Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-28T12:43:11.818Z Has data issue: false hasContentIssue false
  • English
  • Français

The evolution of general intelligence

Published online by Cambridge University Press:  28 July 2016

Judith M. Burkart ,
Michèle N. Schubiger  and
Carel P. van Schaik
Judith M. Burkart
Affiliation:
Department of Anthropology, University of Zurich, CH-8125 Zurich, SwitzerlandJudith.Burkart@aim.uzh.chhttp://www.aim.uzh.ch/de/Members/seniorlecturers/judithburkart.html
Michèle N. Schubiger
Affiliation:
Department of Anthropology, University of Zurich, CH-8125 Zurich, Switzerlandmichele.schubiger@aim.uzh.chhttp://www.aim.uzh.ch/de/Members/phdstudents/micheleschubiger.html
Carel P. van Schaik
Affiliation:
Department of Anthropology, University of Zurich, CH-8125 Zurich, Switzerlandvschaik@aim.uzh.chhttp://www.aim.uzh.ch/de/Members/profofinstitute/vanschaik.html
Get access Rights & Permissions [Opens in a new window]

Abstract

The presence of general intelligence poses a major evolutionary puzzle, which has led to increased interest in its presence in nonhuman animals. The aim of this review is to critically evaluate this question and to explore the implications for current theories about the evolution of cognition. We first review domain-general and domain-specific accounts of human cognition in order to situate attempts to identify general intelligence in nonhuman animals. Recent studies are consistent with the presence of general intelligence in mammals (rodents and primates). However, the interpretation of a psychometric g factor as general intelligence needs to be validated, in particular in primates, and we propose a range of such tests. We then evaluate the implications of general intelligence in nonhuman animals for current theories about its evolution and find support for the cultural intelligence approach, which stresses the critical importance of social inputs during the ontogenetic construction of survival-relevant skills. The presence of general intelligence in nonhumans implies that modular abilities can arise in two ways, primarily through automatic development with fixed content and secondarily through learning and automatization with more variable content. The currently best-supported model, for humans and nonhuman vertebrates alike, thus construes the mind as a mix of skills based on primary and secondary modules. The relative importance of these two components is expected to vary widely among species, and we formulate tests to quantify their strength.

Keywords

brain size evolutioncomparative approachcultural intelligenceevolution of intelligencegeneral intelligencemodularitynonhuman primatespositive manifoldpsychometric intelligencerodentssocial learningspecies comparisons
Type
Target Article
Information
Behavioral and Brain Sciences , Volume 40 , 2017 , e195
Check for updates
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abutalebi, J. & Clahsen, H. (2015) Bilingualism, cognition, and aging. Bilingualism: Language and Cognition 18(01):1–2.CrossRefGoogle Scholar
Amici, F., Aureli, F. & Call, J. (2008) Fission-fusion dynamics, behavioral flexibility, and inhibitory control in primates. Current Biology 18(18):1415–19.Google Scholar
Amici, F., Aureli, F. & Call, J. (2010) Monkeys and apes: Are their cognitive skills really so different? American Journal of Physical Anthropology 143(2):188–97.CrossRefGoogle ScholarPubMed
Amici, F., Barney, B., Johnson, V. E., Call, J. & Aureli, F. (2012) A modular mind? A test using individual data from seven primate species. PLoS One 7(12):e51918.Google Scholar
