T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells

Autores
Beining, Marcel; Mongiat, Lucas Alberto; Schwarzacher, Stephan Wolfgang; Cuntz, Hermann; Jedlicka, Peter
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.
Fil: Beining, Marcel. Ernst Strungmann Institute; Alemania. Frankfurt Institute for Advanced Studies; Alemania. Goethe Universitat Frankfurt; Alemania
Fil: Mongiat, Lucas Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Schwarzacher, Stephan Wolfgang. Goethe Universitat Frankfurt; Alemania
Fil: Cuntz, Hermann. Frankfurt Institute for Advanced Studies; Alemania. Ernst Strungmann Institute; Alemania
Fil: Jedlicka, Peter. Goethe Universitat Frankfurt; Alemania
Materia
NEURONAL MODELING
HIPPOCAMPUS
ADULT NEUROGENESIS
COMPARTMENTAL MODELING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/69639
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/69639
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cellsBeining, MarcelMongiat, Lucas AlbertoSchwarzacher, Stephan WolfgangCuntz, HermannJedlicka, PeterNEURONAL MODELINGHIPPOCAMPUSADULT NEUROGENESISCOMPARTMENTAL MODELINGhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.Fil: Beining, Marcel. Ernst Strungmann Institute; Alemania. Frankfurt Institute for Advanced Studies; Alemania. Goethe Universitat Frankfurt; AlemaniaFil: Mongiat, Lucas Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Schwarzacher, Stephan Wolfgang. Goethe Universitat Frankfurt; AlemaniaFil: Cuntz, Hermann. Frankfurt Institute for Advanced Studies; Alemania. Ernst Strungmann Institute; AlemaniaFil: Jedlicka, Peter. Goethe Universitat Frankfurt; AlemaniaeLife Sciences Publications Ltd2017-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/69639Beining, Marcel; Mongiat, Lucas Alberto; Schwarzacher, Stephan Wolfgang; Cuntz, Hermann; Jedlicka, Peter; T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells; eLife Sciences Publications Ltd; eLife; 6; 11-2017; 1-562050-084XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.7554/eLife.26517.001info:eu-repo/semantics/altIdentifier/url/https://elifesciences.org/articles/26517info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:10:22Zoai:ri.conicet.gov.ar:11336/69639instacron: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 15:10:22.736CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells
title T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells
spellingShingle T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells
Beining, Marcel
NEURONAL MODELING
HIPPOCAMPUS
ADULT NEUROGENESIS
COMPARTMENTAL MODELING
title_short T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells
title_full T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells
title_fullStr T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells
title_full_unstemmed T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells
title_sort T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells
dc.creator.none.fl_str_mv Beining, Marcel
Mongiat, Lucas Alberto
Schwarzacher, Stephan Wolfgang
Cuntz, Hermann
Jedlicka, Peter
author Beining, Marcel
author_facet Beining, Marcel
Mongiat, Lucas Alberto
Schwarzacher, Stephan Wolfgang
Cuntz, Hermann
Jedlicka, Peter
author_role author
author2 Mongiat, Lucas Alberto
Schwarzacher, Stephan Wolfgang
Cuntz, Hermann
Jedlicka, Peter
author2_role author
author
author
author
dc.subject.none.fl_str_mv NEURONAL MODELING
HIPPOCAMPUS
ADULT NEUROGENESIS
COMPARTMENTAL MODELING
topic NEURONAL MODELING
HIPPOCAMPUS
ADULT NEUROGENESIS
COMPARTMENTAL MODELING
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.
Fil: Beining, Marcel. Ernst Strungmann Institute; Alemania. Frankfurt Institute for Advanced Studies; Alemania. Goethe Universitat Frankfurt; Alemania
Fil: Mongiat, Lucas Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Schwarzacher, Stephan Wolfgang. Goethe Universitat Frankfurt; Alemania
Fil: Cuntz, Hermann. Frankfurt Institute for Advanced Studies; Alemania. Ernst Strungmann Institute; Alemania
Fil: Jedlicka, Peter. Goethe Universitat Frankfurt; Alemania
description Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.
publishDate 2017
dc.date.none.fl_str_mv 2017-11
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/11336/69639
Beining, Marcel; Mongiat, Lucas Alberto; Schwarzacher, Stephan Wolfgang; Cuntz, Hermann; Jedlicka, Peter; T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells; eLife Sciences Publications Ltd; eLife; 6; 11-2017; 1-56
2050-084X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/69639
identifier_str_mv Beining, Marcel; Mongiat, Lucas Alberto; Schwarzacher, Stephan Wolfgang; Cuntz, Hermann; Jedlicka, Peter; T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells; eLife Sciences Publications Ltd; eLife; 6; 11-2017; 1-56
2050-084X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.7554/eLife.26517.001
info:eu-repo/semantics/altIdentifier/url/https://elifesciences.org/articles/26517
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv eLife Sciences Publications Ltd
publisher.none.fl_str_mv eLife Sciences Publications Ltd
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
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score 12.891075

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