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MM-MDS: A Multidimensional Scaling Database with Similarity Ratings for 240 Object Categories from the Massive Memory Picture Database

Cognitive theories in visual attention and perception, categorization, and memory often critically rely on concepts of similarity among objects, and empirically require measures of “sameness” among their stimuli. For instance, a researcher may require similarity estimates among multiple exemplars of...

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Detalles Bibliográficos
Autores principales: Hout, Michael C., Goldinger, Stephen D., Brady, Kyle J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4229237/
https://www.ncbi.nlm.nih.gov/pubmed/25390369
http://dx.doi.org/10.1371/journal.pone.0112644
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author Hout, Michael C.
Goldinger, Stephen D.
Brady, Kyle J.
author_facet Hout, Michael C.
Goldinger, Stephen D.
Brady, Kyle J.
author_sort Hout, Michael C.
collection PubMed
description Cognitive theories in visual attention and perception, categorization, and memory often critically rely on concepts of similarity among objects, and empirically require measures of “sameness” among their stimuli. For instance, a researcher may require similarity estimates among multiple exemplars of a target category in visual search, or targets and lures in recognition memory. Quantifying similarity, however, is challenging when everyday items are the desired stimulus set, particularly when researchers require several different pictures from the same category. In this article, we document a new multidimensional scaling database with similarity ratings for 240 categories, each containing color photographs of 16–17 exemplar objects. We collected similarity ratings using the spatial arrangement method. Reports include: the multidimensional scaling solutions for each category, up to five dimensions, stress and fit measures, coordinate locations for each stimulus, and two new classifications. For each picture, we categorized the item's prototypicality, indexed by its proximity to other items in the space. We also classified pairs of images along a continuum of similarity, by assessing the overall arrangement of each MDS space. These similarity ratings will be useful to any researcher that wishes to control the similarity of experimental stimuli according to an objective quantification of “sameness.”
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spelling pubmed-42292372014-11-18 MM-MDS: A Multidimensional Scaling Database with Similarity Ratings for 240 Object Categories from the Massive Memory Picture Database Hout, Michael C. Goldinger, Stephen D. Brady, Kyle J. PLoS One Research Article Cognitive theories in visual attention and perception, categorization, and memory often critically rely on concepts of similarity among objects, and empirically require measures of “sameness” among their stimuli. For instance, a researcher may require similarity estimates among multiple exemplars of a target category in visual search, or targets and lures in recognition memory. Quantifying similarity, however, is challenging when everyday items are the desired stimulus set, particularly when researchers require several different pictures from the same category. In this article, we document a new multidimensional scaling database with similarity ratings for 240 categories, each containing color photographs of 16–17 exemplar objects. We collected similarity ratings using the spatial arrangement method. Reports include: the multidimensional scaling solutions for each category, up to five dimensions, stress and fit measures, coordinate locations for each stimulus, and two new classifications. For each picture, we categorized the item's prototypicality, indexed by its proximity to other items in the space. We also classified pairs of images along a continuum of similarity, by assessing the overall arrangement of each MDS space. These similarity ratings will be useful to any researcher that wishes to control the similarity of experimental stimuli according to an objective quantification of “sameness.” Public Library of Science 2014-11-12 /pmc/articles/PMC4229237/ /pubmed/25390369 http://dx.doi.org/10.1371/journal.pone.0112644 Text en © 2014 Hout et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Hout, Michael C.
Goldinger, Stephen D.
Brady, Kyle J.
MM-MDS: A Multidimensional Scaling Database with Similarity Ratings for 240 Object Categories from the Massive Memory Picture Database
title MM-MDS: A Multidimensional Scaling Database with Similarity Ratings for 240 Object Categories from the Massive Memory Picture Database
title_full MM-MDS: A Multidimensional Scaling Database with Similarity Ratings for 240 Object Categories from the Massive Memory Picture Database
title_fullStr MM-MDS: A Multidimensional Scaling Database with Similarity Ratings for 240 Object Categories from the Massive Memory Picture Database
title_full_unstemmed MM-MDS: A Multidimensional Scaling Database with Similarity Ratings for 240 Object Categories from the Massive Memory Picture Database
title_short MM-MDS: A Multidimensional Scaling Database with Similarity Ratings for 240 Object Categories from the Massive Memory Picture Database
title_sort mm-mds: a multidimensional scaling database with similarity ratings for 240 object categories from the massive memory picture database
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4229237/
https://www.ncbi.nlm.nih.gov/pubmed/25390369
http://dx.doi.org/10.1371/journal.pone.0112644
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