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Crawford DW, Patel KR, Swiecka A, Bond J, Tiwari A, Plaisted NM, Rednam N, McKeen KM, Patel HM, Sharma P, Roslewicz E, Matzel LD. Unpredictable Mixed-Valence Outcomes Induce a Chronic and Reversible Generalized Anxiety-like Phenotype in Male Mice. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100318. [PMID: 38883866 PMCID: PMC11179253 DOI: 10.1016/j.bpsgos.2024.100318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 03/21/2024] [Accepted: 03/25/2024] [Indexed: 06/18/2024] Open
Abstract
Background Clinical anxiety is a generalized state characterized by feelings of apprehensive expectation and is distinct from momentary responses such as fear or stress. In contrast, most laboratory tests of anxiety focus on acute responses to momentary stressors. Methods Apprehensive expectation was induced by subjecting mice (for 18 days) to manipulations in which a running response (experiment 1) or a conditioned stimulus (experiment 2) were unpredictably paired with reward (food) or punishment (footshock). Before this treatment, the mice were tested in an open field and light/dark box to assess momentary responses that are asserted to reflect state anxiety. After treatment, the mice were assessed for state anxiety in an elevated plus maze, social interaction test, startle response test, intrusive object burying test, and stress-induced corticosterone elevations. In experiment 3, we treated mice similarly to experiment 1, but after mixed-valence training, some mice received either no additional training, additional mixed-valence training, or were shifted to consistent (predictable) reinforcement with food. Results We consistently observed an increase in anxiety-like behaviors after the experience with mixed-valence unpredictable reinforcement. This generalized anxiety persisted for at least 4 weeks after the mixed-valence training and could be reversed if the mixed-valence training was followed by predictable reinforcement with food. Conclusions Results indicate that experience with unpredictable reward/punishment can induce a chronic state analogous to generalized anxiety that can be mitigated by exposure to stable, predictable conditions. This learned apprehension protocol provides a conceptually valid model for the study of the etiology and treatment of anxiety in laboratory animals.
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Affiliation(s)
- Dylan W Crawford
- Department of Psychology, Program in Behavioral & Systems Neuroscience, Rutgers University, Piscataway, New Jersey
| | - Komal R Patel
- Department of Psychology, Program in Behavioral & Systems Neuroscience, Rutgers University, Piscataway, New Jersey
| | - Ashley Swiecka
- Department of Psychology, Program in Behavioral & Systems Neuroscience, Rutgers University, Piscataway, New Jersey
| | - Julia Bond
- Department of Psychology, Program in Behavioral & Systems Neuroscience, Rutgers University, Piscataway, New Jersey
| | - Alisha Tiwari
- Department of Psychology, Program in Behavioral & Systems Neuroscience, Rutgers University, Piscataway, New Jersey
| | - Nicole M Plaisted
- Department of Psychology, Program in Behavioral & Systems Neuroscience, Rutgers University, Piscataway, New Jersey
| | - Nikita Rednam
- Department of Psychology, Program in Behavioral & Systems Neuroscience, Rutgers University, Piscataway, New Jersey
| | - Kelsey M McKeen
- Department of Psychology, Program in Behavioral & Systems Neuroscience, Rutgers University, Piscataway, New Jersey
| | - Himali M Patel
- Department of Psychology, Program in Behavioral & Systems Neuroscience, Rutgers University, Piscataway, New Jersey
| | - Pranu Sharma
- Department of Psychology, Program in Behavioral & Systems Neuroscience, Rutgers University, Piscataway, New Jersey
| | - Emilia Roslewicz
- Department of Psychology, Program in Behavioral & Systems Neuroscience, Rutgers University, Piscataway, New Jersey
| | - Louis D Matzel
- Department of Psychology, Program in Behavioral & Systems Neuroscience, Rutgers University, Piscataway, New Jersey
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2
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Laitinen RAE, Nikoloski Z. Strategies to identify and dissect trade-offs in plants. Mol Ecol 2024; 33:e16780. [PMID: 36380694 DOI: 10.1111/mec.16780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 10/13/2022] [Accepted: 10/31/2022] [Indexed: 11/17/2022]
Abstract
Trade-offs between traits arise and reflect constraints imposed by the environment and physicochemical laws. Trade-off situations are expected to be highly relevant for sessile plants, which have to respond to changes in the environment to ensure survival. Despite increasing interest in determining the genetic and molecular basis of plant trade-offs, there are still gaps and differences with respect to how trade-offs are defined, how they are measured, and how their genetic architecture is dissected. The first step to fill these gaps is to establish what is meant by trade-offs. In this review we provide a classification of the existing definitions of trade-offs according to: (1) the measures used for their quantification, (2) the dependence of trade-offs on environment, and (3) experimental designed used (i.e. a single individual across different environments or a population of individuals in single or multiple environments). We then compare the approaches for quantification of trade-offs based on phenotypic, between-individual, and genetic correlations, and stress the need for developing further quantification indices particularly for trade-offs between multiple traits. Lastly, we highlight the genetic mechanisms underpinning trade-offs and experimental designs that facilitate their discovery in plants, with focus on usage of natural variability. This review also offers a perspective for future research aimed at identification of plant trade-offs, dissection of their genetic architecture, and development of strategies to overcome trade-offs, with applications in crop breeding.
