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A coupled-oscillator model of olfactory bulb gamma oscillations
The olfactory bulb transforms not only the information content of the primary sensory representation, but also its underlying coding metric. High-variance, slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike p...
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Published in: | PLoS computational biology 2017-11, Vol.13 (11), p.e1005760-e1005760 |
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description | The olfactory bulb transforms not only the information content of the primary sensory representation, but also its underlying coding metric. High-variance, slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike patterns that are tightly regulated in time. This emergent fast timescale for signaling is reflected in gamma-band local field potentials, presumably serving to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system. To understand this transformation and its integration with interareal coordination mechanisms requires that we understand its fundamental dynamical principles. Using a biophysically explicit, multiscale model of olfactory bulb circuitry, we here demonstrate that an inhibition-coupled intrinsic oscillator framework, pyramidal resonance interneuron network gamma (PRING), best captures the diversity of physiological properties exhibited by the olfactory bulb. Most importantly, these properties include global zero-phase synchronization in the gamma band, the phase-restriction of informative spikes in principal neurons with respect to this common clock, and the robustness of this synchronous oscillatory regime to multiple challenging conditions observed in the biological system. These conditions include substantial heterogeneities in afferent activation levels and excitatory synaptic weights, high levels of uncorrelated background activity among principal neurons, and spike frequencies in both principal neurons and interneurons that are irregular in time and much lower than the gamma frequency. This coupled cellular oscillator architecture permits stable and replicable ensemble responses to diverse sensory stimuli under various external conditions as well as to changes in network parameters arising from learning-dependent synaptic plasticity. |
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High-variance, slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike patterns that are tightly regulated in time. This emergent fast timescale for signaling is reflected in gamma-band local field potentials, presumably serving to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system. To understand this transformation and its integration with interareal coordination mechanisms requires that we understand its fundamental dynamical principles. Using a biophysically explicit, multiscale model of olfactory bulb circuitry, we here demonstrate that an inhibition-coupled intrinsic oscillator framework, pyramidal resonance interneuron network gamma (PRING), best captures the diversity of physiological properties exhibited by the olfactory bulb. Most importantly, these properties include global zero-phase synchronization in the gamma band, the phase-restriction of informative spikes in principal neurons with respect to this common clock, and the robustness of this synchronous oscillatory regime to multiple challenging conditions observed in the biological system. These conditions include substantial heterogeneities in afferent activation levels and excitatory synaptic weights, high levels of uncorrelated background activity among principal neurons, and spike frequencies in both principal neurons and interneurons that are irregular in time and much lower than the gamma frequency. This coupled cellular oscillator architecture permits stable and replicable ensemble responses to diverse sensory stimuli under various external conditions as well as to changes in network parameters arising from learning-dependent synaptic plasticity.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1005760</identifier><identifier>PMID: 29140973</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Action Potentials ; Animals ; Bands ; Biology and Life Sciences ; Central nervous system ; Circuits ; Coding ; Computational Biology ; Computer and Information Sciences ; Firing pattern ; Funding ; Gamma Rhythm - physiology ; Genetic transformation ; Information processing ; Interneurons ; Medicine and Health Sciences ; Models, Neurological ; Nervous system ; Neural coding ; Neurons ; Odor ; Odors ; Olfactory bulb ; Olfactory Bulb - physiology ; Olfactory nerve ; Oscillations ; Physical Sciences ; Physiological aspects ; Rats ; Representations ; Sensory evaluation ; Sensory neurons ; Sensory stimuli ; Signaling ; Smell ; Synaptic plasticity ; Synaptic strength ; Synchronism ; Synchronization ; Time ; Transformation</subject><ispartof>PLoS computational biology, 2017-11, Vol.13 (11), p.e1005760-e1005760</ispartof><rights>COPYRIGHT 2017 Public Library of Science</rights><rights>2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Li G, Cleland TA (2017) A coupled-oscillator model of olfactory bulb gamma oscillations. PLoS Comput Biol 13(11): e1005760. https://doi.org/10.1371/journal.pcbi.1005760</rights><rights>2017 Li, Cleland 2017 Li, Cleland</rights><rights>2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Li G, Cleland TA (2017) A coupled-oscillator model of olfactory bulb gamma oscillations. PLoS Comput Biol 13(11): e1005760. https://doi.org/10.1371/journal.pcbi.1005760</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c661t-516679f5672b74d5216718a52d38f49b83d0ca1e02f773e142c396d53d79c0673</citedby><cites>FETCH-LOGICAL-c661t-516679f5672b74d5216718a52d38f49b83d0ca1e02f773e142c396d53d79c0673</cites><orcidid>0000-0001-7506-1201 ; 0000-0002-8984-4722</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1977641503/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1977641503?