Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex

Structural rules underlying functional properties of cortical circuits are poorly understood. To explore these rules systematically, we integrated information from extensive literature curation and large-scale experimental surveys into a data-driven, biologically realistic simulation of the awake mo...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Neuron (Cambridge, Mass.) Mass.), 2020-05, Vol.106 (3), p.388-403.e18
Hauptverfasser: Billeh, Yazan N., Cai, Binghuang, Gratiy, Sergey L., Dai, Kael, Iyer, Ramakrishnan, Gouwens, Nathan W., Abbasi-Asl, Reza, Jia, Xiaoxuan, Siegle, Joshua H., Olsen, Shawn R., Koch, Christof, Mihalas, Stefan, Arkhipov, Anton
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 403.e18
container_issue 3
container_start_page 388
container_title Neuron (Cambridge, Mass.)
container_volume 106
creator Billeh, Yazan N.
Cai, Binghuang
Gratiy, Sergey L.
Dai, Kael
Iyer, Ramakrishnan
Gouwens, Nathan W.
Abbasi-Asl, Reza
Jia, Xiaoxuan
Siegle, Joshua H.
Olsen, Shawn R.
Koch, Christof
Mihalas, Stefan
Arkhipov, Anton
description Structural rules underlying functional properties of cortical circuits are poorly understood. To explore these rules systematically, we integrated information from extensive literature curation and large-scale experimental surveys into a data-driven, biologically realistic simulation of the awake mouse primary visual cortex. The model was constructed at two levels of granularity, using either biophysically detailed or point neurons. Both variants have identical network connectivity and were compared to each other and to experimental recordings of visual-driven neural activity. While tuning these networks to recapitulate experimental data, we identified rules governing cell-class-specific connectivity and synaptic strengths. These structural constraints constitute hypotheses that can be tested experimentally. Despite their distinct single-cell abstraction, both spatially extended and point models perform similarly at the level of firing rate distributions for the questions we investigated. All data and models are freely available as a resource for the community. [Display omitted] •Two network models of the mouse primary visual cortex are developed and released•One uses compartmental-neuron models and the other point-neuron models•The models recapitulate observations from in vivo experimental data•Simulations identify experimentally testable predictions about cortex circuitry Billeh et al. systematically integrate multi-modal data about neuron types, connectivity, and sensory innervations to create biologically realistic models of the mouse primary visual cortex at two levels of resolution, shared freely as a community resource.
doi_str_mv 10.1016/j.neuron.2020.01.040
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2374307069</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0896627320300672</els_id><sourcerecordid>2374307069</sourcerecordid><originalsourceid>FETCH-LOGICAL-c436t-6caa066bd44df0d3a3e21afa5e5f1e1a4bdf746ae7131f9dd6c33c590f3eb593</originalsourceid><addsrcrecordid>eNp9kc9rFDEUx4Modlv9D0QCXrzM-DLJZHYugqy2FrootHgN2eRFssxOan6I_e_NMNWDB09JyOf7Xl4-hLxi0DJg8t2xnbHEMLcddNACa0HAE7JhMA6NYOP4lGxgO8pGdgM_I-cpHQGY6Ef2nJzxjolOiu2GhNuHlPGkszf0es74PdZtmGlw9DbHYnKJeqJ6tvSyzGa5qsePOmvq5xzovkzZN8noCek-WJzSktyHkpB-jf6k4wP95lOpoV2IGX-9IM-cnhK-fFwvyN3lp7vd5-bmy9X17sNNYwSXuZFGa5DyYIWwDizXHDumne6xdwyZFgfrBiE1DowzN1orDeemH8FxPPQjvyBv17L3MfwomLI6-WRwmvSM9XGq44PgMIBc0Df_oMdQYh2zUqLrpZRbua2UWCkTQ0oRnbpfx1MM1OJDHdXqQy0-FDBVfdTY68fi5XBC-zf0R0AF3q9A_Tr86TGqZDzOBq2PaLKywf-_w29HAp9h</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2425666868</pqid></control><display><type>article</type><title>Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex</title><source>Cell Press Free Archives</source><source>ScienceDirect Journals (5 years ago - present)</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Billeh, Yazan N. ; Cai, Binghuang ; Gratiy, Sergey L. ; Dai, Kael ; Iyer, Ramakrishnan ; Gouwens, Nathan W. ; Abbasi-Asl, Reza ; Jia, Xiaoxuan ; Siegle, Joshua H. ; Olsen, Shawn R. ; Koch, Christof ; Mihalas, Stefan ; Arkhipov, Anton</creator><creatorcontrib>Billeh, Yazan