
collection PubMed
description The human ability to discriminate the duration of two subsequently presented stimuli is often studied with tasks that involve a comparison between a standard stimulus (with fixed duration) and comparison stimuli (with varying durations). The performance in such tasks is influenced by the presentation order of these successively presented stimuli. The so-called Type A effect refers to the impact of presentation order on the point of subjective equality. The Type B effect describes effects of presentation order on the just-noticeable-difference. Cognitive models that account for these context effects assume that participants’ duration estimation is influenced by the history of previously encountered stimuli. For example, the internal reference model assumes that the magnitude of a “typical” stimulus is represented by an internal reference. This internal reference evolves throughout an experiment and is updated on every trial. Different recent models have in common that they describe how the internal reference is computed but are agnostic to the decision process itself. In this study, we develop a new model that incorporates the mechanisms of perceptual discrimination models into a diffusion model. The diffusion model focuses on the dynamics of the decision process itself and accounts for choice and response times based on a set of latent cognitive variables. We show that our model accurately predicts the accuracy and response time distribution in a classical duration discrimination task. Further, model parameters were sensitive to the Type A and B effect. The proposed model opens up new opportunities for studying human discrimination performance (e.g., individual differences).
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spelling pubmed-99357252023-02-18 Duration discrimination: A diffusion decision modeling approach Schumacher, Lukas Voss, Andreas Atten Percept Psychophys Article The human ability to discriminate the duration of two subsequently presented stimuli is often studied with tasks that involve a comparison between a standard stimulus (with fixed duration) and comparison stimuli (with varying durations). The performance in such tasks is influenced by the presentation order of these successively presented stimuli. The so-called Type A effect refers to the impact of presentation order on the point of subjective equality. The Type B effect describes effects of presentation order on the just-noticeable-difference. Cognitive models that account for these context effects assume that participants’ duration estimation is influenced by the history of previously encountered stimuli. For example, the internal reference model assumes that the magnitude of a “typical” stimulus is represented by an internal reference. This internal reference evolves throughout an experiment and is updated on every trial. Different recent models have in common that they describe how the internal reference is computed but are agnostic to the decision process itself. In this study, we develop a new model that incorporates the mechanisms of perceptual discrimination models into a diffusion model. The diffusion model focuses on the dynamics of the decision process itself and accounts for choice and response times based on a set of latent cognitive variables. We show that our model accurately predicts the accuracy and response time distribution in a classical duration discrimination task. Further, model parameters were sensitive to the Type A and B effect. The proposed model opens up new opportunities for studying human discrimination performance (e.g., individual differences). Springer US 2023-01-23 2023 /pmc/articles/PMC9935725/ /pubmed/36690915 http://dx.doi.org/10.3758/s13414-022-02604-1 Text en © The Author(s) 2023 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
Schumacher, Lukas
Voss, Andreas
Duration discrimination: A diffusion decision modeling approach
title Duration discrimination: A diffusion decision modeling approach
title_full Duration discrimination: A diffusion decision modeling approach
title_fullStr Duration discrimination: A diffusion decision modeling approach
title_full_unstemmed Duration discrimination: A diffusion decision modeling approach
title_short Duration discrimination: A diffusion decision modeling approach
title_sort duration discrimination: a diffusion decision modeling approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9935725/
https://www.ncbi.nlm.nih.gov/pubmed/36690915
http://dx.doi.org/10.3758/s13414-022-02604-1
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