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29140973$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Ermentrout, Bard</contributor><creatorcontrib>Li, Guoshi</creatorcontrib><creatorcontrib>Cleland, Thomas A</creatorcontrib><title>A coupled-oscillator model of olfactory bulb gamma oscillations</title><title>PLoS computational biology</title><addtitle>PLoS Comput Biol</addtitle><description>The olfactory bulb transforms not only the information content of the primary sensory representation, but also its underlying coding metric. High-variance, slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike patterns that are tightly regulated in time. This emergent fast timescale for signaling is reflected in gamma-band local field potentials, presumably serving to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system. To understand this transformation and its integration with interareal coordination mechanisms requires that we understand its fundamental dynamical principles. Using a biophysically explicit, multiscale model of olfactory bulb circuitry, we here demonstrate that an inhibition-coupled intrinsic oscillator framework, pyramidal resonance interneuron network gamma (PRING), best captures the diversity of physiological properties exhibited by the olfactory bulb. Most importantly, these properties include global zero-phase synchronization in the gamma band, the phase-restriction of informative spikes in principal neurons with respect to this common clock, and the robustness of this synchronous oscillatory regime to multiple challenging conditions observed in the biological system. These conditions include substantial heterogeneities in afferent activation levels and excitatory synaptic weights, high levels of uncorrelated background activity among principal neurons, and spike frequencies in both principal neurons and interneurons that are irregular in time and much lower than the gamma frequency. This coupled cellular oscillator architecture permits stable and replicable ensemble responses to diverse sensory stimuli under various external conditions as well as to changes in network parameters arising from learning-dependent synaptic plasticity.</description><subject>Action Potentials</subject><subject>Animals</subject><subject>Bands</subject><subject>Biology and Life Sciences</subject><subject>Central nervous system</subject><subject>Circuits</subject><subject>Coding</subject><subject>Computational Biology</subject><subject>Computer and Information Sciences</subject><subject>Firing pattern</subject><subject>Funding</subject><subject>Gamma Rhythm - physiology</subject><subject>Genetic transformation</subject><subject>Information processing</subject><subject>Interneurons</subject><subject>Medicine and Health Sciences</subject><subject>Models, Neurological</subject><subject>Nervous system</subject><subject>Neural coding</subject><subject>Neurons</subject><subject>Odor</subject><subject>Odors</subject><subject>Olfactory bulb</subject><subject>Olfactory Bulb - physiology</subject><subject>Olfactory nerve</subject><subject>Oscillations</subject><subject>Physical Sciences</subject><subject>Physiological aspects</subject><subject>Rats</subject><subject>Representations</subject><subject>Sensory evaluation</subject><subject>Sensory neurons</subject><subject>Sensory stimuli</subject><subject>Signaling</subject><subject>Smell</subject><subject>Synaptic plasticity</subject><subject>Synaptic strength</subject><subject>Synchronism</subject><subject>Synchronization</subject><subject>Time</subject><subject>Transformation</subject><issn>1553-7358</issn><issn>1553-734X</issn><issn>1553-7358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqVkluL1DAUx4so7rr6DUQLvuhDx9zTvCjD4mVgUfDyHNJcaoa0GZtW3G9v6nSWreyL5CHh5Hf-55w_pyieQrCBmMPX-zgNvQqbg278BgJAOQP3inNIKa44pvX9W--z4lFKewDyU7CHxRkSkADB8XnxdlvqOB2CNVVM2oegxjiUXTQ2lNGVMTilc-S6bKbQlK3qOlWeQB_79Lh44FRI9slyXxTf37_7dvmxuvr8YXe5vao0Y3CsKGSMC0cZRw0nhiLIOKwVRQbXjoimxgZoBS1AjnNsIUEaC2YoNlxowDi-KJ4fdQ8hJrnMniQUnDMCKcCZ2B0JE9VeHgbfqeFaRuXl30AcWqmG0etgZS7rkNGiQVYQQpraCot5jRQxBgrjstabpdrUdNZo24-DCivR9U_vf8g2_pKUz83CLPByERjiz8mmUXY-aZtd622c5r4ZRZRwxDL64h_07ukWqlV5AN-7mOvqWVRus7mcccBnlzZ3UPkY23kde-t8jq8SXq0SMjPa32OrppTk7uuX_2A_rVlyZPUQUxqsu_EOAjmv72lIOa-vXNY3pz277ftN0mlf8R8frukx</recordid><startdate>20171101</startdate><enddate>20171101</enddate><creator>Li, Guoshi</creator><creator>Cleland, Thomas A</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISN</scope><scope>ISR</scope><scope>3V.