N. ; Cai, Binghuang ; Gratiy, Sergey L. ; Dai, Kael ; Iyer, Ramakrishnan ; Gouwens, Nathan W. ; Abbasi-Asl, Reza ; Jia, Xiaoxuan ; Siegle, Joshua H. ; Olsen, Shawn R. ; Koch, Christof ; Mihalas, Stefan ; Arkhipov, Anton</creatorcontrib><description>Structural rules underlying functional properties of cortical circuits are poorly understood. To explore these rules systematically, we integrated information from extensive literature curation and large-scale experimental surveys into a data-driven, biologically realistic simulation of the awake mouse primary visual cortex. The model was constructed at two levels of granularity, using either biophysically detailed or point neurons. Both variants have identical network connectivity and were compared to each other and to experimental recordings of visual-driven neural activity. While tuning these networks to recapitulate experimental data, we identified rules governing cell-class-specific connectivity and synaptic strengths. These structural constraints constitute hypotheses that can be tested experimentally. Despite their distinct single-cell abstraction, both spatially extended and point models perform similarly at the level of firing rate distributions for the questions we investigated. All data and models are freely available as a resource for the community. [Display omitted] •Two network models of the mouse primary visual cortex are developed and released•One uses compartmental-neuron models and the other point-neuron models•The models recapitulate observations from in vivo experimental data•Simulations identify experimentally testable predictions about cortex circuitry Billeh et al. systematically integrate multi-modal data about neuron types, connectivity, and sensory innervations to create biologically realistic models of the mouse primary visual cortex at two levels of resolution, shared freely as a community resource.</description><identifier>ISSN: 0896-6273</identifier><identifier>EISSN: 1097-4199</identifier><identifier>DOI: 10.1016/j.neuron.2020.01.040</identifier><identifier>PMID: 32142648</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Animal models ; Firing rate ; Functional morphology ; Information processing ; Neural networks ; Neurons ; Physiology ; Structure-function relationships ; Visual cortex ; Visual pathways</subject><ispartof>Neuron (Cambridge, Mass.), 2020-05, Vol.106 (3), p.388-403.e18</ispartof><rights>2020 Elsevier Inc.</rights><rights>Copyright © 2020 Elsevier Inc. All rights reserved.</rights><rights>2020. Elsevier Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c436t-6caa066bd44df0d3a3e21afa5e5f1e1a4bdf746ae7131f9dd6c33c590f3eb593</citedby><cites>FETCH-LOGICAL-c436t-6caa066bd44df0d3a3e21afa5e5f1e1a4bdf746ae7131f9dd6c33c590f3eb593</cites><orcidid>0000-0001-5200-4992 ; 0000-0003-1106-8310</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.neuron.2020.01.040$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,3548,27922,27923,45993</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32142648$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Billeh, Yazan N.</creatorcontrib><creatorcontrib>Cai, Binghuang</creatorcontrib><creatorcontrib>Gratiy, Sergey L.</creatorcontrib><creatorcontrib>Dai, Kael</creatorcontrib><creatorcontrib>Iyer, Ramakrishnan</creatorcontrib><creatorcontrib>Gouwens, Nathan W.</creatorcontrib><creatorcontrib>Abbasi-Asl, Reza</creatorcontrib><creatorcontrib>Jia, Xiaoxuan</creatorcontrib><creatorcontrib>Siegle, Joshua H.</creatorcontrib><creatorcontrib>Olsen, Shawn R.</creatorcontrib><creatorcontrib>Koch, Christof</creatorcontrib><creatorcontrib>Mihalas, Stefan</creatorcontrib><creatorcontrib>Arkhipov, Anton</creatorcontrib><title>Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex</title><title>Neuron (Cambridge, Mass.)