Emergence of stochastic resonance in a two-compartment hippocampal pyramidal neuron model
In vitro studies have shown that hippocampal pyramidal neurons employ a mechanism similar to stochastic resonance (SR) to enhance the detection and transmission of weak stimuli generated at distal synapses. To support the experimental findings from the perspective of multicompartment model analysis,...
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| Veröffentlicht in: | Journal of computational neuroscience 2022-05, Vol.50 (2), p.217-240 |
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| creator | Ghori, Muhammad Bilal Kang, Yanmei Chen, Yaqian |
| description | In vitro
studies have shown that hippocampal pyramidal neurons employ a mechanism similar to stochastic resonance (SR) to enhance the detection and transmission of weak stimuli generated at distal synapses. To support the experimental findings from the perspective of multicompartment model analysis, this paper aimed to elucidate the phenomenon of SR in a noisy two-compartment hippocampal pyramidal neuron model, which was a variant of the Pinsky-Rinzel neuron model with smooth activation functions and a hyperpolarization-activated cation current. With a bifurcation analysis of the model, we demonstrated the underlying dynamical structure responsible for the occurrence of SR. Furthermore, using a stochastically generated biphasic pulse train and broadband noise generated by the Orenstein-Uhlenbeck process as noise perturbation, both SR and suprathreshold SR were observed and quantified. Spectral analysis revealed that the distribution of spectral power under noise perturbations, in addition to inherent neurodynamics, is the main factor affecting SR behavior. The research results suggested that noise enhances the transmission of weak stimuli associated with elongated dendritic structures of hippocampal pyramidal neurons, thereby providing support for related laboratory findings. |
| doi_str_mv | 10.1007/s10827-021-00808-2 |
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studies have shown that hippocampal pyramidal neurons employ a mechanism similar to stochastic resonance (SR) to enhance the detection and transmission of weak stimuli generated at distal synapses. To support the experimental findings from the perspective of multicompartment model analysis, this paper aimed to elucidate the phenomenon of SR in a noisy two-compartment hippocampal pyramidal neuron model, which was a variant of the Pinsky-Rinzel neuron model with smooth activation functions and a hyperpolarization-activated cation current. With a bifurcation analysis of the model, we demonstrated the underlying dynamical structure responsible for the occurrence of SR. Furthermore, using a stochastically generated biphasic pulse train and broadband noise generated by the Orenstein-Uhlenbeck process as noise perturbation, both SR and suprathreshold SR were observed and quantified. Spectral analysis revealed that the distribution of spectral power under noise perturbations, in addition to inherent neurodynamics, is the main factor affecting SR behavior. The research results suggested that noise enhances the transmission of weak stimuli associated with elongated dendritic structures of hippocampal pyramidal neurons, thereby providing support for related laboratory findings.</description><identifier>ISSN: 0929-5313</identifier><identifier>EISSN: 1573-6873</identifier><identifier>DOI: 10.1007/s10827-021-00808-2</identifier><identifier>PMID: 35022992</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Biomedical and Life Sciences ; Biomedicine ; Broadband ; Dendritic structure ; Electric power distribution ; Elongated structure ; Hippocampus ; Hippocampus - physiology ; Human Genetics ; Hyperpolarization ; Models, Neurological ; Neurology ; Neurons ; Neurons - physiology ; Neurosciences ; Noise ; Original Article ; Perturbation ; Pyramidal cells ; Pyramidal Cells - physiology ; Resonance ; Spectral analysis ; Spectrum analysis ; Stimuli ; Stochastic Processes ; Stochastic resonance ; Synapses ; Theory of Computation</subject><ispartof>Journal of computational neuroscience, 2022-05, Vol.50 (2), p.217-240</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021</rights><rights>2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.