</scope><scope>7QO</scope><scope>7QP</scope><scope>7TK</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>LK8</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-7506-1201</orcidid><orcidid>https://orcid.org/0000-0002-8984-4722</orcidid></search><sort><creationdate>20171101</creationdate><title>A coupled-oscillator model of olfactory bulb gamma oscillations</title><author>Li, Guoshi ; Cleland, Thomas A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c661t-516679f5672b74d5216718a52d38f49b83d0ca1e02f773e142c396d53d79c0673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Action Potentials</topic><topic>Animals</topic><topic>Bands</topic><topic>Biology and Life Sciences</topic><topic>Central nervous system</topic><topic>Circuits</topic><topic>Coding</topic><topic>Computational Biology</topic><topic>Computer and Information Sciences</topic><topic>Firing pattern</topic><topic>Funding</topic><topic>Gamma Rhythm - physiology</topic><topic>Genetic transformation</topic><topic>Information processing</topic><topic>Interneurons</topic><topic>Medicine and Health Sciences</topic><topic>Models, Neurological</topic><topic>Nervous system</topic><topic>Neural coding</topic><topic>Neurons</topic><topic>Odor</topic><topic>Odors</topic><topic>Olfactory bulb</topic><topic>Olfactory Bulb - physiology</topic><topic>Olfactory nerve</topic><topic>Oscillations</topic><topic>Physical Sciences</topic><topic>Physiological aspects</topic><topic>Rats</topic><topic>Representations</topic><topic>Sensory evaluation</topic><topic>Sensory neurons</topic><topic>Sensory stimuli</topic><topic>Signaling</topic><topic>Smell</topic><topic>Synaptic plasticity</topic><topic>Synaptic strength</topic><topic>Synchronism</topic><topic>Synchronization</topic><topic>Time</topic><topic>Transformation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Guoshi</creatorcontrib><creatorcontrib>Cleland, Thomas A</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Canada</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>ProQuest Biological Science Journals</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PLoS computational biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Guoshi</au><au>Cleland, Thomas A</au><au>Ermentrout, Bard</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A coupled-oscillator model of olfactory bulb gamma oscillations</atitle><jtitle>PLoS computational biology</jtitle><addtitle>PLoS Comput Biol</addtitle><date>2017-11-01</date><risdate>2017</risdate><volume>13</volume><issue>11</issue><spage>e1005760</spage><epage>e1005760</epage><pages>e1005760-e1005760</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><abstract>The olfactory bulb transforms not only the information content of the primary sensory representation, but also its underlying coding metric. High-variance, slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike patterns that are tightly regulated in time. This emergent fast timescale for signaling is reflected in gamma-band local field potentials, presumably serving to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system. To understand this transformation and its integration with interareal coordination mechanisms requires that we understand its fundamental dynamical principles. Using a biophysically explicit, multiscale model of olfactory bulb circuitry, we here demonstrate that an inhibition-coupled intrinsic oscillator framework, pyramidal resonance interneuron network gamma (PRING), best captures the diversity of physiological properties exhibited by the olfactory bulb. Most importantly, these properties include global zero-phase synchronization in the gamma band, the phase-restriction of informative spikes in principal neurons with respect to this common clock, and the robustness of this synchronous oscillatory regime to multiple challenging conditions observed in the biological system. These conditions include substantial heterogeneities in afferent activation levels and excitatory synaptic weights, high levels of uncorrelated background activity among principal neurons, and spike frequencies in both principal neurons and interneurons that are irregular in time and much lower than the gamma frequency. This coupled cellular oscillator architecture permits stable and replicable ensemble responses to diverse sensory stimuli under various external conditions as well as to changes in network parameters arising from learning-dependent synaptic plasticity.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>29140973</pmid><doi>10.1371/journal.pcbi.1005760</doi><orcidid>https://orcid.org/0000-0001-7506-1201</orcidid><orcidid>https://orcid.org/0000-0002-8984-4722</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Action Potentials Animals Bands Biology and Life Sciences Central nervous system Circuits Coding Computational Biology Computer and Information Sciences Firing pattern Funding Gamma Rhythm - physiology Genetic transformation Information processing Interneurons Medicine and Health Sciences Models, Neurological Nervous system Neural coding Neurons Odor Odors Olfactory bulb Olfactory Bulb - physiology Olfactory nerve Oscillations Physical Sciences Physiological aspects Rats Representations Sensory evaluation Sensory neurons Sensory stimuli Signaling Smell Synaptic plasticity Synaptic strength Synchronism Synchronization Time Transformation |
title | A coupled-oscillator model of olfactory bulb gamma oscillations |
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