</title><addtitle>Neuron</addtitle><description>Structural rules underlying functional properties of cortical circuits are poorly understood. To explore these rules systematically, we integrated information from extensive literature curation and large-scale experimental surveys into a data-driven, biologically realistic simulation of the awake mouse primary visual cortex. The model was constructed at two levels of granularity, using either biophysically detailed or point neurons. Both variants have identical network connectivity and were compared to each other and to experimental recordings of visual-driven neural activity. While tuning these networks to recapitulate experimental data, we identified rules governing cell-class-specific connectivity and synaptic strengths. These structural constraints constitute hypotheses that can be tested experimentally. Despite their distinct single-cell abstraction, both spatially extended and point models perform similarly at the level of firing rate distributions for the questions we investigated. All data and models are freely available as a resource for the community. [Display omitted] •Two network models of the mouse primary visual cortex are developed and released•One uses compartmental-neuron models and the other point-neuron models•The models recapitulate observations from in vivo experimental data•Simulations identify experimentally testable predictions about cortex circuitry Billeh et al. systematically integrate multi-modal data about neuron types, connectivity, and sensory innervations to create biologically realistic models of the mouse primary visual cortex at two levels of resolution, shared freely as a community resource.</description><subject>Animal models</subject><subject>Firing rate</subject><subject>Functional morphology</subject><subject>Information processing</subject><subject>Neural networks</subject><subject>Neurons</subject><subject>Physiology</subject><subject>Structure-function relationships</subject><subject>Visual cortex</subject><subject>Visual pathways</subject><issn>0896-6273</issn><issn>1097-4199</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kc9rFDEUx4Modlv9D0QCXrzM-DLJZHYugqy2FrootHgN2eRFssxOan6I_e_NMNWDB09JyOf7Xl4-hLxi0DJg8t2xnbHEMLcddNACa0HAE7JhMA6NYOP4lGxgO8pGdgM_I-cpHQGY6Ef2nJzxjolOiu2GhNuHlPGkszf0es74PdZtmGlw9DbHYnKJeqJ6tvSyzGa5qsePOmvq5xzovkzZN8noCek-WJzSktyHkpB-jf6k4wP95lOpoV2IGX-9IM-cnhK-fFwvyN3lp7vd5-bmy9X17sNNYwSXuZFGa5DyYIWwDizXHDumne6xdwyZFgfrBiE1DowzN1orDeemH8FxPPQjvyBv17L3MfwomLI6-WRwmvSM9XGq44PgMIBc0Df_oMdQYh2zUqLrpZRbua2UWCkTQ0oRnbpfx1MM1OJDHdXqQy0-FDBVfdTY68fi5XBC-zf0R0AF3q9A_Tr86TGqZDzOBq2PaLKywf-_w29HAp9h</recordid><startdate>20200506</startdate><enddate>20200506</enddate><creator>Billeh, Yazan N.</creator><creator>Cai, Binghuang</creator><creator>Gratiy, Sergey L.</creator><creator>Dai, Kael</creator><creator>Iyer, Ramakrishnan</creator><creator>Gouwens, Nathan W.</creator><creator>Abbasi-Asl, Reza</creator><creator>Jia, Xiaoxuan</creator><creator>Siegle, Joshua H.</creator><creator>Olsen, Shawn R.</creator><creator>Koch, Christof</creator><creator>Mihalas, Stefan</creator><creator>Arkhipov, Anton</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><scope>6I.</scope><scope>AAFTH</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QP</scope><scope>7QR</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-5200-4992</orcidid><orcidid>https://orcid.org/0000-0003-1106-8310</orcidid></search><sort><creationdate>20200506</creationdate><title>Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex</title><author>Billeh, Yazan N. ; Cai, Binghuang ; Gratiy, Sergey L. ; Dai, Kael ; Iyer, Ramakrishnan ; Gouwens, Nathan W. ; Abbasi-Asl, Reza ; Jia, Xiaoxuan ; Siegle, Joshua H. ; Olsen, Shawn R. ; Koch, Christof ; Mihalas, Stefan ; Arkhipov, Anton</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c436t-6caa066bd44df0d3a3e21afa5e5f1e1a4bdf746ae7131f9dd6c33c590f3eb593</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Animal models</topic><topic>Firing rate</topic><topic>Functional morphology</topic><topic>Information processing</topic><topic>Neural networks</topic><topic>Neurons</topic><topic>Physiology</topic><topic>Structure-function relationships</topic><topic>Visual cortex</topic><topic>Visual pathways</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Billeh, Yazan N.</creatorcontrib><creatorcontrib>Cai, Binghuang</creatorcontrib><creatorcontrib>Gratiy, Sergey L.</creatorcontrib><creatorcontrib>Dai, Kael</creatorcontrib><creatorcontrib>Iyer, Ramakrishnan</creatorcontrib><creatorcontrib>Gouwens, Nathan W.