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Inferring Evolutionary Process From Neuroanatomical Data.
Lewitus, Eric.
Affiliation
  • Lewitus E; Institut de Biologie de l'ENS, Paris Sciences et Lettres Université, Paris, France.
Front Neuroanat ; 12: 54, 2018.
Article in En | MEDLINE | ID: mdl-30100868
Brain evolution has interested neuroanatomists for over a century. These interests often fall on how free the brain is to evolve independently of the body, how free brain regions are to evolve independently of each other, and how different environmental and ecological factors affect the brain over evolutionary time. But despite major advances in phylogenetic methods, comparative neuroanatomists have tended to limit their macroevolutionary toolbox to regression-based analyses and ignored the scope of evolutionary process-based models at their disposal. This Review summarizes the history of comparative neuroanatomy and highlights the pitfalls of the methodologies traditionally used. It provides an overview of evolutionary process-based modeling approaches for investigating univariate and multivariate data, as well as more sophisticated methods that incorporate hypotheses about biotic and abiotic pressures that may drive brain evolution. The benefits of evolutionary process-based models, and shortcomings of regression-based ones, are illustrated with widely used neuroanatomical data. Ultimately, the intent of this Review is to be a guide for subsuming macroevolutionary methods not typically used in comparative neuroanatomy, in order to improve our understanding of how the brain evolves.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Front Neuroanat Year: 2018 Document type: Article Affiliation country: Francia Country of publication: Suiza

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Front Neuroanat Year: 2018 Document type: Article Affiliation country: Francia Country of publication: Suiza