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Cauchoix M, Chow PKY, van Horik JO, Atance CM, Barbeau EJ, Barragan-Jason G, Bize P, Boussard A, Buechel SD, Cabirol A, Cauchard L, Claidière N, Dalesman S, Devaud JM, Didic M, Doligez B, Fagot J, Fichtel C, Henke-von der Malsburg J, Hermer E, Huber L, Huebner F, Kappeler PM, Klein S, Langbein J, Langley EJG, Lea SEG, Lihoreau M, Lovlie H, Matzel LD, Nakagawa S, Nawroth C, Oesterwind S, Sauce B, Smith EA, Sorato E, Tebbich S, Wallis LJ, Whiteside MA, Wilkinson A, Chaine AS, Morand-Ferron J. The repeatability of cognitive performance: a meta-analysis. Philos Trans R Soc Lond B Biol Sci 2018; 373:20170281. [PMID: 30104426 PMCID: PMC6107569 DOI: 10.1098/rstb.2017.0281] [Citation(s) in RCA: 81] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/28/2018] [Indexed: 12/20/2022] Open
Abstract
Behavioural and cognitive processes play important roles in mediating an individual's interactions with its environment. Yet, while there is a vast literature on repeatable individual differences in behaviour, relatively little is known about the repeatability of cognitive performance. To further our understanding of the evolution of cognition, we gathered 44 studies on individual performance of 25 species across six animal classes and used meta-analysis to assess whether cognitive performance is repeatable. We compared repeatability (R) in performance (1) on the same task presented at different times (temporal repeatability), and (2) on different tasks that measured the same putative cognitive ability (contextual repeatability). We also addressed whether R estimates were influenced by seven extrinsic factors (moderators): type of cognitive performance measurement, type of cognitive task, delay between tests, origin of the subjects, experimental context, taxonomic class and publication status. We found support for both temporal and contextual repeatability of cognitive performance, with mean R estimates ranging between 0.15 and 0.28. Repeatability estimates were mostly influenced by the type of cognitive performance measures and publication status. Our findings highlight the widespread occurrence of consistent inter-individual variation in cognition across a range of taxa which, like behaviour, may be associated with fitness outcomes.This article is part of the theme issue 'Causes and consequences of individual differences in cognitive abilities'.
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Affiliation(s)
- M Cauchoix
- Station d'Ecologie Théorique et Expérimentale du CNRS UMR5321, Evolutionary Ecology Group, 2 route du CNRS, 09200 Moulis, France
- Institute for Advanced Study in Toulouse, 21 allée de Brienne, 31015 Toulouse, France
| | - P K Y Chow
- Centre for Research in Animal Behaviour, Psychology, University of Exeter, Exeter, UK
- Graduate School of Environmental Science, Division of Biospohere Science, Hokkaido University, Sapporo, Hokkaido, Japan
| | - J O van Horik
- Centre for Research in Animal Behaviour, Psychology, University of Exeter, Exeter, UK
| | - C M Atance
- School of Psychology, University of Ottawa, Ottawa, Canada
| | - E J Barbeau
- Centre de recherche Cerveau et Cognition, UPS-CNRS, UMR5549, Toulouse, France
| | - G Barragan-Jason
- Institute for Advanced Study in Toulouse, 21 allée de Brienne, 31015 Toulouse, France
| | - P Bize
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, UK
| | - A Boussard
- Department of Zoology/Ethology, Stockholm University, Svante Arrheniusväg 18B, 10691 Stockholm, Sweden
| | - S D Buechel
- Department of Zoology/Ethology, Stockholm University, Svante Arrheniusväg 18B, 10691 Stockholm, Sweden
| | - A Cabirol
- Research Center on Animal Cognition (CRCA), Center for Integrative Biology (CBI), CNRS, University Paul Sabatier, Toulouse, France
| | - L Cauchard
- Département de Sciences Biologiques, Université de Montréal, Montreal, Quebec, Canada
| | - N Claidière
- LPC, Aix Marseille University, CNRS, Marseille, France
| | - S Dalesman
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, UK
| | - J M Devaud
- Research Center on Animal Cognition (CRCA), Center for Integrative Biology (CBI), CNRS, University Paul Sabatier, Toulouse, France
| | - M Didic
- AP-HM Timone & Institut de Neurosciences des Systèmes, Marseille, France
| | - B Doligez
- Department of Biometry and Evolutionary Biology, CNRS UMR 5558, Université Lyon 1, Université de Lyon, Villeurbanne, France
| | - J Fagot
- LPC, Aix Marseille University, CNRS, Marseille, France
| | - C Fichtel
- Behavioural Ecology and Sociobiology Unit, German Primate Centre, Leibniz Institute for Primatology, Kellnerweg 4, 37077 Göttingen, Germany
- Department of Sociobiology/Anthropology, Johann-Friedrich-Blumenbach Institute for Zoology and Anthropology, University of Göttingen, Kellnerweg 6, 37077 Göttingen, Germany
- Leibniz Science Campus 'Primate Cognition', Göttingen, Germany
| | - J Henke-von der Malsburg
- Behavioural Ecology and Sociobiology Unit, German Primate Centre, Leibniz Institute for Primatology, Kellnerweg 4, 37077 Göttingen, Germany
- Department of Sociobiology/Anthropology, Johann-Friedrich-Blumenbach Institute for Zoology and Anthropology, University of Göttingen, Kellnerweg 6, 37077 Göttingen, Germany
- Leibniz Science Campus 'Primate Cognition', Göttingen, Germany
| | - E Hermer
- Department of Sociobiology/Anthropology, Johann-Friedrich-Blumenbach Institute for Zoology and Anthropology, University of Göttingen, Kellnerweg 6, 37077 Göttingen, Germany
| | - L Huber
- Leibniz Science Campus 'Primate Cognition', Göttingen, Germany
| | - F Huebner