</creatorcontrib><creatorcontrib>Abbasi-Asl, Reza</creatorcontrib><creatorcontrib>Jia, Xiaoxuan</creatorcontrib><creatorcontrib>Siegle, Joshua H.</creatorcontrib><creatorcontrib>Olsen, Shawn R.</creatorcontrib><creatorcontrib>Koch, Christof</creatorcontrib><creatorcontrib>Mihalas, Stefan</creatorcontrib><creatorcontrib>Arkhipov, Anton</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Calcium &amp; Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Neuron (Cambridge, Mass.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Billeh, Yazan N.</au><au>Cai, Binghuang</au><au>Gratiy, Sergey L.</au><au>Dai, Kael</au><au>Iyer, Ramakrishnan</au><au>Gouwens, Nathan W.</au><au>Abbasi-Asl, Reza</au><au>Jia, Xiaoxuan</au><au>Siegle, Joshua H.</au><au>Olsen, Shawn R.</au><au>Koch, Christof</au><au>Mihalas, Stefan</au><au>Arkhipov, Anton</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex</atitle><jtitle>Neuron (Cambridge, Mass.)</jtitle><addtitle>Neuron</addtitle><date>2020-05-06</date><risdate>2020</risdate><volume>106</volume><issue>3</issue><spage>388</spage><epage>403.e18</epage><pages>388-403.e18</pages><issn>0896-6273</issn><eissn>1097-4199</eissn><abstract>Structural rules underlying functional properties of cortical circuits are poorly understood. To explore these rules systematically, we integrated information from extensive literature curation and large-scale experimental surveys into a data-driven, biologically realistic simulation of the awake mouse primary visual cortex. The model was constructed at two levels of granularity, using either biophysically detailed or point neurons. Both variants have identical network connectivity and were compared to each other and to experimental recordings of visual-driven neural activity. While tuning these networks to recapitulate experimental data, we identified rules governing cell-class-specific connectivity and synaptic strengths. These structural constraints constitute hypotheses that can be tested experimentally. Despite their distinct single-cell abstraction, both spatially extended and point models perform similarly at the level of firing rate distributions for the questions we investigated. All data and models are freely available as a resource for the community. [Display omitted] •Two network models of the mouse primary visual cortex are developed and released•One uses compartmental-neuron models and the other point-neuron models•The models recapitulate observations from in vivo experimental data•Simulations identify experimentally testable predictions about cortex circuitry Billeh et al. systematically integrate multi-modal data about neuron types, connectivity, and sensory innervations to create biologically realistic models of the mouse primary visual cortex at two levels of resolution, shared freely as a community resource.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>32142648</pmid><doi>10.1016/j.neuron.2020.01.040</doi><orcidid>https://orcid.org/0000-0001-5200-4992</orcidid><orcidid>https://orcid.org/0000-0003-1106-8310</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0896-6273
ispartof Neuron (Cambridge, Mass.), 2020-05, Vol.106 (3), p.388-403.e18
issn 0896-6273
1097-4199
language eng
recordid cdi_proquest_miscellaneous_2374307069
source Cell Press Free Archives; ScienceDirect Journals (5 years ago - present); EZB-FREE-00999 freely available EZB journals
subjects Animal models
Firing rate
Functional morphology
Information processing
Neural networks
Neurons
Physiology
Structure-function relationships
Visual cortex
Visual pathways
title Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T20%3A58%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Systematic%20Integration%20of%20Structural%20and%20Functional%20Data%20into%20Multi-scale%20Models%20of%20Mouse%20Primary%20Visual%20Cortex&rft.jtitle=Neuron%20(Cambridge,%20Mass.)&rft.au=Billeh,%20Yazan%20N.&rft.date=2020-05-06&rft.volume=106&rft.issue=3&rft.spage=388&rft.epage=403.e18&rft.pages=388-403.e18&rft.issn=0896-6273&rft.eissn=1097-4199&rft_id=info:doi/10.1016/j.neuron.2020.01.040&rft_dat=%3Cproquest_cross%3E2374307069%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2425666868&rft_id=info:pmid/32142648&rft_els_id=S0896627320300672&rfr_iscdi=true