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Affiliation(s)
- Roosa A E Laitinen
- Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
| | - Zoran Nikoloski
- Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
- Systems Biology and Mathematical Modelling, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany
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3
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Speechley EM, Ashton BJ, Thornton A, Simmons LW, Ridley AR. Heritability of cognitive performance in wild Western Australian magpies. ROYAL SOCIETY OPEN SCIENCE 2024; 11:231399. [PMID: 38481983 PMCID: PMC10933533 DOI: 10.1098/rsos.231399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/21/2023] [Accepted: 02/10/2024] [Indexed: 04/26/2024]
Abstract
Individual differences in cognitive performance can have genetic, social and environmental components. Most research on the heritability of cognitive traits comes from humans or captive non-human animals, while less attention has been given to wild populations. Western Australian magpies (Gymnorhina tibicen dorsalis, hereafter magpies) show phenotypic variation in cognitive performance, which affects reproductive success. Despite high levels of individual repeatability, we do not know whether cognitive performance is heritable in this species. Here, we quantify the broad-sense heritability of associative learning ability in a wild population of Western Australian magpies. Specifically, we explore whether offspring associative learning performance is predicted by maternal associative learning performance or by the social environment (group size) when tested at three time points during the first year of life. We found little evidence that offspring associative learning performance is heritable, with an estimated broad-sense heritability of just -0.046 ± 0.084 (confidence interval: -0.234/0.140). However, complementing previous findings, we find that at 300 days post-fledging, individuals raised in larger groups passed the test in fewer trials compared with individuals from small groups. Our results highlight the pivotal influence of the social environment on cognitive development.
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Affiliation(s)
- Elizabeth M. Speechley
- Centre for Evolutionary Biology, School of Biological Sciences, University of Western Australia, Perth, Western Australia 6009, Australia
| | - Benjamin J. Ashton
- Centre for Evolutionary Biology, School of Biological Sciences, University of Western Australia, Perth, Western Australia 6009, Australia
- School of Natural Sciences, Macquarie University, Sydney, New South Wales 2109, Australia
| | - Alex Thornton
- Centre for Ecology and Conservation, University of Exeter, PenrynTR10 9FE, UK
| | - Leigh W. Simmons
- Centre for Evolutionary Biology, School of Biological Sciences, University of Western Australia, Perth, Western Australia 6009, Australia
| | - Amanda R. Ridley
- Centre for Evolutionary Biology, School of Biological Sciences, University of Western Australia, Perth, Western Australia 6009, Australia
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4
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McCallum E, Shaw RC. Repeatability and heritability of inhibitory control performance in wild toutouwai ( Petroica longipes). ROYAL SOCIETY OPEN SCIENCE 2023; 10:231476. [PMID: 38026029 PMCID: PMC10646466 DOI: 10.1098/rsos.231476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 10/25/2023] [Indexed: 12/01/2023]
Abstract
Despite increasing interest in the evolution of inhibitory control, few studies have examined the validity of widespread testing paradigms, the long-term repeatability and the heritability of this cognitive ability in the wild. We investigated these aspects in the inhibitory control performance of wild toutouwai (North Island robin; Petroica longipes), using detour and reversal learning tasks. We assessed convergent validity by testing whether individual performance correlated across detour and reversal learning tasks. We then further evaluated task validity by examining whether individual performance was confounded by non-cognitive factors. We tested a subset of subjects twice in each task to estimate the repeatability of performance across a 1-year period. Finally, we used a population pedigree to estimate the heritability of task performance. Individual performance was unrelated across detour and reversal learning tasks, indicating that these measured different cognitive abilities. Task performance was not influenced by body condition, boldness or prior experience, and showed moderate between-year repeatability. Yet despite this individual consistency, we found no evidence that task performance was heritable. Our findings suggest that detour and reversal learning tasks measure consistent individual differences in distinct forms of inhibitory control in toutouwai, but this variation may be environmentally determined rather than genetic.
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Affiliation(s)
- Ella McCallum
- School of Biological Sciences, Te Herenga Waka Victoria University of Wellington, Wellington, New Zealand
| | - Rachael C. Shaw
- School of Biological Sciences, Te Herenga Waka Victoria University of Wellington, Wellington, New Zealand
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5
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Riordan R, Rong W, Yu Z, Ross G, Valerio J, Dimas-Muñoz J, Heredia V, Magnusson K, Galvan V, Perez VI. Effect of Nrf2 loss on senescence and cognition of tau-based P301S mice. GeroScience 2023; 45:1451-1469. [PMID: 36976489 PMCID: PMC10400516 DOI: 10.1007/s11357-023-00760-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 02/20/2023] [Indexed: 03/29/2023] Open
Abstract
Cellular senescence may contribute to chronic inflammation involved in the progression of age-related diseases such as Alzheimer's disease (AD), and its removal prevents cognitive impairment in a model of tauopathy. Nrf2, the major transcription factor for damage response pathways and regulators of inflammation, declines with age. Our previous work showed that silencing Nrf2 gives rise to premature senescence in cells and mice. Others have shown that Nrf2 ablation can exacerbate cognitive phenotypes of some AD models. In this study, we aimed to understand the relationship between Nrf2 elimination, senescence, and cognitive impairment in AD, by generating a mouse model expressing a mutant human tau transgene in an Nrf2 knockout (Nrf2KO) background. We assessed senescent cell burden and cognitive decline of P301S mice in the presence and absence of Nrf2. Lastly, we administered 4.5-month-long treatments with two senotherapeutic drugs to analyze their potential to prevent senescent cell burden and cognitive decline: the senolytic drugs dasatinib and quercetin (DQ) and the senomorphic drug rapamycin. Nrf2 loss accelerated the onset of hind-limb paralysis in P301S mice. At 8.5 months of age, P301S mice did not exhibit memory deficits, while P301S mice without Nrf2 were significantly impaired. However, markers of senescence were not elevated by Nrf2 ablation in any of tissues that we examined. Neither drug treatment improved cognitive performance, nor did it reduce expression of senescence markers in brains of P301S mice. Contrarily, rapamycin treatment at the doses used delayed spatial learning and led to a modest decrease in spatial memory. Taken together, our data suggests that the emergence of senescence may be causally associated with onset of cognitive decline in the P301S model, indicate that Nrf2 protects brain function in a model of AD through mechanisms that may include, but do not require the inhibition of senescence, and suggest possible limitations for DQ and rapamycin as therapies for AD.