- Behavioural Ecology and Sociobiology Unit, German Primate Centre, Leibniz Institute for Primatology, Kellnerweg 4, 37077 Göttingen, Germany
- Department of Sociobiology/Anthropology, Johann-Friedrich-Blumenbach Institute for Zoology and Anthropology, University of Göttingen, Kellnerweg 6, 37077 Göttingen, Germany
- Leibniz Science Campus 'Primate Cognition', Göttingen, Germany
| | - P M Kappeler
- Behavioural Ecology and Sociobiology Unit, German Primate Centre, Leibniz Institute for Primatology, Kellnerweg 4, 37077 Göttingen, Germany
- Department of Sociobiology/Anthropology, Johann-Friedrich-Blumenbach Institute for Zoology and Anthropology, University of Göttingen, Kellnerweg 6, 37077 Göttingen, Germany
- Leibniz Science Campus 'Primate Cognition', Göttingen, Germany
| | - S Klein
- Research Center on Animal Cognition (CRCA), Center for Integrative Biology (CBI), CNRS, University Paul Sabatier, Toulouse, France
| | - J Langbein
- Institute of Behavioural Physiology, Leibniz Institute for Farm Animal Biology, Dummerstorf, Germany
| | - E J G Langley
- Centre for Research in Animal Behaviour, Psychology, University of Exeter, Exeter, UK
| | - S E G Lea
- Centre for Research in Animal Behaviour, Psychology, University of Exeter, Exeter, UK
| | - M Lihoreau
- Research Center on Animal Cognition (CRCA), Center for Integrative Biology (CBI), CNRS, University Paul Sabatier, Toulouse, France
| | - H Lovlie
- IFM Biology, Linköping University, 58183 Linköping, Sweden
| | - L D Matzel
- Department of Psychology, Rutgers University, Piscataway, NJ, USA
| | - S Nakagawa
- Evolution & Ecology Research Centre and School of Biological, Earth & Environmental Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - C Nawroth
- Institute of Behavioural Physiology, Leibniz Institute for Farm Animal Biology, Dummerstorf, Germany
| | - S Oesterwind
- Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany
| | - B Sauce
- Department of Psychology, Rutgers University, Piscataway, NJ, USA
| | - E A Smith
- School of Life Sciences, University of Lincoln, Lincoln, UK
| | - E Sorato
- IFM Biology, Linköping University, 58183 Linköping, Sweden
| | - S Tebbich
- Department of Behavioural Biology, University of Vienna, Vienna, Austria
| | - L J Wallis
- Clever Dog Lab, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna, University of Vienna, Vienna, Austria
- Department of Ethology, Eötvös Loránd University, Budapest, Hungary
| | - M A Whiteside
- Centre for Research in Animal Behaviour, Psychology, University of Exeter, Exeter, UK
| | - A Wilkinson
- School of Life Sciences, University of Lincoln, Lincoln, UK
| | - A S Chaine
- Station d'Ecologie Théorique et Expérimentale du CNRS UMR5321, Evolutionary Ecology Group, 2 route du CNRS, 09200 Moulis, France
- Institute for Advanced Study in Toulouse, 21 allée de Brienne, 31015 Toulouse, France
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Saint-Aubert L, Nemmi F, Péran P, Barbeau EJ, Payoux P, Chollet F, Pariente J. Comparison between PET template-based method and MRI-based method for cortical quantification of florbetapir (AV-45) uptake in vivo. Eur J Nucl Med Mol Imaging 2013; 41:836-43. [PMID: 24435769 PMCID: PMC3978219 DOI: 10.1007/s00259-013-2656-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2013] [Accepted: 11/28/2013] [Indexed: 01/18/2023]
Abstract
PURPOSE Florbetapir (AV-45) has been shown to be a reliable tool for assessing in vivo amyloid load in patients with Alzheimer's disease from the early stages. However, nonspecific white matter binding has been reported in healthy subjects as well as in patients with Alzheimer's disease. To avoid this issue, cortical quantification might increase the reliability of AV-45 PET analyses. In this study, we compared two quantification methods for AV-45 binding, a classical method relying on PET template registration (route 1), and a MRI-based method (route 2) for cortical quantification. METHODS We recruited 22 patients at the prodromal stage of Alzheimer's disease and 17 matched controls. AV-45 binding was assessed using both methods, and target-to-cerebellum mean global standard uptake values (SUVr) were obtained for each of them, together with SUVr in specific regions of interest. Quantification using the two routes was compared between the clinical groups (intragroup comparison), and between groups for each route (intergroup comparison). Discriminant analysis was performed. RESULTS In the intragroup comparison, differences in uptake values were observed between route 1 and route 2 in both groups. In the intergroup comparison, AV-45 uptake was higher in patients than controls in all regions of interest using both methods, but the effect size of this difference was larger using route 2. In the discriminant analysis, route 2 showed a higher specificity (94.1 % versus 70.6 %), despite a lower sensitivity (77.3 % versus 86.4 %), and D-prime values were higher for route 2. CONCLUSION These findings suggest that, although both quantification methods enabled patients at early stages of Alzheimer's disease to be well discriminated from controls, PET template-based quantification seems adequate for clinical use, while the MRI-based cortical quantification method led to greater intergroup differences and may be more suitable for use in current clinical research.
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Affiliation(s)
- L Saint-Aubert
- Inserm, imagerie cérébrale et handicaps neurologiques UMR 825, Centre Hospitalier Universitaire de Toulouse, Pavillon Baudot CHU Purpan lace Dr Baylac, 31059, Toulouse, France,
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