Heterogeneity and convergence of olfactory first-order neurons account for the high speed and sensitivity of second-order neurons.
Identifieur interne : 000060 ( PubMed/Corpus ); précédent : 000059; suivant : 000061Heterogeneity and convergence of olfactory first-order neurons account for the high speed and sensitivity of second-order neurons.
Auteurs : Jean-Pierre Rospars ; Alexandre Grémiaux ; David Jarriault ; Antoine Chaffiol ; Christelle Monsempes ; Nina Deisig ; Sylvia Anton ; Philippe Lucas ; Dominique MartinezSource :
- PLoS computational biology [ 1553-7358 ] ; 2014.
English descriptors
- KwdEn :
- MESH :
- chemical , metabolism : Pheromones.
- metabolism : Olfactory Receptor Neurons.
- physiology : Moths, Neurons, Olfactory Pathways, Olfactory Receptor Neurons.
- Animals, Computational Biology, Male, Models, Neurological.
Abstract
In the olfactory system of male moths, a specialized subset of neurons detects and processes the main component of the sex pheromone emitted by females. It is composed of several thousand first-order olfactory receptor neurons (ORNs), all expressing the same pheromone receptor, that contact synaptically a few tens of second-order projection neurons (PNs) within a single restricted brain area. The functional simplicity of this system makes it a favorable model for studying the factors that contribute to its exquisite sensitivity and speed. Sensory information--primarily the identity and intensity of the stimulus--is encoded as the firing rate of the action potentials, and possibly as the latency of the neuron response. We found that over all their dynamic range, PNs respond with a shorter latency and a higher firing rate than most ORNs. Modelling showed that the increased sensitivity of PNs can be explained by the ORN-to-PN convergent architecture alone, whereas their faster response also requires cell-to-cell heterogeneity of the ORN population. So, far from being detrimental to signal detection, the ORN heterogeneity is exploited by PNs, and results in two different schemes of population coding based either on the response of a few extreme neurons (latency) or on the average response of many (firing rate). Moreover, ORN-to-PN transformations are linear for latency and nonlinear for firing rate, suggesting that latency could be involved in concentration-invariant coding of the pheromone blend and that sensitivity at low concentrations is achieved at the expense of precise encoding at high concentrations.
DOI: 10.1371/journal.pcbi.1003975
PubMed: 25474026
Links to Exploration step
pubmed:25474026Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Heterogeneity and convergence of olfactory first-order neurons account for the high speed and sensitivity of second-order neurons.</title><author><name sortKey="Rospars, Jean Pierre" sort="Rospars, Jean Pierre" uniqKey="Rospars J" first="Jean-Pierre" last="Rospars">Jean-Pierre Rospars</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Gremiaux, Alexandre" sort="Gremiaux, Alexandre" uniqKey="Gremiaux A" first="Alexandre" last="Grémiaux">Alexandre Grémiaux</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Jarriault, David" sort="Jarriault, David" uniqKey="Jarriault D" first="David" last="Jarriault">David Jarriault</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Chaffiol, Antoine" sort="Chaffiol, Antoine" uniqKey="Chaffiol A" first="Antoine" last="Chaffiol">Antoine Chaffiol</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Monsempes, Christelle" sort="Monsempes, Christelle" uniqKey="Monsempes C" first="Christelle" last="Monsempes">Christelle Monsempes</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Deisig, Nina" sort="Deisig, Nina" uniqKey="Deisig N" first="Nina" last="Deisig">Nina Deisig</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Anton, Sylvia" sort="Anton, Sylvia" uniqKey="Anton S" first="Sylvia" last="Anton">Sylvia Anton</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Lucas, Philippe" sort="Lucas, Philippe" uniqKey="Lucas P" first="Philippe" last="Lucas">Philippe Lucas</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Martinez, Dominique" sort="Martinez, Dominique" uniqKey="Martinez D" first="Dominique" last="Martinez">Dominique Martinez</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France; Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Unité Mixte de Recherche 7503, Centre National de la Recherche Scientifique (CNRS), Vandœuvre-lès-Nancy, France.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2014">2014</date><idno type="doi">10.1371/journal.pcbi.1003975</idno><idno type="RBID">pubmed:25474026</idno><idno type="pmid">25474026</idno><idno type="wicri:Area/PubMed/Corpus">000060</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000060</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Heterogeneity and convergence of olfactory first-order neurons account for the high speed and sensitivity of second-order neurons.