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Ingredients for Understanding Brain and Behavioral Evolution: Ecology, Phylogeny, and Mechanism

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dc.contributor.author Stephen, H. Montgomery
dc.contributor.author Adrian, Currie
dc.contributor.author Dieter, Lukas
dc.contributor.author Andrew, Buskell
dc.contributor.author Fiona, R. Cross
dc.contributor.author Sarah, Jelbert
dc.contributor.author Shahar, Avin
dc.contributor.author Rafael, Mares
dc.contributor.author Ana, F. Navarrete
dc.contributor.author Shuichi, Shigeno
dc.contributor.author Corina, J. Logan
dc.date.accessioned 2019-05-23T06:34:02Z
dc.date.available 2019-05-23T06:34:02Z
dc.date.issued 2018
dc.identifier.uri http://hdl.handle.net/123456789/953
dc.description.abstract Uncovering the neural correlates and evolutionary drivers of behavioral and cognitive traits has been held back by traditional perspectives on which correlations to look for—in particular,anthropocentric conceptions of cognition and coarse-grained brain measurements. We welcome our colleagues’ comments on our overview of the field and their suggestions for how to move forward. Here, we counter, clarify, and extend some points, focusing on the merits of looking for the “best” predictor of cognitive ability, the sources and meaning of “noise,” and the ways in which we can deduce and test meaningful conclusions from comparative analyses of complex traits. en_US
dc.rights Attribution-NonCommercial-ShareAlike 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/us/ *
dc.subject Brain measures en_US
dc.subject Cognition en_US
dc.subject Behavior en_US
dc.subject Noise en_US
dc.title Ingredients for Understanding Brain and Behavioral Evolution: Ecology, Phylogeny, and Mechanism en_US
dc.type Article en_US


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