</rights><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c441t-608943cf392125f4d68d6276f3443b5c5b0cfa82b0bb6fc3f8d907041e0211dd3</citedby><cites>FETCH-LOGICAL-c441t-608943cf392125f4d68d6276f3443b5c5b0cfa82b0bb6fc3f8d907041e0211dd3</cites><orcidid>0000-0001-8608-9242</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10827-021-00808-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10827-021-00808-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35022992$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ghori, Muhammad Bilal</creatorcontrib><creatorcontrib>Kang, Yanmei</creatorcontrib><creatorcontrib>Chen, Yaqian</creatorcontrib><title>Emergence of stochastic resonance in a two-compartment hippocampal pyramidal neuron model</title><title>Journal of computational neuroscience</title><addtitle>J Comput Neurosci</addtitle><addtitle>J Comput Neurosci</addtitle><description>In vitro
studies have shown that hippocampal pyramidal neurons employ a mechanism similar to stochastic resonance (SR) to enhance the detection and transmission of weak stimuli generated at distal synapses. To support the experimental findings from the perspective of multicompartment model analysis, this paper aimed to elucidate the phenomenon of SR in a noisy two-compartment hippocampal pyramidal neuron model, which was a variant of the Pinsky-Rinzel neuron model with smooth activation functions and a hyperpolarization-activated cation current. With a bifurcation analysis of the model, we demonstrated the underlying dynamical structure responsible for the occurrence of SR. Furthermore, using a stochastically generated biphasic pulse train and broadband noise generated by the Orenstein-Uhlenbeck process as noise perturbation, both SR and suprathreshold SR were observed and quantified. Spectral analysis revealed that the distribution of spectral power under noise perturbations, in addition to inherent neurodynamics, is the main factor affecting SR behavior. The research results suggested that noise enhances the transmission of weak stimuli associated with elongated dendritic structures of hippocampal pyramidal neurons, thereby providing support for related laboratory findings.</description><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Broadband</subject><subject>Dendritic structure</subject><subject>Electric power distribution</subject><subject>Elongated structure</subject><subject>Hippocampus</subject><subject>Hippocampus - physiology</subject><subject>Human Genetics</subject><subject>Hyperpolarization</subject><subject>Models, Neurological</subject><subject>Neurology</subject><subject>Neurons</subject><subject>Neurons - physiology</subject><subject>Neurosciences</subject><subject>Noise</subject><subject>Original Article</subject><subject>Perturbation</subject><subject>Pyramidal cells</subject><subject>Pyramidal Cells - physiology</subject><subject>Resonance</subject><subject>Spectral analysis</subject><subject>Spectrum analysis</subject><subject>Stimuli</subject><subject>Stochastic Processes</subject><subject>Stochastic resonance</subject><subject>Synapses</subject><subject>Theory of Computation</subject><issn>0929-5313</issn><issn>1573-6873</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp9kE1PwzAMhiMEYmPwBzigSly4BJykXzmiaXxISFzgwClK02Tr1CYlaYX278nYAIkDJ1v249f2i9A5gWsCUNwEAiUtMFCCAUooMT1AU5IVDOdlwQ7RFDjlOGOETdBJCGuIVEHgGE1YBpRyTqfobdFpv9RW6cSZJAxOrWQYGpV4HZyV23pjE5kMHw4r1_XSD522Q7Jq-t4pGQtt0m-87Jo6ZlaP3tmkc7VuT9GRkW3QZ_s4Q693i5f5A356vn-c3z5hlaZkwDmUPGXKME4JzUxa52Wd0yI3LE1ZlamsAmVkSSuoqtwoZsqaQwEp0fFvUtdshq52ur1376MOg-iaoHTbSqvdGATNCc9SEvdE9PIPunajt_G6SGUsZxHkkaI7SnkXgtdG9L7ppN8IAmJrvNgZL-IB4st4QePQxV56rDpd_4x8Ox0BtgNCbNml9r-7_5H9BEzKjbo</recordid><startdate>20220501</startdate><enddate>20220501</enddate><creator>Ghori, Muhammad Bilal</creator><creator>Kang, Yanmei</creator><creator>Chen, Yaqian</creator><general>Springer US</general><general>Springer Nature B.V</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>3V.