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Supplementary material from "Intra-individual variation in performance on novel variants of similar tasks influences single factor explanations of general cognitive processes"

Version 2 2018-07-04, 14:04
Version 1 2018-06-20, 18:45
Posted on 2018-07-04 - 14:04
Intra-individual variation in performance within and across cognitive domains may confound interpretations of both domain-general and domain-specific abilities. Such variation is rarely considered in animal test batteries. We investigate individual consistency in performance by presenting pheasant chicks (n = 31), raised under standardized conditions, with nine different cognitive tasks. Among these tasks were two replicated novel variants of colour learning and colour reversal problems, tests of positional learning and memory, as well as two different tasks that captured multiple putative measures of inhibitory control and motor-related performance. These task variants were also used to compare subjects' performance on alternative test batteries comprised of different task combinations. Subjects’ performance improved with experience, yet we found relatively little consistency in their performance, both within similar tasks using different paradigms and across different tasks. Parallel analysis revealed non-significant factors when all nine tasks were included in a principal axis factor analysis. However, when different combinations of six of the nine tasks were included in principal axis factoring, 14 of 84 combinations revealed significant main factors, explaining between 28 and 35% of the variance in task performance. While comparable findings have been suggested to reflect domain-general intelligence in other species, we found no evidence to suggest that a single factor encompassed a diverse range of cognitive abilities in pheasants. Instead, we reveal how single factor explanations of cognitive processes can be influenced by test battery composition and intra-individual variation in performance across tasks. Our findings highlight the importance of conducting multiple tests within specific domains to ensure robust cognitive measures are obtained.

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