Amiel, J. J., Tingley, R. & Shine, R. (2011) Smart moves: Effects of relative brain size on establishment success of invasive amphibians and reptiles. PLoS One 6(4):e18277.CrossRefGoogle ScholarPubMed
Anderson, B. (1993) Evidence from the rat for a general factor that underlies cognitive performance and that relates to brain size: Intelligence? Neuroscience Letters 153(1):98–102.Google Scholar
Anderson, M. L. & Finlay, B. L. (2014) Allocating structure to function: The strong links between neuroplasticity and natural selection. Frontiers in Human Neuroscience 7:918, 1–16.Google Scholar
Aplin, L. M., Farine, D. R., Morand-Ferron, J., Cockburn, A., Thornton, A. & Sheldon, B. C. (2015) Experimentally induced innovations lead to persistent culture via conformity in wild birds. Nature 518(7540):538–41.CrossRefGoogle ScholarPubMed
Arden, R. & Adams, M. J. (2016) A general intelligence factor in dogs. Intelligence 55:79–85.Google Scholar
Baddeley, A. (2010) Working memory. Current Biology 20:R136–40.Google Scholar
Bailey, A. M., McDaniel, W. F. & Thomas, R. K. (2007) Approaches to the study of higher cognitive functions related to creativity in nonhuman animals. Methods 42(1):3–11.CrossRefGoogle Scholar
Banerjee, K., Chabris, C. F., Johnson, V. E., Lee, J. J., Tsao, F. & Hauser, M. D. (2009) General intelligence in another primate: Individual differences across cognitive task performance in a New World monkey (Saguinus oedipus). PLoS ONE 4(6):e5883.Google Scholar
Barbey, A. K., Colom, R., Solomon, J., Krueger, F., Forbes, C. & Grafman, J. (2012) An integrative architecture for general intelligence and executive function revealed by lesion mapping. Brain 135(4):1154–64.Google Scholar
Barney, B. J., Amici, F., Aureli, F., Call, J. & Johnson, V. E. (2015) Joint Bayesian modeling of binomial and rank data for primate cognition. Journal of the American Statistical Association 110(510):573–82.Google Scholar
Barrett, H. C. (2015) Modularity. In: Evolutionary perspectives on social psychology, ed. Zeigler-Hill, V., Welling, L. L. M. & Schackelford, T. K., pp. 39–51. Springer International.Google Scholar
Barrett, H. C. & Kurzban, R. (2006) Modularity in cognition: Framing the debate. Psychological Review 113(3):628–47.Google Scholar
Barrett, H. C. & Kurzban, R. (2012) What are the functions of System 2 modules? A reply to Chiappe and Gardner. Theory & Psychology 22(5):683–88.Google Scholar
Bartholomew, D. J., Deary, I. J. & Lawn, M. (2009) A new lease of life for Thomson's bonds model of intelligence. Psychological Review 116:567–79. Available at: https://doi.org/10.1037/a0016262.CrossRefGoogle ScholarPubMed
Behrens, T. E. J., Hunt, L. T., Woolrich, M. W. & Rushworth, M. F. S. (2008) Associative learning of social value. Nature 456(7219):245–49.CrossRefGoogle ScholarPubMed
Bialystok, E., Craik, F. I. & Luk, G. (2012) Bilingualism: Consequences for mind and brain. Trends in Cognitive Sciences 16(4):240–50.Google Scholar
Bilalić, M., Langner, R., Ulrich, R. & Grodd, W. (2011) Many faces of expertise: Fusiform face area in chess experts and novices. The Journal of Neuroscience 31(28):10206–14.Google Scholar
Blair, C. (2006) How similar are fluid cognition and general intelligence? A developmental neuroscience perspective on fluid cognition as an aspect of human cognitive ability. Behavioral and Brain Sciences 29(2):109–25; discussion 125–60. doi: 10.1017/S0140525X06009034.Google Scholar
Bolhuis, J. J., Brown, G. R., Richardson, R. C. & Laland, K. N. (2011) Darwin in mind: New opportunities for evolutionary psychology. PLoS Biology 9(7):e1001109.CrossRefGoogle ScholarPubMed