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Affiliation(s)
- Ruben Riordan
- Department of Biochemistry and Biophysics, Linus Pauling Institute, Oregon State University, 351 Linus Pauling Science Center, Corvallis, OR, 97331, USA
- Linus Pauling Institute, Oregon State University, Corvallis, OR, USA
| | - Wang Rong
- Department of Biochemistry and Biophysics, Linus Pauling Institute, Oregon State University, 351 Linus Pauling Science Center, Corvallis, OR, 97331, USA
- Linus Pauling Institute, Oregon State University, Corvallis, OR, USA
| | - Zhen Yu
- Department of Biochemistry and Biophysics, Linus Pauling Institute, Oregon State University, 351 Linus Pauling Science Center, Corvallis, OR, 97331, USA
- Linus Pauling Institute, Oregon State University, Corvallis, OR, USA
| | - Grace Ross
- Department of Biochemistry and Biophysics, Linus Pauling Institute, Oregon State University, 351 Linus Pauling Science Center, Corvallis, OR, 97331, USA
- Linus Pauling Institute, Oregon State University, Corvallis, OR, USA
| | - Juno Valerio
- Department of Biochemistry and Biophysics, Linus Pauling Institute, Oregon State University, 351 Linus Pauling Science Center, Corvallis, OR, 97331, USA
- Linus Pauling Institute, Oregon State University, Corvallis, OR, USA
| | - Jovita Dimas-Muñoz
- Department of Biochemistry and Biophysics, Linus Pauling Institute, Oregon State University, 351 Linus Pauling Science Center, Corvallis, OR, 97331, USA
- Linus Pauling Institute, Oregon State University, Corvallis, OR, USA
| | - Valeria Heredia
- Department of Biochemistry and Biophysics, Linus Pauling Institute, Oregon State University, 351 Linus Pauling Science Center, Corvallis, OR, 97331, USA
- Linus Pauling Institute, Oregon State University, Corvallis, OR, USA
| | - Kathy Magnusson
- Linus Pauling Institute, Oregon State University, Corvallis, OR, USA
- Department of Biomedical Sciences, Carlson College of Veterinary Medicine, Oregon State University, Corvallis, OR, USA
| | - Veronica Galvan
- Department of Biochemistry and Molecular Biology, Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 740 Stanton L. Young Bvd BMSB 821, Oklahoma City, OK, 73104, USA.
- Oklahoma City VA Medical Center, US Department of Veterans Affairs, Oklahoma City, OK, USA.
| | - Viviana I Perez
- Department of Biochemistry and Biophysics, Linus Pauling Institute, Oregon State University, 351 Linus Pauling Science Center, Corvallis, OR, 97331, USA.
- Linus Pauling Institute, Oregon State University, Corvallis, OR, USA.
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Signs of a Flynn effect in rodents? Secular differentiation of the manifold of general cognitive ability in laboratory mice (Mus musculus) and Norwegian rats (Rattus norvegicus) over a century—Results from two cross-temporal meta-analyses. INTELLIGENCE 2022. [DOI: 10.1016/j.intell.2022.101700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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7
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Changes in heritability: Unpredictable and of limited use. Behav Brain Sci 2022; 45:e159. [PMID: 36098439 DOI: 10.1017/s0140525x2100159x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
We argue that heritability estimates cannot be used to make informed judgments about the populations from which they are drawn. Furthermore, predicting changes in heritability from population changes is likely impossible, and of limited value. We add that the attempt to separate human environments into cultural and non-cultural components does not advance our understanding of the environmental multiplier effect.
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8
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Integrating cultural evolution and behavioral genetics. Behav Brain Sci 2022; 45:e182. [PMID: 36098400 DOI: 10.1017/s0140525x22000036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
The 29 commentaries amplified our key arguments; offered extensions, implications, and applications of the framework; and pushed back and clarified. To help forge the path forward for cultural evolutionary behavioral genetics, we (1) focus on conceptual disagreements and misconceptions about the concepts of heritability and culture; (2) further discuss points raised about the intertwined relationship between culture and genes; and (3) address extensions to the proposed framework, particularly as it relates to cultural clusters, development, and power. These commentaries, and the deep engagement they represent, reinforce the importance of integrating cultural evolution and behavioral genetics.
