Odorant mixtures elicit less variable and faster responses than pure odorants
In natural environments, odors are typically mixtures of several different chemical compounds. However, the implications of mixtures for odor processing have not been fully investigated. We have extended a standard olfactory receptor model to mixtures and found through its mathematical analysis that...
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todo:paper_1553734X_v14_n12_p_Chan2023-10-03T16:25:28Z Odorant mixtures elicit less variable and faster responses than pure odorants Chan, H.K. Hersperger, F. Marachlian, E. Smith, B.H. Locatelli, F. Szyszka, P. Nowotny, T. 2 butanone 2 hexenyl acetic acid acetic acid ethyl ester chemical compound ethyl 2 methylbutanoic acid methylbutyric acid unclassified drug fragrance Apis mellifera Article concentration (parameter) controlled study Drosophila melanogaster honeybee mathematical analysis mathematical model nonhuman odor olfactory receptor olfactory system signal transduction analysis animal bee chemistry drug mixture insect odor olfactory bulb olfactory receptor neuron physiology theoretical model Animals Bees Complex Mixtures Insecta Models, Theoretical Odorants Olfactory Bulb Olfactory Receptor Neurons Receptors, Odorant Smell In natural environments, odors are typically mixtures of several different chemical compounds. However, the implications of mixtures for odor processing have not been fully investigated. We have extended a standard olfactory receptor model to mixtures and found through its mathematical analysis that odorant-evoked activity patterns are more stable across concentrations and first-spike latencies of receptor neurons are shorter for mixtures than for pure odorants. Shorter first-spike latencies arise from the nonlinear dependence of binding rate on odorant concentration, commonly described by the Hill coefficient, while the more stable activity patterns result from the competition between different ligands for receptor sites. These results are consistent with observations from numerical simulations and physiological recordings in the olfactory system of insects. Our results suggest that mixtures allow faster and more reliable olfactory coding, which could be one of the reasons why animals often use mixtures in chemical signaling. © 2018 Chan et al. http://creativecommons.org/licenses/by/4.0/. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_1553734X_v14_n12_p_Chan |
institution |
Universidad de Buenos Aires |
institution_str |
I-28 |
repository_str |
R-134 |
collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
topic |
2 butanone 2 hexenyl acetic acid acetic acid ethyl ester chemical compound ethyl 2 methylbutanoic acid methylbutyric acid unclassified drug fragrance Apis mellifera Article concentration (parameter) controlled study Drosophila melanogaster honeybee mathematical analysis mathematical model nonhuman odor olfactory receptor olfactory system signal transduction analysis animal bee chemistry drug mixture insect odor olfactory bulb olfactory receptor neuron physiology theoretical model Animals Bees Complex Mixtures Insecta Models, Theoretical Odorants Olfactory Bulb Olfactory Receptor Neurons Receptors, Odorant Smell |
spellingShingle |
2 butanone 2 hexenyl acetic acid acetic acid ethyl ester chemical compound ethyl 2 methylbutanoic acid methylbutyric acid unclassified drug fragrance Apis mellifera Article concentration (parameter) controlled study Drosophila melanogaster honeybee mathematical analysis mathematical model nonhuman odor olfactory receptor olfactory system signal transduction analysis animal bee chemistry drug mixture insect odor olfactory bulb olfactory receptor neuron physiology theoretical model Animals Bees Complex Mixtures Insecta Models, Theoretical Odorants Olfactory Bulb Olfactory Receptor Neurons Receptors, Odorant Smell Chan, H.K. Hersperger, F. Marachlian, E. Smith, B.H. Locatelli, F. Szyszka, P. Nowotny, T. Odorant mixtures elicit less variable and faster responses than pure odorants |
topic_facet |
2 butanone 2 hexenyl acetic acid acetic acid ethyl ester chemical compound ethyl 2 methylbutanoic acid methylbutyric acid unclassified drug fragrance Apis mellifera Article concentration (parameter) controlled study Drosophila melanogaster honeybee mathematical analysis mathematical model nonhuman odor olfactory receptor olfactory system signal transduction analysis animal bee chemistry drug mixture insect odor olfactory bulb olfactory receptor neuron physiology theoretical model Animals Bees Complex Mixtures Insecta Models, Theoretical Odorants Olfactory Bulb Olfactory Receptor Neurons Receptors, Odorant Smell |
description |
In natural environments, odors are typically mixtures of several different chemical compounds. However, the implications of mixtures for odor processing have not been fully investigated. We have extended a standard olfactory receptor model to mixtures and found through its mathematical analysis that odorant-evoked activity patterns are more stable across concentrations and first-spike latencies of receptor neurons are shorter for mixtures than for pure odorants. Shorter first-spike latencies arise from the nonlinear dependence of binding rate on odorant concentration, commonly described by the Hill coefficient, while the more stable activity patterns result from the competition between different ligands for receptor sites. These results are consistent with observations from numerical simulations and physiological recordings in the olfactory system of insects. Our results suggest that mixtures allow faster and more reliable olfactory coding, which could be one of the reasons why animals often use mixtures in chemical signaling. © 2018 Chan et al. http://creativecommons.org/licenses/by/4.0/. |
format |
JOUR |
author |
Chan, H.K. Hersperger, F. Marachlian, E. Smith, B.H. Locatelli, F. Szyszka, P. Nowotny, T. |
author_facet |
Chan, H.K. Hersperger, F. Marachlian, E. Smith, B.H. Locatelli, F. Szyszka, P. Nowotny, T. |
author_sort |
Chan, H.K. |
title |
Odorant mixtures elicit less variable and faster responses than pure odorants |
title_short |
Odorant mixtures elicit less variable and faster responses than pure odorants |
title_full |
Odorant mixtures elicit less variable and faster responses than pure odorants |
title_fullStr |
Odorant mixtures elicit less variable and faster responses than pure odorants |
title_full_unstemmed |
Odorant mixtures elicit less variable and faster responses than pure odorants |
title_sort |
odorant mixtures elicit less variable and faster responses than pure odorants |
url |
http://hdl.handle.net/20.500.12110/paper_1553734X_v14_n12_p_Chan |
work_keys_str_mv |
AT chanhk odorantmixtureselicitlessvariableandfasterresponsesthanpureodorants AT herspergerf odorantmixtureselicitlessvariableandfasterresponsesthanpureodorants AT marachliane odorantmixtureselicitlessvariableandfasterresponsesthanpureodorants AT smithbh odorantmixtureselicitlessvariableandfasterresponsesthanpureodorants AT locatellif odorantmixtureselicitlessvariableandfasterresponsesthanpureodorants AT szyszkap odorantmixtureselicitlessvariableandfasterresponsesthanpureodorants AT nowotnyt odorantmixtureselicitlessvariableandfasterresponsesthanpureodorants |
_version_ |
1807320604541452288 |