Bouchard, T. J. (2014) Genes, evolution and intelligence. Behavioural Genetics 44(6):549–77.Google Scholar
Box, H. O. (1984) Primate behavior and social ecology. Chapman and Hall.Google Scholar
Boyd, R., Richerson, P. J. & Henrich, J. (2011) The cultural niche: Why social learning is essential for human adaptation. Proceedings of the National Academy of Sciences USA 108(Supplement 2):10918–25.CrossRefGoogle ScholarPubMed
Brodin, A. (2010) The history of scatter hoarding studies. Philosophical Transactions of the Royal Society B: Biological Sciences 365(1542):869–81.Google Scholar
Brown, J., Kaplan, G., Rogers, L. J. & Vallortigara, G. (2010) Perception of biological motion in common marmosets (Callithrix jacchus): By females only. Animal Cognition 13(3):555–64.Google Scholar
Burgess, G. C., Gray, J. R., Conway, A. R. A. & Braver, T. S. (2011) Neural mechanisms of interference control underlie the relationship between fluid intelligence and working memory span. Journal of Experimental Psychology: General 140(4):674.Google Scholar
Burkart, J. M. (2017) The evolution and consequences of sociality. In: Oxford handbook of comparative psychology, ed. Call, J., Burghardt, G. M., Pepperberg, I. M., Snowdon, C. T. & Zentall, T.. Oxford University Press.Google Scholar
Burkart, J. M., Hrdy, S. B. & van Schaik, C. P. (2009) Cooperative breeding and human cognitive evolution. Evolutionary Anthropology 18:175–86.CrossRefGoogle Scholar
Burkart, J. M. & van Schaik, C. P. (2010) Cognitive consequences of cooperative breeding. Animal Cognition 31:1–19.Google Scholar
Burkart, J. M. & van Schaik, C. P. (2016a) Revisiting the consequences of cooperative breeding. A response to Thornton & McAuliffe (2015) Journal of Zoology 299:77–83. doi:10.1111/jzo.12322.Google Scholar
Burkart, J. M. & van Schaik, C. P. (2016b) The cooperative breeding perspective helps pinning down when uniquely human evolutionary processes are necessary. Commentary to Richerson et al. . (2016) Behavioral and Brain Sciences 39:e34.Google Scholar
Byrne, R. W. (1994) The evolution of intelligence. In: Behaviour and evolution, ed. Slater, P. J. B. & Halliday, T. R., Cambridge University Press.Google Scholar
Byrne, R. W. & Corp, N. (2004) Neocortex size predicts deception rate in primates. Proceedings of the Royal Society of London B: Biological Sciences 271:1693–99.Google Scholar
Byrne, R. W. & Whiten, A. (1990) Tactical deception in primates: The 1990 database. Primate Report 27:1–101.Google Scholar
Cardoso, R. M. (2013) Resolução de problema por macacos-prego selvagens (Sapajus libidinosus) de duas populações com diferentes repertórios de uso de ferramentas. Ph.D. dissertation, Departamento de Psicologia Experimental, Universidade de São Paulo.Google Scholar
Carey, S. (2009) The origin of concepts. Oxford University Press.Google Scholar
Carroll, J. B. (1993) Human cognitive abilities: A survey of factor-analytic studies. Cambridge University Press.Google Scholar
Carruthers, P. (2005) The case for massively modular models of mind. In: Contemporary debates in cognitive science, ed. Stainton, R., pp. 205–25. Blackwell.Google Scholar
Carruthers, P. (2011) I do not exist. Trends in Cognitive Sciences 15(5):189–90.Google Scholar
Cattell, R. B. (1963) Theory of fluid and crystallized intelligence: A critical experiment. Journal of Educational Psychology 54(1):1–22.Google Scholar
Cattell, R. B. (1987) Intelligence: Its structure, growth and action. Elsevier.Google Scholar