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9
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Lambert CT, Sahu PK, Sturdy CB, Guillette LM. Among-individual differences in auditory and physical cognitive abilities in zebra finches. Learn Behav 2022; 50:389-404. [PMID: 35583601 PMCID: PMC9116276 DOI: 10.3758/s13420-022-00520-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/19/2022] [Indexed: 12/13/2022]
Abstract
Among-individual variation in performance on cognitive tasks is ubiquitous across species that have been examined, and understanding the evolution of cognitive abilities requires investigating among-individual variation because natural selection acts on individual differences. However, relatively little is known about the extent to which individual differences in cognition are determined by domain-specific compared with domain-general cognitive abilities. We examined individual differences in learning speed of zebra finches across seven different tasks to determine the extent of domain-specific versus domain-general learning abilities, as well as the relationship between learning speed and learning generalization. Thirty-two zebra finches completed a foraging board experiment that included visual and structural discriminations, and then these same birds went through an acoustic operant discrimination experiment that required discriminating between different natural categories of acoustic stimuli. We found evidence of domain-general learning abilities as birds' relative performance on the seven learning tasks was weakly repeatable and a principal components analysis found a first principal component that explained 36% of the variance in performance across tasks with all tasks loading unidirectionally on this component. However, the few significant correlations between tasks and high repeatability within each experiment suggest the potential for domain-specific abilities. Learning speed did not influence an individual's ability to generalize learning. These results suggest that zebra finch performance across visual, structural, and auditory learning relies upon some common mechanism; some might call this evidence of "general intelligence"(g), but it is also possible that this finding is due to other noncognitive mechanisms such as motivation.
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Affiliation(s)
- Connor T Lambert
- Department of Psychology, University of Alberta, Edmonton, AB, T6G 2R3, Canada
| | - Prateek K Sahu
- Department of Psychology, University of Alberta, Edmonton, AB, T6G 2R3, Canada
| | - Christopher B Sturdy
- Department of Psychology, University of Alberta, Edmonton, AB, T6G 2R3, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, T6G 2R3, Canada
| | - Lauren M Guillette
- Department of Psychology, University of Alberta, Edmonton, AB, T6G 2R3, Canada.
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10
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Lambert CT, Guillette LM. The impact of environmental and social factors on learning abilities: a meta-analysis. Biol Rev Camb Philos Soc 2021; 96:2871-2889. [PMID: 34342125 DOI: 10.1111/brv.12783] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 07/12/2021] [Accepted: 07/16/2021] [Indexed: 12/20/2022]
Abstract
Since the 1950s, researchers have examined how differences in the social and asocial environment affect learning in rats, mice, and, more recently, a variety of other species. Despite this large body of research, little has been done to synthesize these findings and to examine if social and asocial environmental factors have consistent effects on cognitive abilities, and if so, what aspects of these factors have greater or lesser impact. Here, we conducted a systematic review and meta-analysis examining how different external environmental features, including the social environment, impact learning (both speed of acquisition and performance). Using 531 mean-differences from 176 published articles across 27 species (with studies on rats and mice being most prominent) we conducted phylogenetically corrected mixed-effects models that reveal: (i) an average absolute effect size |d| = 0.55 and directional effect size d = 0.34; (ii) interventions manipulating the asocial environment result in larger effects than social interventions alone; and (iii) the length of the intervention is a significant predictor of effect size, with longer interventions resulting in larger effects. Additionally, much of the variation in effect size remained unexplained, possibly suggesting that species differ widely in how they are affected by environmental interventions due to varying ecological and evolutionary histories. Overall our results suggest that social and asocial environmental factors do significantly affect learning, but these effects are highly variable and perhaps not always as predicted. Most notably, the type (social or asocial) and length of interventions are important in determining the strength of the effect.
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Affiliation(s)
- Connor T Lambert
- Department of Psychology, University of Alberta, P217 Biological Sciences Building, Edmonton, AB, T6G 2R3, Canada
| | - Lauren M Guillette
- Department of Psychology, University of Alberta, P217 Biological Sciences Building, Edmonton, AB, T6G 2R3, Canada
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11
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Abstract
Behavioral genetics and cultural evolution have both revolutionized our understanding of human behavior-largely independent of each other. Here we reconcile these two fields under a dual inheritance framework, offering a more nuanced understanding of the interaction between genes and culture. Going beyond typical analyses of gene-environment interactions, we describe the cultural dynamics that shape these interactions by shaping the environment and population structure. A cultural evolutionary approach can explain, for example, how factors such as rates of innovation and diffusion, density of cultural sub-groups, and tolerance for behavioral diversity impact heritability estimates, thus yielding predictions for different social contexts. Moreover, when cumulative culture functionally overlaps with genes, genetic effects become masked, unmasked, or even reversed, and the causal effects of an identified gene become confounded with features of the cultural environment. The manner of confounding is specific to a particular society at a particular time, but a WEIRD (Western, educated, industrialized, rich, democratic) sampling problem obscures this boundedness. Cultural evolutionary dynamics are typically missing from models of gene-to-phenotype causality, hindering generalizability of genetic effects across societies and across time. We lay out a reconciled framework and use it to predict the ways in which heritability should differ between societies, between socioeconomic levels and other groupings within some societies but not others, and over the life course. An integrated cultural evolutionary behavioral genetic approach cuts through the nature-nurture debate and helps resolve controversies in topics such as IQ.
