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Measuring variation in cognition

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  • Candy Rowe
  • Susan D. Healy

Abstract

Across a range of disciplines, researchers are becoming increasingly interested in studying the variation in cognitive abilities found within populations. Behavioral ecology is no exception: the pursuit to understand the evolution of cognition has lead to a rapidly expanding literature that uses various tasks to measure individuals’ cognitive abilities. While this is an exciting time, we are concerned that without being clearer as to the cognitive abilities under test it will be difficult to design appropriate experiments and the interpretation of the data may be unsound. The aim of this review is 3-fold: 1) to highlight problems with designing tasks for measuring individual variation in cognitive abilities and interpreting their outcomes; 2) to increase awareness that noncognitive factors can cause variation in performance among individuals; and 3) to question the theoretical basis for thinking that performance in any cognitive task should necessarily correlate with a measure of fitness. Our take-home message is that variability in performance in cognitive tasks does not necessarily demonstrate individual variation in cognitive ability, and that we need to both design more stringent cognitive tests and be more cautious in their interpretation.

Suggested Citation

  • Candy Rowe & Susan D. Healy, 2014. "Measuring variation in cognition," Behavioral Ecology, International Society for Behavioral Ecology, vol. 25(6), pages 1287-1292.
  • Handle: RePEc:oup:beheco:v:25:y:2014:i:6:p:1287-1292.
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    File URL: http://hdl.handle.net/10.1093/beheco/aru090
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    Citations

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    Cited by:

    1. Li Li & Cwyn Solvi & Feng Zhang & Zhaoyang Qi & Lars Chittka & Wei Zhao, 2021. "Gut microbiome drives individual memory variation in bumblebees," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    2. Candy Rowe & Susan D. Healy, 2014. "Measuring cognition will be difficult but worth it: a response to comments on Rowe and Healy," Behavioral Ecology, International Society for Behavioral Ecology, vol. 25(6), pages 1298-1298.
    3. van Horik, Jayden O. & Langley, Ellis J.G. & Whiteside, Mark A. & Madden, Joah R., 2019. "A single factor explanation for associative learning performance on colour discrimination problems in common pheasants (Phasianus colchicus)," Intelligence, Elsevier, vol. 74(C), pages 53-61.
    4. MacKinlay, Regan D. & Shaw, Rachael C., 2019. "Male New Zealand robin (Petroica longipes) song repertoire size does not correlate with cognitive performance in the wild," Intelligence, Elsevier, vol. 74(C), pages 25-33.
    5. R. Croston & C.L. Branch & D.Y. Kozlovsky & R. Dukas & V.V. Pravosudov, 2015. "Heritability and the evolution of cognitive traits," Behavioral Ecology, International Society for Behavioral Ecology, vol. 26(6), pages 1447-1459.
    6. John L. Quinn & Ella F. Cole & Julie Morand-Ferron, 2014. "Studying microevolutionary processes in cognitive traits: a comment on Rowe and Healy," Behavioral Ecology, International Society for Behavioral Ecology, vol. 25(6), pages 1297-1298.
    7. Niclas Kolm, 2014. "Measuring variation in cognition can be done, but it requires hard empirical work: a comment on Rowe and Healy," Behavioral Ecology, International Society for Behavioral Ecology, vol. 25(6), pages 1296-1297.
    8. Alex Thornton, 2014. "How and why are some species so smart? A comment on Rowe and Healy," Behavioral Ecology, International Society for Behavioral Ecology, vol. 25(6), pages 1294-1295.

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