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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