Literature DB >> 16243694

Odour concentration affects odour identity in honeybees.

Geraldine A Wright1, Mitchell G A Thomson, Brian H Smith.   

Abstract

The fact that most types of sensory stimuli occur naturally over a large range of intensities is a challenge to early sensory processing. Sensory mechanisms appear to be optimized to extract perceptually significant stimulus fluctuations that can be analysed in a manner largely independent of the absolute stimulus intensity. This general principle may not, however, extend to olfaction; many studies have suggested that olfactory stimuli are not perceptually invariant with respect to odour intensity. For many animals, absolute odour intensity may be a feature in itself, such that it forms a part of odour identity and thus plays an important role in discrimination alongside other odour properties such as the molecular identity of the odorant. The experiments with honeybees reported here show a departure from odour-concentration invariance and are consistent with a lower-concentration regime in which odour concentration contributes to overall odour identity and a higher-concentration regime in which it may not. We argue that this could be a natural consequence of odour coding and suggest how an 'intensity feature' might be useful to the honeybee in natural odour detection and discrimination.

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Year:  2005        PMID: 16243694      PMCID: PMC1559969          DOI: 10.1098/rspb.2005.3252

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


  42 in total

Review 1.  How the olfactory system makes sense of scents.

Authors:  S Firestein
Journal:  Nature       Date:  2001-09-13       Impact factor: 49.962

2.  Correspondence between odorant-evoked patterns of receptor neuron input and intrinsic optical signals in the mouse olfactory bulb.

Authors:  Matt Wachowiak; Lawrence B Cohen
Journal:  J Neurophysiol       Date:  2002-10-23       Impact factor: 2.714

Review 3.  Olfactory network dynamics and the coding of multidimensional signals.

Authors:  Gilles Laurent
Journal:  Nat Rev Neurosci       Date:  2002-11       Impact factor: 34.870

4.  Relationship between molecular structure, concentration and odor qualities of oxygenated aliphatic molecules.

Authors:  D G Laing; P K Legha; A L Jinks; I Hutchinson
Journal:  Chem Senses       Date:  2003-01       Impact factor: 3.160

5.  Dissociated neural representations of intensity and valence in human olfaction.

Authors:  A K Anderson; K Christoff; I Stappen; D Panitz; D G Ghahremani; G Glover; J D E Gabrieli; N Sobel
Journal:  Nat Neurosci       Date:  2003-02       Impact factor: 24.884

Review 6.  How lobsters, crayfishes, and crabs locate sources of odor: current perspectives and future directions.

Authors:  Frank W Grasso; Jennifer A Basil
Journal:  Curr Opin Neurobiol       Date:  2002-12       Impact factor: 6.627

7.  Why are olfactory systems of different animals so similar?

Authors:  Heather L Eisthen
Journal:  Brain Behav Evol       Date:  2002       Impact factor: 1.808

8.  Analysis of interaction in binary odorant mixtures.

Authors:  B H Smith
Journal:  Physiol Behav       Date:  1998-12-01

9.  How synchronization properties among second-order sensory neurons can mediate stimulus salience.

Authors:  Thomas A Cleland; Christiane Linster
Journal:  Behav Neurosci       Date:  2002-04       Impact factor: 1.912

10.  Effects of odor flux and pulse rate on chemosensory tracking in turbulent odor plumes by the blue crab, Callinectes sapidus.

Authors:  Troy A Keller; Marc J Weissburg
Journal:  Biol Bull       Date:  2004-08       Impact factor: 1.818

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  21 in total

1.  Mimicking biological design and computing principles in artificial olfaction.

Authors:  Baranidharan Raman; Mark Stopfer; Steve Semancik
Journal:  ACS Chem Neurosci       Date:  2011-05-27       Impact factor: 4.418

2.  A honeybee's ability to learn, recognize, and discriminate odors depends upon odor sampling time and concentration.

Authors:  Geraldine A Wright; Michelle Carlton; Brian H Smith
Journal:  Behav Neurosci       Date:  2009-02       Impact factor: 1.912

3.  Herbivore-specific, density-dependent induction of plant volatiles: honest or "cry wolf" signals?

Authors:  Kaori Shiojiri; Rika Ozawa; Soichi Kugimiya; Masayoshi Uefune; Michiel van Wijk; Maurice W Sabelis; Junji Takabayashi
Journal:  PLoS One       Date:  2010-08-17       Impact factor: 3.240

4.  Reward quality influences the development of learned olfactory biases in honeybees.

Authors:  Geraldine A Wright; Amir F Choudhary; Michael A Bentley
Journal:  Proc Biol Sci       Date:  2009-04-15       Impact factor: 5.349

5.  Odour intensity learning in fruit flies.

Authors:  Ayse Yarali; Sabrina Ehser; Fatma Zehra Hapil; Ju Huang; Bertram Gerber
Journal:  Proc Biol Sci       Date:  2009-07-08       Impact factor: 5.349

6.  Neuronal processing of complex mixtures establishes a unique odor representation in the moth antennal lobe.

Authors:  Linda S Kuebler; Shannon B Olsson; Richard Weniger; Bill S Hansson
Journal:  Front Neural Circuits       Date:  2011-05-11       Impact factor: 3.492

7.  Agitated honeybees exhibit pessimistic cognitive biases.

Authors:  Melissa Bateson; Suzanne Desire; Sarah E Gartside; Geraldine A Wright
Journal:  Curr Biol       Date:  2011-06-21       Impact factor: 10.834

8.  Sequence-Based Prediction of Olfactory Receptor Responses.

Authors:  Shashank Chepurwar; Abhishek Gupta; Rafi Haddad; Nitin Gupta
Journal:  Chem Senses       Date:  2019-10-26       Impact factor: 3.160

9.  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

10.  Keeping their distance? Odor response patterns along the concentration range.

Authors:  Martin Strauch; Mathias Ditzen; C Giovanni Galizia
Journal:  Front Syst Neurosci       Date:  2012-10-18
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