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Are brain weights estimated from scaling relationships suitable for comparative studies of animal cognition?
Author(s) -
Stephen H. Montgomery
Publication year - 2019
Publication title -
animal cognition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.29
H-Index - 77
eISSN - 1435-9456
pISSN - 1435-9448
DOI - 10.1007/s10071-019-01300-2
Subject(s) - variation (astronomy) , cognition , ethology , brain size , cognitive psychology , neuroimaging , animal cognition , psychology , comparative cognition , cognitive science , psychological research , comparative psychology , allometry , behavioural sciences , cognitive neuroscience , multidimensional scaling , computer science , artificial intelligence , neuroscience , machine learning , social psychology , biology , ecology , radiology , medicine , physics , astrophysics , magnetic resonance imaging , psychotherapist
What is the cognitive significance of variation in brain size? This question is simply put, but hard to answer, and remains one of the most enduring questions in comparative ethology. Understanding the causative links between variation in brain size and structure, and cognition requires reliable data on both neural and behavioral traits. A recent study by Horschler et al. (Anim Cogn 22(2):187-198, 2019) demonstrated the potential of citizen science and domestic dogs to provide unprecedented behavioral datasets that can be used to tackle this question. However, data on brain weight is harder to source. To test the link between performance in various cognitive tasks and variation in brain size, the authors instead relied on data for body weight, which was transformed into 'estimated brain weight' using the allometric scaling relationship between brain and body size, an approach that can be found in other papers which lack sufficient neuroanatomical data. Here, I describe some probable limitations of this approach and suggest that such transformations provide no benefit to the analyses and should be avoided.

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