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12
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Poirier MA, Kozlovsky DY, Morand-Ferron J, Careau V. How general is cognitive ability in non-human animals? A meta-analytical and multi-level reanalysis approach. Proc Biol Sci 2020; 287:20201853. [PMID: 33290683 PMCID: PMC7739923 DOI: 10.1098/rspb.2020.1853] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 11/17/2020] [Indexed: 12/15/2022] Open
Abstract
General intelligence has been a topic of high interest for over a century. Traditionally, research on general intelligence was based on principal component analyses and other dimensionality reduction approaches. The advent of high-speed computing has provided alternative statistical tools that have been used to test predictions of human general intelligence. In comparison, research on general intelligence in non-human animals is in its infancy and still relies mostly on factor-analytical procedures. Here, we argue that dimensionality reduction, when incorrectly applied, can lead to spurious results and limit our understanding of ecological and evolutionary causes of variation in animal cognition. Using a meta-analytical approach, we show, based on 555 bivariate correlations, that the average correlation among cognitive abilities is low (r = 0.185; 95% CI: 0.087-0.287), suggesting relatively weak support for general intelligence in animals. We then use a case study with relatedness (genetic) data to demonstrate how analysing traits using mixed models, without dimensionality reduction, provides new insights into the structure of phenotypic variance among cognitive traits, and uncovers genetic associations that would be hidden otherwise. We hope this article will stimulate the use of alternative tools in the study of cognition and its evolution in animals.
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Affiliation(s)
| | - Dovid Y. Kozlovsky
- Department of Biology, University of Ottawa, Ottawa, Ontario, Canada
- Department of Biology, Villanova University, Villanova, Pennsylvania, USA
| | | | - Vincent Careau
- Department of Biology, University of Ottawa, Ottawa, Ontario, Canada
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13
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Matzel LD, Patel HM, Piela MC, Manzano MD, Tu A, Crawford DW. General Cognitive Ability Predicts Survival-Readiness in Genetically Heterogeneous Laboratory Mice. Front Ecol Evol 2020. [DOI: 10.3389/fevo.2020.531014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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14
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Álvarez-Quintero N, Velando A, Kim SY. Long-Lasting Negative Effects of Learning Tasks During Early Life in the Three-Spined Stickleback. Front Ecol Evol 2020. [DOI: 10.3389/fevo.2020.562404] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
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15
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Harris C, Liedtke J, Drees C, Schuett W. Exploratory behaviour is not related to associative learning ability in the carabid beetle Nebria brevicollis. Behav Processes 2020; 180:104224. [PMID: 32828809 DOI: 10.1016/j.beproc.2020.104224] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 08/04/2020] [Accepted: 08/18/2020] [Indexed: 01/01/2023]
Abstract
Recently, it has been hypothesised that as learning performance and animal personality vary along a common axis of fast and slow types, natural selection may act on both in parallel leading to a correlation between learning and personality traits. We examined the relationship between risk-taking, exploratory behaviour and associative learning ability in carabid beetle Nebria brevicollis females by quantifying the number of trials individuals required to reach criterion during an associative learning task ('learning performance'). The associative learning task required the females to associate odour and direction with refugia from light and heat in a T-maze. Further, we assessed learning performance in a reversal task by quantifying the number of correct trials when the reinforcement was switched to previously unrewarding stimuli. We found that N. brevicollis females can associate conditional stimuli with a reward. No female was able to reverse the learned association within the number of trials given, however individuals differed in the number of correct trials in the reversal phase. Contrary to previous predictions neither exploratory behaviour, which was repeatable, nor risk-taking were correlated with learning performance. Our results suggest that the relationship between learning and personality may not take a common form across species.
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Affiliation(s)
- Ciaran Harris
- School of Life Sciences, University of Sussex, Falmer, Brighton BN1 9QG, United Kingdom
| | - Jannis Liedtke
- Department of Biological and Environmental Science, University of Jyvaskyla, PO Box 35, 40014, Finland
| | - Claudia Drees
- School of Life Sciences, University of Sussex, Falmer, Brighton BN1 9QG, United Kingdom; Institute of Zoology, Universität Hamburg, Martin-Luther-King Platz 3, 20146 Hamburg, Germany
| | - Wiebke Schuett
- School of Life Sciences, University of Sussex, Falmer, Brighton BN1 9QG, United Kingdom.
