Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics

Autores
Dura Bernal, Salvador; Neymotin, Samuel A.; Suter, Benjamin A.; Dacre, Joshua; Moreira, Joao V. S.; Urdapilleta, Eugenio; Schiemann, Julia; Duguid, Ian; Shepherd, Gordon M. G.; Lytton, William W.
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Understanding cortical function requires studying multiple scales: molecular, cellular, circuit, and behavioral. We develop a multiscale, biophysically detailed model of mouse primary motor cortex (M1) with over 10,000 neurons and 30 million synapses. Neuron types, densities, spatial distributions, morphologies, biophysics, connectivity, and dendritic synapse locations are constrained by experimental data. The model includes long-range inputs from seven thalamic and cortical regions and noradrenergic inputs. Connectivity depends on cell class and cortical depth at sublaminar resolution. The model accurately predicts in vivo layer- and celltype-specific responses (firing rates and LFP) associated with behavioral states (quiet wakefulness and movement) and experimental manipulations (noradrenaline receptor blockade and thalamus inactivation). We generate mechanistic hypotheses underlying the observed activity and analyzed low-dimensional population latent dynamics. This quantitative theoretical framework can be used to integrate and interpret M1 experimental data and sheds light on the cell-type-specific multiscale dynamics associated with several experimental conditions and behaviors.
Fil: Dura Bernal, Salvador. State University of New York; Estados Unidos. Nathan S. Kline Institute for Psychiatric Research; Estados Unidos
Fil: Neymotin, Samuel A.. University Of New York. School Of Medicine; Estados Unidos. Nathan S. Kline Institute for Psychiatric Research; Estados Unidos
Fil: Suter, Benjamin A.. Northwestern University; Estados Unidos. Universidad de Basilea; Suiza
Fil: Dacre, Joshua. University of Edinburgh; Reino Unido
Fil: Moreira, Joao V. S.. State University of New York; Estados Unidos
Fil: Urdapilleta, Eugenio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; Argentina. State University of New York; Estados Unidos
Fil: Schiemann, Julia. University of Edinburgh; Reino Unido
Fil: Duguid, Ian. University of Edinburgh; Reino Unido. Universitat Saarland; Alemania
Fil: Shepherd, Gordon M. G.. Northwestern University; Estados Unidos
Fil: Lytton, William W.. State University of New York; Estados Unidos
Materia
Motor cortex
Cell type-specific
Cortical circuits
Computational model
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/235425
Acceder
id CONICETDig_89ac362ca163da27635bf0c3c59adb08
oai_identifier_str oai:ri.conicet.gov.ar:11336/235425
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamicsDura Bernal, SalvadorNeymotin, Samuel A.Suter, Benjamin A.Dacre, JoshuaMoreira, Joao V. S.Urdapilleta, EugenioSchiemann, JuliaDuguid, IanShepherd, Gordon M. G.Lytton, William W.Motor cortexCell type-specificCortical circuitsComputational modelhttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1Understanding cortical function requires studying multiple scales: molecular, cellular, circuit, and behavioral. We develop a multiscale, biophysically detailed model of mouse primary motor cortex (M1) with over 10,000 neurons and 30 million synapses. Neuron types, densities, spatial distributions, morphologies, biophysics, connectivity, and dendritic synapse locations are constrained by experimental data. The model includes long-range inputs from seven thalamic and cortical regions and noradrenergic inputs. Connectivity depends on cell class and cortical depth at sublaminar resolution. The model accurately predicts in vivo layer- and celltype-specific responses (firing rates and LFP) associated with behavioral states (quiet wakefulness and movement) and experimental manipulations (noradrenaline receptor blockade and thalamus inactivation). We generate mechanistic hypotheses underlying the observed activity and analyzed low-dimensional population latent dynamics. This quantitative theoretical framework can be used to integrate and interpret M1 experimental data and sheds light on the cell-type-specific multiscale dynamics associated with several experimental conditions and behaviors.Fil: Dura Bernal, Salvador. State University of New York; Estados Unidos. Nathan S. Kline Institute for Psychiatric Research; Estados UnidosFil: Neymotin, Samuel A.. University Of New York. School Of Medicine; Estados Unidos. Nathan S. Kline Institute for Psychiatric Research; Estados UnidosFil: Suter, Benjamin A.. Northwestern University; Estados Unidos. Universidad de Basilea; SuizaFil: Dacre, Joshua. University of Edinburgh; Reino UnidoFil: Moreira, Joao V. S.. State University of New York; Estados UnidosFil: Urdapilleta, Eugenio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; Argentina. State University of New York; Estados UnidosFil: Schiemann, Julia. University of Edinburgh; Reino UnidoFil: Duguid, Ian. University of Edinburgh; Reino Unido. Universitat Saarland; AlemaniaFil: Shepherd, Gordon M. G.. Northwestern University; Estados UnidosFil: Lytton, William W.. State University of New York; Estados UnidosCell Press2023-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/235425Dura Bernal, Salvador; Neymotin, Samuel A.; Suter, Benjamin A.; Dacre, Joshua; Moreira, Joao V. S.; et al.; Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics; Cell Press; Cell Reports; 42; 6; 6-2023; 1-292639-18562211-1247CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S2211124723005855info:eu-repo/semantics/altIdentifier/doi/10.1016/j.celrep.2023.112574info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:19:40Zoai:ri.conicet.gov.ar:11336/235425instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:19:41.131CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics
title Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics
spellingShingle Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics
Dura Bernal, Salvador
Motor cortex
Cell type-specific
Cortical circuits
Computational model
title_short Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics
title_full Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics
title_fullStr Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics
title_full_unstemmed Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics
title_sort Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics
dc.creator.none.fl_str_mv Dura Bernal, Salvador
Neymotin, Samuel A.