Chabris, C. F. (2007) Cognitive and neurobiological mechanisms of the law of general intelligence. In: Integrating the mind: Domain general versus domain specific processes in higher cognition, ed. Roberts, M. J., pp. 449–91. Psychology Press.Google Scholar
Chang, Y. (2014) Reorganization and plastic changes of the human brain associated with skill learning and expertise. Frontiers in Human Neuroscience 8:35.Google Scholar
Chiappe, D. & Gardner, R. A. (2012) The modularity debate in evolutionary psychology. Theory & Psychology 22(5):669–82.Google Scholar
Chittka, L. & Niven, J. (2009) Are bigger brains better? Current Biology 19(21):R995–1008.Google Scholar
Chudasama, Y. (2011) Animal models of prefrontal-executive function. Behavioral Neuroscience 125(3):327–43.CrossRefGoogle ScholarPubMed
Clune, J., Mouret, J. B. & Lipson, H. (2013) The evolutionary origins of modularity. Proceedings of the Royal Society of London B: Biological Sciences 280(1755):20122863.Google Scholar
Colom, R., Abad, F. J., Rebollo, I. & Shih, P. C. (2005) Memory span and general intelligence: A latent-variable approach. Intelligence 33:623–42.Google Scholar
Colom, R., Jung, R. E. & Haier, R. J. (2006) Distributed brain sites for the g-factor of intelligence. NeuroImage 31(3):1359–65.CrossRefGoogle ScholarPubMed
Coltheart, M. (2011) Methods for modular modelling: Additive factors and cognitive neuropsychology. Cognitive Neuropsychology 28(3–4):224–40.Google Scholar
Cook, M. & Mineka, S. (1989) Observational conditioning of fear to fear-relevant versus fear-irrelevant stimuli in rhesus monkeys. Journal of Abnormal Psychology 98:448–59.CrossRefGoogle ScholarPubMed
Cosmides, L. & Tooby, J. (1994) Origins of domain specificity: The evolution of functional organization. In: Mapping the mind: Domain specificity in cognition and culture, ed. Hirschfeld, L. & Gelman, S., pp. 85–116. Cambridge University Press.Google Scholar
Cosmides, L. & Tooby, J. (2002) Unraveling the enigma of human intelligence: Evolutionary psychology and the multimodular mind. In: The evolution of intelligence, ed. Sternberg, R. J. & Kaufman, J. C., pp. 145–98. Erlbaum.Google Scholar
Cosmides, L. & Tooby, J. (2013) Evolutionary psychology: New perspectives on cognition and motivation. Annual Review of Psychology 64:201–29.CrossRefGoogle ScholarPubMed
Cosmides, L., Barrett, H. C. & Tooby, J. (2010) Adaptive specializations, social exchange, and the evolution of human intelligence. Proceedings of the National Academy of Sciences USA 107(Supplement 2):9007–14.Google Scholar
d'Souza, D. & Karmiloff-Smith, A. (2011) When modularization fails to occur: A developmental perspective. Cognitive Neuropsychology 28(3–4):276–87.Google Scholar
Dahl, C. D., Chen, C. C. & Rasch, M. J. (2014) Own-race and own-species advantages in face perception: A computational view. Scientific Reports 4:6654.Google Scholar
Davies, G., Tenesa, A., Payton, A., Yang, J., Harris, S. E., Liewald, D., Liewald D, Ke X, Le Hellard, S., Christoforou, A., Luciano, M., McGhee, K., Lopez, L., Gow, A. J., Corley, J., Redmond, P., Fox, H. C., Haggarty, P., Whalley, L. J., McNeill, G., Goddard, M. E., Espeseth, T., Lundervold, A. J., Reinvang, I., Pickles, A., Steen, V. M., Ollier, W., Porteous, D. J., Horan, M., Starr, J. M., Pendleton, N., Visscher, P. M. & Deary, I. J. (2011) Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Molecular Psychiatry 16:996–1005.Google Scholar
Dean, L. G., Vale, G. L., Laland, K. N., Flynn, E. & Kendal, R. L. (2014) Human cumulative culture: A comparative perspective. Biological Reviews 89(2):284–301.Google Scholar
