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Comparing basal dendrite branches in human and mouse hippocampal CA1 pyramidal neurons with Bayesian networks.
Mihaljevic, Bojan; Larrañaga, Pedro; Benavides-Piccione, Ruth; DeFelipe, Javier; Bielza, Concha.
Afiliação
  • Mihaljevic B; Computational Intelligence Group, Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Boadilla del Monte, 28660, Madrid, Spain. bmihaljevic@fi.upm.es.
  • Larrañaga P; Computational Intelligence Group, Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Boadilla del Monte, 28660, Madrid, Spain.
  • Benavides-Piccione R; Laboratorio Cajal de Circuitos Corticales, Universidad Politécnica de Madrid and Instituto Cajal (CSIC), Pozuelo de Alarcón, 28223, Madrid, Spain.
  • DeFelipe J; Laboratorio Cajal de Circuitos Corticales, Universidad Politécnica de Madrid and Instituto Cajal (CSIC), Pozuelo de Alarcón, 28223, Madrid, Spain.
  • Bielza C; Computational Intelligence Group, Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Boadilla del Monte, 28660, Madrid, Spain.
Sci Rep ; 10(1): 18592, 2020 10 29.
Article em En | MEDLINE | ID: mdl-33122691
Pyramidal neurons are the most common cell type in the cerebral cortex. Understanding how they differ between species is a key challenge in neuroscience. A recent study provided a unique set of human and mouse pyramidal neurons of the CA1 region of the hippocampus, and used it to compare the morphology of apical and basal dendritic branches of the two species. The study found inter-species differences in the magnitude of the morphometrics and similarities regarding their variation with respect to morphological determinants such as branch type and branch order. We use the same data set to perform additional comparisons of basal dendrites. In order to isolate the heterogeneity due to intrinsic differences between species from the heterogeneity due to differences in morphological determinants, we fit multivariate models over the morphometrics and the determinants. In particular, we use conditional linear Gaussian Bayesian networks, which provide a concise graphical representation of the independencies and correlations among the variables. We also extend the previous study by considering additional morphometrics and by formally testing whether a morphometric increases or decreases with the distance from the soma. This study introduces a multivariate methodology for inter-species comparison of morphology.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Células Piramidais / Dendritos / Hipocampo Tipo de estudo: Prognostic_studies Limite: Animals / Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Células Piramidais / Dendritos / Hipocampo Tipo de estudo: Prognostic_studies Limite: Animals / Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article