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Luengo Sánchez, Sergio and Fernaud Espinosa, Isabel and Bielza Lozoya, María Concepción and Benavides Piccione, Ruth and Larrañaga Múgica, Pedro María and Felipe Oroquieta, Javier de (2018). 3D morphology-based clustering and simulation of human pyramidal cell dendritic spines. "PLOS Computational Biology", v. 14 (n. 6); pp. 1-22. ISSN 1553-7358. https://doi.org/10.1371/journal.pcbi.1006221.
Title: | 3D morphology-based clustering and simulation of human pyramidal cell dendritic spines |
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Author/s: |
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Item Type: | Article |
Título de Revista/Publicación: | PLOS Computational Biology |
Date: | 2018 |
ISSN: | 1553-7358 |
Volume: | 14 |
Subjects: | |
Faculty: | E.T.S. de Ingenieros Informáticos (UPM) |
Department: | Inteligencia Artificial |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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The dendritic spines of pyramidal neurons are the targets of most excitatory synapses in the cerebral cortex. They have a wide variety of morphologies, and their morphology appears to be critical from the functional point of view. To further characterize dendritic spine geometry, we used in this paper over 7,000 individually 3D reconstructed dendritic spines from human cortical pyramidal neurons to group dendritic spines using model-based clustering. This approach uncovered six separate groups of human dendritic spines. To better understand the differences between these groups, the discriminative characteristics of each group were identified as a set of rules. Model-based clustering was also useful for simulating accurate 3D virtual representations of spines that matched the morphological definitions of each cluster. This mathematical approach could provide a useful tool for theoretical predictions on the functional features of human pyramidal neurons based on the morphology of dendritic spines.
Type | Code | Acronym | Leader | Title |
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Government of Spain | C080020-09 | Unspecified | Unspecified | Cajal Blue Brain |
Government of Spain | TIN2016-79684-P | Unspecified | Universidad Politécnica de Madrid | Avances en clasificación multidimensional y detección de anomalías con redes bayesianas |
Madrid Regional Government | S2013/ICE-2845 | CASI – CAM | Unspecified | Conceptos y aplicaciones de los sistemas inteligentes |
Horizon 2020 | 720270 | HBP SGA1 | Unspecified | Human Brain Project Specific Grant Agreement 1 |
Item ID: | 54566 |
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DC Identifier: | https://oa.upm.es/54566/ |
OAI Identifier: | oai:oa.upm.es:54566 |
DOI: | 10.1371/journal.pcbi.1006221 |
Official URL: | https://journals.plos.org/ploscompbiol/article?rev=2&id=10.1371/journal.pcbi.1006221 |
Deposited by: | Memoria Investigacion |
Deposited on: | 14 May 2019 10:08 |
Last Modified: | 30 Nov 2022 09:00 |