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16
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Predictors of individual variation in reversal learning performance in three-spined sticklebacks. Anim Cogn 2020; 23:925-938. [PMID: 32514661 DOI: 10.1007/s10071-020-01399-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 05/18/2020] [Accepted: 05/25/2020] [Indexed: 12/30/2022]
Abstract
Behavioral flexibility is a type of phenotypic plasticity that can influence how animals cope with environmental change and is often measured with a reversal learning paradigm. The goal of this study was to understand why individuals differ in behavioral flexibility, and whether individual differences in behavioral flexibility fit the predictions of coping styles theory. We tested whether individual variation in flexibility correlates with response to novelty (response to a novel object), boldness (emergence into a novel environment), and behavioral persistence (response to a barrier), and tested for trade-offs between how quickly individuals learn an initial discrimination and flexibility. We compare results when reversal learning performance is measured during an early step of reversal learning (e.g. the number of errors during the first reversal session) to when reversal learning performance is measured by time to criterion. Individuals that made fewer mistakes during an early step of reversal learning spent more time away from the novel object, were less bold, less persistent, and performed worse during initial discrimination learning. In contrast, time to criterion was not correlated with any of the behaviors measured. This result highlights the utility of dissecting the steps of reversal learning to better understand variation in behavioral flexibility. Altogether, this study suggests that individuals differ in flexibility because flexibility is a key ingredient to their overall integrated strategy for coping with environmental challenges.
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Langley EJG, Adams G, Beardsworth CE, Dawson DA, Laker PR, van Horik JO, Whiteside MA, Wilson AJ, Madden JR. Heritability and correlations among learning and inhibitory control traits. Behav Ecol 2020; 31:798-806. [PMID: 32821079 PMCID: PMC7428062 DOI: 10.1093/beheco/araa029] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 02/19/2020] [Accepted: 03/13/2020] [Indexed: 12/22/2022] Open
Abstract
To understand the evolution of cognitive abilities, we need to understand both how selection acts upon them and their genetic (co)variance structure. Recent work suggests that there are fitness consequences for free-living individuals with particular cognitive abilities. However, our current understanding of the heritability of these abilities is restricted to domesticated species subjected to artificial selection. We investigated genetic variance for, and genetic correlations among four cognitive abilities: inhibitory control, visual and spatial discrimination, and spatial ability, measured on >450 pheasants, Phasianus colchicus, over four generations. Pheasants were reared in captivity but bred from adults that lived in the wild and hence, were subject to selection on survival. Pheasant chicks are precocial and were reared without parents, enabling us to standardize environmental and parental care effects. We constructed a pedigree based on 15 microsatellite loci and implemented animal models to estimate heritability. We found moderate heritabilities for discrimination learning and inhibitory control (h2 = 0.17-0.23) but heritability for spatial ability was low (h2 = 0.09). Genetic correlations among-traits were largely positive but characterized by high uncertainty and were not statistically significant. Principle component analysis of the genetic correlation matrix estimate revealed a leading component that explained 69% of the variation, broadly in line with expectations under a general intelligence model of cognition. However, this pattern was not apparent in the phenotypic correlation structure which was more consistent with a modular view of animal cognition. Our findings highlight that the expression of cognitive traits is influenced by environmental factors which masks the underlying genetic structure.
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Affiliation(s)
- Ellis J G Langley
- Centre for Research in Animal Behaviour, College of Life and Environmental Sciences, Washington Singer Labs, University of Exeter, Exeter, UK
| | - Gracie Adams
- Department of Animal and Plant Sciences, Alfred Denny Building, University of Sheffield, Western Bank, Sheffield, UK
| | - Christine E Beardsworth
- Centre for Research in Animal Behaviour, College of Life and Environmental Sciences, Washington Singer Labs, University of Exeter, Exeter, UK
| | - Deborah A Dawson
- Department of Animal and Plant Sciences, Alfred Denny Building, University of Sheffield, Western Bank, Sheffield, UK
| | - Philippa R Laker
- Centre for Research in Animal Behaviour, College of Life and Environmental Sciences, Washington Singer Labs, University of Exeter, Exeter, UK
| | - Jayden O van Horik
- Centre for Research in Animal Behaviour, College of Life and Environmental Sciences, Washington Singer Labs, University of Exeter, Exeter, UK
| | - Mark A Whiteside
- Centre for Research in Animal Behaviour, College of Life and Environmental Sciences, Washington Singer Labs, University of Exeter, Exeter, UK
| | - Alastair J Wilson
- Centre for Ecology and Conservation, University of Exeter, Penryn Campus, Penryn, UK
| | - Joah R Madden
- Centre for Research in Animal Behaviour, College of Life and Environmental Sciences, Washington Singer Labs, University of Exeter, Exeter, UK
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18
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Golub MS, Sobin CA. Statistical modeling with litter as a random effect in mixed models to manage "intralitter likeness". Neurotoxicol Teratol 2019; 77:106841. [PMID: 31863841 DOI: 10.1016/j.ntt.2019.106841] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 10/25/2019] [Accepted: 10/31/2019] [Indexed: 12/15/2022]
Abstract
"Intralitter likeness," the possibility that the shared genetics and/or maternal environment in multiparous species causes strong similarity for outcome variables in littermates, violates a core statistical assumption, that of observation independence, when littermate outcomes are analyzed. Intralitter likeness has been of major concern to investigators for several decades. Despite consensus and guidance, many research reports in the rodent literature continue to ignore intralitter likeness. A historical review of the literature revealed that the long-preferred solution was to include litter as an effect in statistical models. Limitations in software development and computing capacity prior to 1990, however, appear to have led researchers and guidance authorities to endorse instead the method of using one value per litter. Here, the history of discussions regarding intralitter likeness in developmental neurotoxicological research is reviewed; growing knowledge regarding the biological bases and significance of intralitter likeness is discussed; principles underlying the use of litter as a random effect in mixed models are presented; statistical examples are provided illustrating the advantages and critical importance of including litter as a random effect in mixed models; and results using all data points (all pups from all litters) with litter as a random effect, are compared to results based on random selections of representative littermates. Mixed models with litter included as a random effect have distinct advantages for the analysis of clustered data. Modern computing capacity provides ready accessibility to mixed models for all researchers. Accessibility however does not preclude the need for appropriate expertise and consultation in the use of mixed (hierarchical) models.
