Literature DB >> 9855481

The influence of odor type on the discrimination and identification of odorants in multicomponent odor mixtures.

A Livermore1, D G Laing.   

Abstract

Using a limited set of odorants, previous studies have indicated that the ability of humans to discriminate and identify the components of olfactory mixtures is limited to approximately four. However, the ability to generalize these results may have been limited by specific neural or cognitive interactions among the particular odorants used. In the present experiment, 41 subjects examined the influence of odor type (different individual odorants), from two very different odor sets, on the perception of the components of complex mixtures. One set contained odors that were selected by an expert panel to blend well in mixtures (good blenders), whereas the other contained odors that blended poorly in mixtures (poor blenders). The stimuli were common, dissimilar odorants of equivalent, moderate intensity, each of which was a single chemical. A computer-controlled air dilution olfactometer delivered a single odorant or a mixture containing up to eight odorants. Although the poor blenders were more easily discriminated, this superiority was displayed within a narrow range, and the ability of subjects to identify mixture components with either odor set was limited to approximately four. The results indicate that, whereas odor type can alter which odorants will be perceived in a mixture, the limited capacity to discriminate mixture components is independent of the type of odorants. These findings are discussed in terms of their implications for olfactory coding.

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Year:  1998        PMID: 9855481     DOI: 10.1016/s0031-9384(98)00168-1

Source DB:  PubMed          Journal:  Physiol Behav        ISSN: 0031-9384


  16 in total

1.  Time and intensity factors in identification of components of odor mixtures.

Authors:  Marion E Frank; Holly F Goyert; Thomas P Hettinger
Journal:  Chem Senses       Date:  2010-08-18       Impact factor: 3.160

2.  Symmetry, stereotypy, and topography of odorant representations in mouse olfactory bulbs.

Authors:  L Belluscio; L C Katz
Journal:  J Neurosci       Date:  2001-03-15       Impact factor: 6.167

3.  Perceptual convergence of multi-component mixtures in olfaction implies an olfactory white.

Authors:  Tali Weiss; Kobi Snitz; Adi Yablonka; Rehan M Khan; Danyel Gafsou; Elad Schneidman; Noam Sobel
Journal:  Proc Natl Acad Sci U S A       Date:  2012-11-19       Impact factor: 11.205

4.  Songbird chemical signals reflect uropygial gland androgen sensitivity and predict aggression: implications for the role of the periphery in chemosignaling.

Authors:  Danielle J Whittaker; Kimberly A Rosvall; Samuel P Slowinski; Helena A Soini; Milos V Novotny; Ellen D Ketterson
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2017-10-23       Impact factor: 1.836

5.  Characteristic component odors emerge from mixtures after selective adaptation.

Authors:  Holly F Goyert; Marion E Frank; Janneane F Gent; Thomas P Hettinger
Journal:  Brain Res Bull       Date:  2007-01-16       Impact factor: 4.077

6.  Songbird preen oil odour reflects haemosporidian parasite load.

Authors:  K M Talbott; D J Becker; H A Soini; B J Higgins; M V Novotny; E D Ketterson
Journal:  Anim Behav       Date:  2022-05-11       Impact factor: 3.039

7.  Effects of visual priming on taste-odor interaction.

Authors:  Marije van Beilen; Harold Bult; Remco Renken; Markus Stieger; Stefan Thumfart; Frans Cornelissen; Valesca Kooijman
Journal:  PLoS One       Date:  2011-09-28       Impact factor: 3.240

8.  Rabbit neonates and human adults perceive a blending 6-component odor mixture in a comparable manner.

Authors:  Charlotte Sinding; Thierry Thomas-Danguin; Adeline Chambault; Noelle Béno; Thibaut Dosne; Claire Chabanet; Benoist Schaal; Gérard Coureaud
Journal:  PLoS One       Date:  2013-01-16       Impact factor: 3.240

9.  Rapid odor processing in the honeybee antennal lobe network.

Authors:  Sabine Krofczik; Randolf Menzel; Martin P Nawrot
Journal:  Front Comput Neurosci       Date:  2009-01-15       Impact factor: 2.380

10.  Predicting odor perceptual similarity from odor structure.

Authors:  Kobi Snitz; Adi Yablonka; Tali Weiss; Idan Frumin; Rehan M Khan; Noam Sobel
Journal:  PLoS Comput Biol       Date:  2013-09-12       Impact factor: 4.475

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