</title><author><name sortKey="Rospars, Jean Pierre" sort="Rospars, Jean Pierre" uniqKey="Rospars J" first="Jean-Pierre" last="Rospars">Jean-Pierre Rospars</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Gremiaux, Alexandre" sort="Gremiaux, Alexandre" uniqKey="Gremiaux A" first="Alexandre" last="Grémiaux">Alexandre Grémiaux</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Jarriault, David" sort="Jarriault, David" uniqKey="Jarriault D" first="David" last="Jarriault">David Jarriault</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Chaffiol, Antoine" sort="Chaffiol, Antoine" uniqKey="Chaffiol A" first="Antoine" last="Chaffiol">Antoine Chaffiol</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Monsempes, Christelle" sort="Monsempes, Christelle" uniqKey="Monsempes C" first="Christelle" last="Monsempes">Christelle Monsempes</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Deisig, Nina" sort="Deisig, Nina" uniqKey="Deisig N" first="Nina" last="Deisig">Nina Deisig</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Anton, Sylvia" sort="Anton, Sylvia" uniqKey="Anton S" first="Sylvia" last="Anton">Sylvia Anton</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Lucas, Philippe" sort="Lucas, Philippe" uniqKey="Lucas P" first="Philippe" last="Lucas">Philippe Lucas</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</nlm:affiliation></affiliation></author><author><name sortKey="Martinez, Dominique" sort="Martinez, Dominique" uniqKey="Martinez D" first="Dominique" last="Martinez">Dominique Martinez</name><affiliation><nlm:affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France; Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Unité Mixte de Recherche 7503, Centre National de la Recherche Scientifique (CNRS), Vandœuvre-lès-Nancy, France.</nlm:affiliation></affiliation></author></analytic><series><title level="j">PLoS computational biology</title><idno type="eISSN">1553-7358</idno><imprint><date when="2014" type="published">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Animals</term><term>Computational Biology</term><term>Male</term><term>Models, Neurological</term><term>Moths (physiology)</term><term>Neurons (physiology)</term><term>Olfactory Pathways (physiology)</term><term>Olfactory Receptor Neurons (metabolism)</term><term>Olfactory Receptor Neurons (physiology)</term><term>Pheromones (metabolism)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="metabolism" xml:lang="en"><term>Pheromones</term></keywords><keywords scheme="MESH" qualifier="metabolism" xml:lang="en"><term>Olfactory Receptor Neurons</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Moths</term><term>Neurons</term><term>Olfactory Pathways</term><term>Olfactory Receptor Neurons</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Computational Biology</term><term>Male</term><term>Models, Neurological</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In the olfactory system of male moths, a specialized subset of neurons detects and processes the main component of the sex pheromone emitted by females. It is composed of several thousand first-order olfactory receptor neurons (ORNs), all expressing the same pheromone receptor, that contact synaptically a few tens of second-order projection neurons (PNs) within a single restricted brain area. The functional simplicity of this system makes it a favorable model for studying the factors that contribute to its exquisite sensitivity and speed. Sensory information--primarily the identity and intensity of the stimulus--is encoded as the firing rate of the action potentials, and possibly as the latency of the neuron response. We found that over all their dynamic range, PNs respond with a shorter latency and a higher firing rate than most ORNs. Modelling showed that the increased sensitivity of PNs can be explained by the ORN-to-PN convergent architecture alone, whereas their faster response also requires cell-to-cell heterogeneity of the ORN population. So, far from being detrimental to signal detection, the ORN heterogeneity is exploited by PNs, and results in two different schemes of population coding based either on the response of a few extreme neurons (latency) or on the average response of many (firing rate). Moreover, ORN-to-PN transformations are linear for latency and nonlinear for firing rate, suggesting that latency could be involved in concentration-invariant coding of the pheromone blend and that sensitivity at low concentrations is achieved at the expense of precise encoding at high concentrations.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">25474026</PMID><DateCreated><Year>2014</Year><Month>12</Month><Day>05</Day></DateCreated><DateCompleted><Year>2016</Year><Month>01</Month><Day>05</Day></DateCompleted><DateRevised><Year>2014</Year><Month>12</Month><Day>15</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1553-7358</ISSN><JournalIssue CitedMedium="Internet"><Volume>10</Volume><Issue>12</Issue><PubDate><Year>2014</Year><Month>Dec</Month></PubDate></JournalIssue><Title>PLoS computational biology</Title><ISOAbbreviation>PLoS Comput. Biol.</ISOAbbreviation></Journal><ArticleTitle>Heterogeneity and convergence of olfactory first-order neurons account for the high speed and sensitivity of second-order neurons.