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Affiliation(s)
- Mari S Golub
- California National Primate Research Center, University of California, Davis, Davis, CA, United States of America
| | - Christina A Sobin
- College of Health Sciences, University of Texas EL Paso, El Paso, TX, United States of America; Laboratory of Neuroendocrinology, The Rockefeller University, New York, NY, United States of America.
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19
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Abstract
'Enriched environments' are a key experimental paradigm to decipher how interactions between genes and environment change the structure and function of the brain across the lifespan of an animal. The regulation of adult hippocampal neurogenesis by environmental enrichment is a prime example of this complex interaction. As each animal in an enriched environment will have a slightly different set of experiences that results in downstream differences between individuals, enrichment can be considered not only as an external source of rich stimuli but also to provide the room for individual behaviour that shapes individual patterns of brain plasticity and thus function.
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20
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21
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Sorato E, Zidar J, Garnham L, Wilson A, Løvlie H. Heritabilities and co-variation among cognitive traits in red junglefowl. Philos Trans R Soc Lond B Biol Sci 2019; 373:rstb.2017.0285. [PMID: 30104430 DOI: 10.1098/rstb.2017.0285] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 06/20/2018] [Indexed: 12/15/2022] Open
Abstract
Natural selection can act on between-individual variation in cognitive abilities, yet evolutionary responses depend on the presence of underlying genetic variation. It is, therefore, crucial to determine the relative extent of genetic versus environmental control of these among-individual differences in cognitive traits to understand their causes and evolutionary potential. We investigated heritability of associative learning performance and of a cognitive judgement bias (optimism), as well as their covariation, in a captive pedigree-bred population of red junglefowl (Gallus gallus, n > 300 chicks over 5 years). We analysed performance in discriminative and reversal learning (two facets of associative learning), and cognitive judgement bias, by conducting animal models to disentangle genetic from environmental contributions. We demonstrate moderate heritability for reversal learning, and weak to no heritability for optimism and discriminative learning, respectively. The two facets of associative learning were weakly negatively correlated, consistent with hypothesized trade-offs underpinning individual cognitive styles. Reversal, but not discriminative learning performance, was associated with judgement bias; less optimistic individuals reversed a previously learnt association faster. Together these results indicate that genetic and environmental contributions differ among traits. While modular models of cognitive abilities predict a lack of common genetic control for different cognitive traits, further investigation is required to fully ascertain the degree of covariation between a broader range of cognitive traits and the extent of any shared genetic control.This article is part of the theme issue 'Causes and consequences of individual differences in cognitive abilities'.
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Affiliation(s)
- Enrico Sorato
- Department of Physics, Chemistry and Biology, IFM Biology, Linköping University, Linköping 581 83, Sweden
| | - Josefina Zidar
- Department of Physics, Chemistry and Biology, IFM Biology, Linköping University, Linköping 581 83, Sweden
| | - Laura Garnham
- Department of Physics, Chemistry and Biology, IFM Biology, Linköping University, Linköping 581 83, Sweden
| | - Alastair Wilson
- Centre for Ecology and Conservation, University of Exeter, Penryn Campus, Penryn, Cornwall TR10 9FE, UK
| | - Hanne Løvlie
- Department of Physics, Chemistry and Biology, IFM Biology, Linköping University, Linköping 581 83, Sweden
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22
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Boogert NJ, Madden JR, Morand-Ferron J, Thornton A. Measuring and understanding individual differences in cognition. Philos Trans R Soc Lond B Biol Sci 2019; 373:rstb.2017.0280. [PMID: 30104425 DOI: 10.1098/rstb.2017.0280] [Citation(s) in RCA: 122] [Impact Index Per Article: 24.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/10/2018] [Indexed: 12/30/2022] Open
Abstract
Individuals vary in their cognitive performance. While this variation forms the foundation of the study of human psychometrics, its broader importance is only recently being recognized. Explicitly acknowledging this individual variation found in both humans and non-human animals provides a novel opportunity to understand the mechanisms, development and evolution of cognition. The papers in this special issue highlight the growing emphasis on individual cognitive differences from fields as diverse as neurobiology, experimental psychology and evolutionary biology. Here, we synthesize this body of work. We consider the distinct challenges in quantifying individual differences in cognition and provide concrete methodological recommendations. In particular, future studies would benefit from using multiple task variants to ensure they target specific, clearly defined cognitive traits and from conducting repeated testing to assess individual consistency. We then consider how neural, genetic, developmental and behavioural factors may generate individual differences in cognition. Finally, we discuss the potential fitness consequences of individual cognitive variation and place these into an evolutionary framework with testable hypotheses. We intend for this special issue to stimulate researchers to position individual variation at the centre of the cognitive sciences.This article is part of the theme issue 'Causes and consequences of individual differences in cognitive abilities'.