Suter, Benjamin A.
Dacre, Joshua
Moreira, Joao V. S.
Urdapilleta, Eugenio
Schiemann, Julia
Duguid, Ian
Shepherd, Gordon M. G.
Lytton, William W.
author Dura Bernal, Salvador
author_facet Dura Bernal, Salvador
Neymotin, Samuel A.
Suter, Benjamin A.
Dacre, Joshua
Moreira, Joao V. S.
Urdapilleta, Eugenio
Schiemann, Julia
Duguid, Ian
Shepherd, Gordon M. G.
Lytton, William W.
author_role author
author2 Neymotin, Samuel A.
Suter, Benjamin A.
Dacre, Joshua
Moreira, Joao V. S.
Urdapilleta, Eugenio
Schiemann, Julia
Duguid, Ian
Shepherd, Gordon M. G.
Lytton, William W.
author2_role author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Motor cortex
Cell type-specific
Cortical circuits
Computational model
topic Motor cortex
Cell type-specific
Cortical circuits
Computational model
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Understanding cortical function requires studying multiple scales: molecular, cellular, circuit, and behavioral. We develop a multiscale, biophysically detailed model of mouse primary motor cortex (M1) with over 10,000 neurons and 30 million synapses. Neuron types, densities, spatial distributions, morphologies, biophysics, connectivity, and dendritic synapse locations are constrained by experimental data. The model includes long-range inputs from seven thalamic and cortical regions and noradrenergic inputs. Connectivity depends on cell class and cortical depth at sublaminar resolution. The model accurately predicts in vivo layer- and celltype-specific responses (firing rates and LFP) associated with behavioral states (quiet wakefulness and movement) and experimental manipulations (noradrenaline receptor blockade and thalamus inactivation). We generate mechanistic hypotheses underlying the observed activity and analyzed low-dimensional population latent dynamics. This quantitative theoretical framework can be used to integrate and interpret M1 experimental data and sheds light on the cell-type-specific multiscale dynamics associated with several experimental conditions and behaviors.
Fil: Dura Bernal, Salvador. State University of New York; Estados Unidos. Nathan S. Kline Institute for Psychiatric Research; Estados Unidos
Fil: Neymotin, Samuel A.. University Of New York. School Of Medicine; Estados Unidos. Nathan S. Kline Institute for Psychiatric Research; Estados Unidos
Fil: Suter, Benjamin A.. Northwestern University; Estados Unidos. Universidad de Basilea; Suiza
Fil: Dacre, Joshua. University of Edinburgh; Reino Unido
Fil: Moreira, Joao V. S.. State University of New York; Estados Unidos
Fil: Urdapilleta, Eugenio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; Argentina. State University of New York; Estados Unidos
Fil: Schiemann, Julia. University of Edinburgh; Reino Unido
Fil: Duguid, Ian. University of Edinburgh; Reino Unido. Universitat Saarland; Alemania
Fil: Shepherd, Gordon M. G.. Northwestern University; Estados Unidos
Fil: Lytton, William W.. State University of New York; Estados Unidos
description Understanding cortical function requires studying multiple scales: molecular, cellular, circuit, and behavioral. We develop a multiscale, biophysically detailed model of mouse primary motor cortex (M1) with over 10,000 neurons and 30 million synapses. Neuron types, densities, spatial distributions, morphologies, biophysics, connectivity, and dendritic synapse locations are constrained by experimental data. The model includes long-range inputs from seven thalamic and cortical regions and noradrenergic inputs. Connectivity depends on cell class and cortical depth at sublaminar resolution. The model accurately predicts in vivo layer- and celltype-specific responses (firing rates and LFP) associated with behavioral states (quiet wakefulness and movement) and experimental manipulations (noradrenaline receptor blockade and thalamus inactivation). We generate mechanistic hypotheses underlying the observed activity and analyzed low-dimensional population latent dynamics. This quantitative theoretical framework can be used to integrate and interpret M1 experimental data and sheds light on the cell-type-specific multiscale dynamics associated with several experimental conditions and behaviors.
publishDate 2023
dc.date.none.fl_str_mv 2023-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/235425
Dura Bernal, Salvador; Neymotin, Samuel A.; Suter, Benjamin A.; Dacre, Joshua; Moreira, Joao V. S.; et al.; Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics; Cell Press; Cell Reports; 42; 6; 6-2023; 1-29
2639-1856
2211-1247
CONICET Digital
CONICET
url http://hdl.handle.net/11336/235425
identifier_str_mv Dura Bernal, Salvador; Neymotin, Samuel A.; Suter, Benjamin A.; Dacre, Joshua; Moreira, Joao V. S.; et al.; Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics; Cell Press; Cell Reports; 42; 6; 6-2023; 1-29
2639-1856
2211-1247
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S2211124723005855
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.celrep.2023.112574
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Cell Press
publisher.none.fl_str_mv Cell Press
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846083345766678528
score 13.22299

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