</scope><scope>7QO</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</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>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-8608-9242</orcidid></search><sort><creationdate>20220501</creationdate><title>Emergence of stochastic resonance in a two-compartment hippocampal pyramidal neuron model</title><author>Ghori, Muhammad Bilal ; Kang, Yanmei ; Chen, Yaqian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c441t-608943cf392125f4d68d6276f3443b5c5b0cfa82b0bb6fc3f8d907041e0211dd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Broadband</topic><topic>Dendritic structure</topic><topic>Electric power distribution</topic><topic>Elongated structure</topic><topic>Hippocampus</topic><topic>Hippocampus - physiology</topic><topic>Human Genetics</topic><topic>Hyperpolarization</topic><topic>Models, Neurological</topic><topic>Neurology</topic><topic>Neurons</topic><topic>Neurons - physiology</topic><topic>Neurosciences</topic><topic>Noise</topic><topic>Original Article</topic><topic>Perturbation</topic><topic>Pyramidal cells</topic><topic>Pyramidal Cells - physiology</topic><topic>Resonance</topic><topic>Spectral analysis</topic><topic>Spectrum analysis</topic><topic>Stimuli</topic><topic>Stochastic Processes</topic><topic>Stochastic resonance</topic><topic>Synapses</topic><topic>Theory of Computation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ghori, Muhammad Bilal</creatorcontrib><creatorcontrib>Kang, Yanmei</creatorcontrib><creatorcontrib>Chen, Yaqian</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>ProQuest Pharma Collection</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 Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>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>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Psychology</collection><collection>Biological Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</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 China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of computational neuroscience</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ghori, Muhammad Bilal</au><au>Kang, Yanmei</au><au>Chen, Yaqian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Emergence of stochastic resonance in a two-compartment hippocampal pyramidal neuron model</atitle><jtitle>Journal of computational neuroscience</jtitle><stitle>J Comput Neurosci</stitle><addtitle>J Comput Neurosci</addtitle><date>2022-05-01</date><risdate>2022</risdate><volume>50</volume><issue>2</issue><spage>217</spage><epage>240</epage><pages>217-240</pages><issn>0929-5313</issn><eissn>1573-6873</eissn><abstract>In vitro
studies have shown that hippocampal pyramidal neurons employ a mechanism similar to stochastic resonance (SR) to enhance the detection and transmission of weak stimuli generated at distal synapses. To support the experimental findings from the perspective of multicompartment model analysis, this paper aimed to elucidate the phenomenon of SR in a noisy two-compartment hippocampal pyramidal neuron model, which was a variant of the Pinsky-Rinzel neuron model with smooth activation functions and a hyperpolarization-activated cation current. With a bifurcation analysis of the model, we demonstrated the underlying dynamical structure responsible for the occurrence of SR. Furthermore, using a stochastically generated biphasic pulse train and broadband noise generated by the Orenstein-Uhlenbeck process as noise perturbation, both SR and suprathreshold SR were observed and quantified. Spectral analysis revealed that the distribution of spectral power under noise perturbations, in addition to inherent neurodynamics, is the main factor affecting SR behavior. The research results suggested that noise enhances the transmission of weak stimuli associated with elongated dendritic structures of hippocampal pyramidal neurons, thereby providing support for related laboratory findings.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>35022992</pmid><doi>10.1007/s10827-021-00808-2</doi><tpages>24</tpages><orcidid>https://orcid.org/0000-0001-8608-9242</orcidid></addata></record> |
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| subjects | Biomedical and Life Sciences Biomedicine Broadband Dendritic structure Electric power distribution Elongated structure Hippocampus Hippocampus - physiology Human Genetics Hyperpolarization Models, Neurological Neurology Neurons Neurons - physiology Neurosciences Noise Original Article Perturbation Pyramidal cells Pyramidal Cells - physiology Resonance Spectral analysis Spectrum analysis Stimuli Stochastic Processes Stochastic resonance Synapses Theory of Computation |
| title | Emergence of stochastic resonance in a two-compartment hippocampal pyramidal neuron model |
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