Deaner, R. O., Isler, K., Burkart, J. M. & van Schaik, C. P. (2007) Overall brain size, and not encephalization quotient, best predicts cognitive ability across non-human primates. Brain, Behaviour and Evolution 70(2):115–24.Google Scholar
Deaner, R. O., van Schaik, C. P. & Johnson, V. E. (2006) Do some taxa have better domain-general cognition than others? A meta-analysis of nonhuman primate studies. Evolutionary Psychology 4:149–96.Google Scholar
Deary, I. J., Penke, L. & Johnson, W. (2010) The neuroscience of human intelligence differences. Nature Reviews Neuroscience 11(3):201–11.Google Scholar
Diamond, A. (2013) Executive functions. Annual Review of Psychology 64:135.Google Scholar
Drake, J. M. (2007) Parental investment and fecundity, but not brain size, are associated with establishment success in introduced fishes. Functional Ecology 21(5):963–68.CrossRefGoogle Scholar
Ducatez, S., Clavel, J. & Lefebvre, L. (2015) Ecological generalism and behavioural innovation in birds: Technical intelligence or the simple incorporation of new foods? Journal of Animal Ecology 84(1):79–89.CrossRefGoogle ScholarPubMed
Duchaine, B., Cosmides, L. & Tooby, J. (2001) Evolutionary psychology and the brain. Current Opinion in Neurobiology 11(2):225–30.Google Scholar
Dunbar, R. I. M. (1992) Neocortex size as a constraint on group size in primates. Journal of Human Evolution 20:469–93.Google Scholar
Dunbar, R. I. M. & Shultz, S. (2007a) Evolution in the social brain. Science 317:1344–47.Google Scholar
Dunbar, R. I. M. & Shultz, S. (2007b) Understanding primate brain evolution. Philosophical Transactions of the Royal Society B: Biological Sciences 362(1480):649–58.Google Scholar
Embretson, S. E. (1995) The role of working memory capacity and general control processes in intelligence. Intelligence 20(2):169–89.Google Scholar
Eraña, A. (2012) Dual process theories versus massive modularity hypotheses. Philosophical Psychology 25(6):855–72.Google Scholar
Evans, J. S. B. T. (2011) Dual-process theories of reasoning: Contemporary issues and developmental applications. Developmental Review 31(2):86–102.Google Scholar
Evans, J. S. B. T. (2013) Two minds rationality. Thinking & Reasoning 20:129–46.Google Scholar
Fernandes, H. B. F., Woodley, M. A. & te Nijenhuis, J. (2014) Differences in cognitive abilities among primates are concentrated on G: Phenotypic and phylogenetic comparisons with two meta-analytical databases. Intelligence 46:311–22.CrossRefGoogle Scholar
Firestone, C. & Scholl, B. J. (2015) Cognition does not affect perception: Evaluating the evidence for “top-down” effects. Behavioral and Brain Sciences, 1–72. doi: http://dx.doi.org/10.1017/S0140525X15000965.Google Scholar
Fodor, J. A. (1983) Modularity of the mind. MIT Press.Google Scholar
Forss, S. I. F., Schuppli, C., Haiden, D., Zweifel, N. & van Schaik, C. P. (2015) Contrasting responses to novelty by wild and captive orangutans. American Journal of Primatology 77(10):1109–21.CrossRefGoogle ScholarPubMed
Frankenhuis, W. E. & Ploeger, A. (2007) Evolutionary psychology versus Fodor: Arguments for and against the massive modularity hypothesis. Philosophical Psychology 20(6):687–710.CrossRefGoogle Scholar
Galef, B. G. (2015) Laboratory studies of imitation/field studies of tradition: Towards a synthesis in animal social learning. Behavioural Processes 112:114–19.CrossRefGoogle ScholarPubMed
Galsworthy, M. J., Arden, R. & Chabris, C. F. (2014) Animal models of general cognitive ability for genetic research into cognitive functioning. In: Behavior genetics of cognition across the lifespan, ed. Finkel, D. & Reynolds, C. A., pp. 257–78. Springer.Google Scholar
