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Prediction Models for the Pleasantness of Binary Mixtures in Olfaction

Whereas the rules underlying the perceived intensity of binary mixtures have been investigated, minimal efforts have been directed at elucidating the rules underlying the perceived pleasantness of such mixtures. To address this, 84 subjects ranked the pleasantness and intensity of 5 distinct binary...

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Detalles Bibliográficos
Autores principales: Lapid, Hadas, Harel, David, Sobel, Noam
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2533422/
https://www.ncbi.nlm.nih.gov/pubmed/18534998
http://dx.doi.org/10.1093/chemse/bjn026
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author Lapid, Hadas
Harel, David
Sobel, Noam
author_facet Lapid, Hadas
Harel, David
Sobel, Noam
author_sort Lapid, Hadas
collection PubMed
description Whereas the rules underlying the perceived intensity of binary mixtures have been investigated, minimal efforts have been directed at elucidating the rules underlying the perceived pleasantness of such mixtures. To address this, 84 subjects ranked the pleasantness and intensity of 5 distinct binary mixtures (15 pairs, inter-stimulus interval = 4 s, inter-trial interval = 30 s, flow = 6 l/min, pulse = 2 s) constructed from different ratios (0:100%, 25:75%, 50:50%, 75:25%, and 100:0%, olfactometer-generated vapor phase). We found that in the majority of cases, the pleasantness of the mixture fell between the pleasantness values of its separated constituents and that it was strongly influenced by the relative intensities of the constituents. Based on these results, we proposed a prediction paradigm for the pleasantness of binary mixtures from the pleasantness of their separated constituents weighted by their respective perceived intensities. The uniqueness of the proposed paradigm is that it neither requires presetting an interaction constant between the mixture components nor require any factorization of the pleasantness weights. It does, nonetheless, require solid psychophysical data on the separated components at their different concentrations, and currently it can only explain the behavior of intermediate pleasantness of mixtures.
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spelling pubmed-25334222009-02-25 Prediction Models for the Pleasantness of Binary Mixtures in Olfaction Lapid, Hadas Harel, David Sobel, Noam Chem Senses Articles Whereas the rules underlying the perceived intensity of binary mixtures have been investigated, minimal efforts have been directed at elucidating the rules underlying the perceived pleasantness of such mixtures. To address this, 84 subjects ranked the pleasantness and intensity of 5 distinct binary mixtures (15 pairs, inter-stimulus interval = 4 s, inter-trial interval = 30 s, flow = 6 l/min, pulse = 2 s) constructed from different ratios (0:100%, 25:75%, 50:50%, 75:25%, and 100:0%, olfactometer-generated vapor phase). We found that in the majority of cases, the pleasantness of the mixture fell between the pleasantness values of its separated constituents and that it was strongly influenced by the relative intensities of the constituents. Based on these results, we proposed a prediction paradigm for the pleasantness of binary mixtures from the pleasantness of their separated constituents weighted by their respective perceived intensities. The uniqueness of the proposed paradigm is that it neither requires presetting an interaction constant between the mixture components nor require any factorization of the pleasantness weights. It does, nonetheless, require solid psychophysical data on the separated components at their different concentrations, and currently it can only explain the behavior of intermediate pleasantness of mixtures. Oxford University Press 2008-09 2008-06-04 /pmc/articles/PMC2533422/ /pubmed/18534998 http://dx.doi.org/10.1093/chemse/bjn026 Text en © 2008 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Lapid, Hadas
Harel, David
Sobel, Noam
Prediction Models for the Pleasantness of Binary Mixtures in Olfaction
title Prediction Models for the Pleasantness of Binary Mixtures in Olfaction
title_full Prediction Models for the Pleasantness of Binary Mixtures in Olfaction
title_fullStr Prediction Models for the Pleasantness of Binary Mixtures in Olfaction
title_full_unstemmed Prediction Models for the Pleasantness of Binary Mixtures in Olfaction
title_short Prediction Models for the Pleasantness of Binary Mixtures in Olfaction
title_sort prediction models for the pleasantness of binary mixtures in olfaction
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2533422/
https://www.ncbi.nlm.nih.gov/pubmed/18534998
http://dx.doi.org/10.1093/chemse/bjn026
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