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Structural and functional, empirical and modeled connectivity in the cerebral cortex of the rat

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Structural and functional, empirical and modeled connectivity in the cerebral cortex of the rat

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dc.contributor.author Díaz-Parra, Antonio es_ES
dc.contributor.author Osborn, Z. es_ES
dc.contributor.author Canals Gamoneda, Santiago es_ES
dc.contributor.author Moratal, David es_ES
dc.contributor.author Sporns, O. es_ES
dc.date.accessioned 2018-05-18T07:30:47Z
dc.date.available 2018-05-18T07:30:47Z
dc.date.issued 2017 es_ES
dc.identifier.issn 1053-8119 es_ES
dc.identifier.uri http://hdl.handle.net/10251/102205
dc.description.abstract [EN] Connectomics data from animal models provide an invaluable opportunity to reveal the complex interplay between structure and function in the mammalian brain. In this work, we investigate the relationship between structural and functional connectivity in the rat brain cortex using a directed anatomical network generated from a carefully curated meta-analysis of published tracing data, along with resting-state functional MRI data obtained from a group of 14 anesthetized Wistar rats. We found a high correspondence between the strength of functional connections, measured as blood oxygen level dependent (BOLD) signal correlations between cortical regions, and the weight of the corresponding anatomical links in the connectome graph (maximum Spearman rank-order correlation rho = 0.48). At the network-level, regions belonging to the same functionally defined community tend to form more mutual weighted connections between each other compared to regions located in different communities. We further found that functional communities in resting-state networks are enriched in densely connected anatomical motifs. Importantly, these higher-order structural subgraphs cannot be explained by lower-order topological properties, suggesting that dense structural patterns support functional associations in the resting brain. Simulations of brain-wide resting-state activity based on neural mass models implemented on the empirical rat anatomical connectome demonstrated high correlation between the simulated and the measured functional connectivity (maximum Pearson correlation rho = 0: 53), further suggesting that the topology of structural connections plays an important role in shaping functional cortical networks. es_ES
dc.description.sponsorship This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and FEDER funds under grants BFU2015-64380-C2-1-R (S.C) and BFU2015-64380-C2-2-R (D.M.) and EU Horizon 2020 Program 668863-SyBil-AA grant (S.C.). S.C. acknowledges financial support from the Spanish State Research Agency, through the "Severo Ochoa" Programme for Centres of Excellence in R&D (ref. SEV-2013-0317). A. D.-P., was supported by grant FPU13/01475 from the Spanish Ministerio de Educacion, Cultura y Deporte (MECD). O.S. acknowledges support by the J.S. McDonnell Foundation (#220020387) and the National Institutes of Health (NIH R01 AT009036-01). We are also grateful to Andrea Avena-Koenigsberger and Begona Fernandez for their technical support. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof NeuroImage es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Brain connectivity es_ES
dc.subject Connectome es_ES
dc.subject Resting-state es_ES
dc.subject Network science es_ES
dc.subject Computational modelling es_ES
dc.subject Rat es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Structural and functional, empirical and modeled connectivity in the cerebral cortex of the rat es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.neuroimage.2017.07.046 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/668863/EU/Systems Biology of Alcohol Addiction: Modeling and validating disease state networks in human and animal brains for understanding pathophysiolgy, predicting outcomes and improving therapy/ en_EN
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//BFU2015-64380-C2-2-R/ES/ANALISIS DE TEXTURAS EN IMAGEN CEREBRAL MULTIMODAL POR RESONANCIA MAGNETICA PARA UNA DETECCION TEMPRANA DE ALTERACIONES EN LA RED Y BIOMARCADORES DE ENFERMEDAD/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MECD//FPU13%2F01475/ES/FPU13%2F01475/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NIH/NATIONAL CENTER FOR COMPLEMENTARY & INTEGRATIVE HEALTH/5R01AT009036-03/US/
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.description.bibliographicCitation Díaz-Parra, A.; Osborn, Z.; Canals Gamoneda, S.; Moratal, D.; Sporns, O. (2017). Structural and functional, empirical and modeled connectivity in the cerebral cortex of the rat. NeuroImage. 159:170-184. https://doi.org/10.1016/j.neuroimage.2017.07.046 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.neuroimage.2017.07.046 es_ES
dc.description.upvformatpinicio 170 es_ES
dc.description.upvformatpfin 184 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 159 es_ES
dc.identifier.pmid 28739119 en_EN
dc.identifier.pmcid PMC5724396 en_EN
dc.relation.pasarela S\353074 es_ES
dc.contributor.funder Ministerio de Educación, Cultura y Deporte es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES


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