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Affiliation(s)
- Neeltje J Boogert
- Centre for Ecology and Conservation, Daphne du Maurier Building, University of Exeter, Penryn TR10 9FE, UK
| | - Joah R Madden
- Department of Psychology, Washington Singer Labs, University of Exeter, Exeter EX4 4QG, UK
| | - Julie Morand-Ferron
- Department of Biology, University of Ottawa, 30 Marie Curie, Ottawa, Canada, K1N 6N5
| | - Alex Thornton
- Centre for Ecology and Conservation, Daphne du Maurier Building, University of Exeter, Penryn TR10 9FE, UK
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23
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Boogert NJ, Lachlan RF, Spencer KA, Templeton CN, Farine DR. Stress hormones, social associations and song learning in zebra finches. Philos Trans R Soc Lond B Biol Sci 2018; 373:20170290. [PMID: 30104435 PMCID: PMC6107560 DOI: 10.1098/rstb.2017.0290] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/18/2018] [Indexed: 11/12/2022] Open
Abstract
The use of information provided by others is a common short-cut adopted to inform decision-making. However, instead of indiscriminately copying others, animals are often selective in what, when and whom they copy. How do they decide which 'social learning strategy' to use? Previous research indicates that stress hormone exposure in early life may be important: while juvenile zebra finches copied their parents' behaviour when solving novel foraging tasks, those exposed to elevated levels of corticosterone (CORT) during development copied only unrelated adults. Here, we tested whether this switch in social learning strategy generalizes to vocal learning. In zebra finches, juvenile males often copy their father's song; would CORT-treated juveniles in free-flying aviaries switch to copying songs of other males? We found that CORT-treated juveniles copied their father's song less accurately as compared to control juveniles. We hypothesized that this could be due to having weaker social foraging associations with their fathers, and found that sons that spent less time foraging with their fathers produced less similar songs. Our findings are in line with a novel hypothesis linking early-life stress and social learning: early-life CORT exposure may affect social learning indirectly as a result of the way it shapes social affiliations.This article is part of the theme issue 'Causes and consequences of individual differences in cognitive abilities'.
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Affiliation(s)
- Neeltje J Boogert
- Centre for Ecology and Conservation, University of Exeter, Penryn Campus, Penryn TR10 9FE, UK
| | - Robert F Lachlan
- School of Biological and Chemical Sciences, Queen Mary University of London, London E1 4NS, UK
| | - Karen A Spencer
- School of Psychology and Neuroscience, University of St. Andrews, St Andrews KY16 9JP, UK
| | | | - Damien R Farine
- Department of Collective Behaviour, Max Planck Institute for Ornithology, Radolfzell 78315, Germany
- Chair of Biodiversity and Collective Behaviour, Department of Biology, University of Konstanz, Konstanz 78464, Germany
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24
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Dubois J, Galdi P, Paul LK, Adolphs R. A distributed brain network predicts general intelligence from resting-state human neuroimaging data. Philos Trans R Soc Lond B Biol Sci 2018; 373:20170284. [PMID: 30104429 PMCID: PMC6107566 DOI: 10.1098/rstb.2017.0284] [Citation(s) in RCA: 149] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/30/2018] [Indexed: 02/04/2023] Open
Abstract
Individual people differ in their ability to reason, solve problems, think abstractly, plan and learn. A reliable measure of this general ability, also known as intelligence, can be derived from scores across a diverse set of cognitive tasks. There is great interest in understanding the neural underpinnings of individual differences in intelligence, because it is the single best predictor of long-term life success. The most replicated neural correlate of human intelligence to date is total brain volume; however, this coarse morphometric correlate says little about function. Here, we ask whether measurements of the activity of the resting brain (resting-state fMRI) might also carry information about intelligence. We used the final release of the Young Adult Human Connectome Project (N = 884 subjects after exclusions), providing a full hour of resting-state fMRI per subject; controlled for gender, age and brain volume; and derived a reliable estimate of general intelligence from scores on multiple cognitive tasks. Using a cross-validated predictive framework, we predicted 20% of the variance in general intelligence in the sampled population from their resting-state connectivity matrices. Interestingly, no single anatomical structure or network was responsible or necessary for this prediction, which instead relied on redundant information distributed across the brain.This article is part of the theme issue 'Causes and consequences of individual differences in cognitive abilities'.
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Affiliation(s)
- Julien Dubois
- Division of Humanities and Social Sciences, Pasadena, CA 91125, USA
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Paola Galdi
- Department of Management and Innovation Systems, University of Salerno, Fisciano Salerno, Italy
- MRC Centre for Reproductive Health, University of Edinburgh, EH16 4TJ, UK
| | - Lynn K Paul
- Division of Humanities and Social Sciences, Pasadena, CA 91125, USA
- Chen Neuroscience Institute, California Institute of Technology, Pasadena, CA 91125, USA
| | - Ralph Adolphs
- Division of Humanities and Social Sciences, Pasadena, CA 91125, USA
- Division of Biology and Biological Engineering, Pasadena, CA 91125, USA
- Chen Neuroscience Institute, California Institute of Technology, Pasadena, CA 91125, USA
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25
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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] [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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