</ArticleTitle><Pagination><MedlinePgn>e1003975</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pcbi.1003975</ELocationID><Abstract><AbstractText>In the olfactory system of male moths, a specialized subset of neurons detects and processes the main component of the sex pheromone emitted by females. It is composed of several thousand first-order olfactory receptor neurons (ORNs), all expressing the same pheromone receptor, that contact synaptically a few tens of second-order projection neurons (PNs) within a single restricted brain area. The functional simplicity of this system makes it a favorable model for studying the factors that contribute to its exquisite sensitivity and speed. Sensory information--primarily the identity and intensity of the stimulus--is encoded as the firing rate of the action potentials, and possibly as the latency of the neuron response. We found that over all their dynamic range, PNs respond with a shorter latency and a higher firing rate than most ORNs. Modelling showed that the increased sensitivity of PNs can be explained by the ORN-to-PN convergent architecture alone, whereas their faster response also requires cell-to-cell heterogeneity of the ORN population. So, far from being detrimental to signal detection, the ORN heterogeneity is exploited by PNs, and results in two different schemes of population coding based either on the response of a few extreme neurons (latency) or on the average response of many (firing rate). Moreover, ORN-to-PN transformations are linear for latency and nonlinear for firing rate, suggesting that latency could be involved in concentration-invariant coding of the pheromone blend and that sensitivity at low concentrations is achieved at the expense of precise encoding at high concentrations.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Rospars</LastName><ForeName>Jean-Pierre</ForeName><Initials>JP</Initials><AffiliationInfo><Affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Grémiaux</LastName><ForeName>Alexandre</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jarriault</LastName><ForeName>David</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chaffiol</LastName><ForeName>Antoine</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Monsempes</LastName><ForeName>Christelle</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Deisig</LastName><ForeName>Nina</ForeName><Initials>N</Initials><AffiliationInfo><Affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Anton</LastName><ForeName>Sylvia</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lucas</LastName><ForeName>Philippe</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Martinez</LastName><ForeName>Dominique</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France; Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Unité Mixte de Recherche 7503, Centre National de la Recherche Scientifique (CNRS), Vandœuvre-lès-Nancy, France.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2014</Year><Month>12</Month><Day>04</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS Comput Biol</MedlineTA><NlmUniqueID>101238922</NlmUniqueID><ISSNLinking>1553-734X</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D010675">Pheromones</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Trends Neurosci. 2007 Mar;30(3):92-100</RefSource><PMID Version="1">17224191</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Science. 1991 Aug 9;253(5020):675-7</RefSource><PMID Version="1">1908118</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Nat Neurosci. 2007 Nov;10(11):1474-82</RefSource><PMID Version="1">17922008</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>PLoS Biol. 2008 Jan;6(1):e16</RefSource><PMID Version="1">18232737</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>J Neurosci. 2008 Mar 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Neurological</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D009036">Moths</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D009474">Neurons</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D009833">Olfactory Pathways</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D018034">Olfactory Receptor Neurons</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000378">metabolism</QualifierName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D010675">Pheromones</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000378">metabolism</QualifierName></MeshHeading></MeshHeadingList><OtherID Source="NLM">PMC4256018</OtherID></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="ecollection"><Year>2014</Year><Month>12</Month><Day></Day></PubMedPubDate><PubMedPubDate PubStatus="received"><Year>2014</Year><Month>7</Month><Day>13</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2014</Year><Month>10</Month><Day>9</Day></PubMedPubDate><PubMedPubDate PubStatus="epublish"><Year>2014</Year><Month>12</Month><Day>4</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2014</Year><Month>12</Month><Day>5</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2014</Year><Month>12</Month><Day>5</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate 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