Galsworthy, M. J., Paya-Cano, J. L., Liu, L., Monleón, S., Gregoryan, G., Fernandes, C., Schalkwyk, L. C. & Plomin, R. (2005) Assessing reliability, heritability and general cognitive ability in a battery of cognitive tasks for laboratory mice. Behavioral Genetics 35(5):675–92.Google Scholar
Galsworthy, M. J., Paya-Cano, J. L., Monleo, S. & Plomin, R. (2002) Evidence for general cognitive ability (g) in heterogeneous stock mice and an analysis of potential confounds. Genes, Brain and Behavior 1:88–95.Google Scholar
Garcia, J. & Koelling, R. A. (1966) Relation of cue to consequence in avoidance learning. Psychonomic Science 4(1):123–24.Google Scholar
Garson, D. G. (2013) Factor analysis. Statistical Associates.Google Scholar
Geary, D. C. (1995) Reflections of evolution and culture in children's cognition: Implications for mathematical development and instruction. American Psychologist 50(1):24.CrossRefGoogle ScholarPubMed
Geary, D. C. (2005) The origin of mind. Evolution of brain, cognition, and general Intelligence. American Psychological Association.Google Scholar
Geary, D. C. (2009) The evolution of general fluid intelligence. In: Foundations in evolutionary cognitive neuroscience, ed. Platek, S. M. & Shackelford, T. K., pp. 22–56. Cambridge University Press.Google Scholar
Geary, D. C. & Huffman, K. J. (2002) Brain and cognitive evolution: Forms of modularity and functions of mind. Psychological Bulletin 128(5):667.Google Scholar
Gelman, R. (1990) First principles organize attention to and learning about relevant data: Number and the animate-inanimate distinction as examples. Cognitive Science 14(1):79–106.Google Scholar
Gläscher, J., Rudrauf, D., Colom, R., Paul, L. K., Tranel, D., Damasio, H. & Adolphs, R. (2010) Distributed neural system for general intelligence revealed by lesion mapping. Proceedings of the National Academy of Sciences USA 107(10):4705–709.Google Scholar
Gottfredson, L. S. (1997) Mainstream science on intelligence: An editorial with 52 signatories, history, and bibliography. Intelligence 24:13–23.CrossRefGoogle Scholar
Greenough, W. T., Black, J. E. & Wallace, C. S. (1987) Experience and brain development. Child Development 58:539–59.Google Scholar
Grossi, G. (2014) A module is a module is a module: Evolution of modularity in Evolutionary Psychology. Dialectical Anthropology 38(3):333–51.Google Scholar
Grossman, H. C., Hale, G., Light, K., Kolata, S., Townsend, D. A., Goldfarb, Y., Kusnecov, A. & Matzel, L. D. (2007) Pharmacological modulation of stress reactivity dissociates general learning ability from the propensity for exploration. Behavioral Neuroscience 121(5):949.Google Scholar
Gruber, T., Muller, M. N., Reynolds, V., Wrangham, R. & Zuberbühler, K. (2011) Community-specific evaluation of tool affordances in wild chimpanzees. Scientific Reports 1:128.Google Scholar
Heldstab, S. A., Kosonen, Z. K., Koski, S. E., Burkart, J. M., van Schaik, C. P. & Isler, K. (2016) Manipulation complexity in primates coevolved with brain size and terrestriality. Scientific Reports 6:24528. doi: 10.1038/srep24528.Google Scholar
Herndon, J. G., Moss, M. B., Rosene, D. L. & Killiany, R. (1997) Patterns of cognitive decline in aged rhesus monkeys. Behavioural Brain Research 87:25–34.Google Scholar
Herrmann, E. & Call, J. (2012) Are there geniuses among the apes? Philosophical Transactions of the Royal Society B 367:2753–61.Google Scholar
Herrmann, E., Call, J., Hernández-Lloreda, M. V., Hare, B. & Tomasello, M. (2007) Humans have evolved specialized skills of social cognition: The cultural intelligence hypothesis. Science 317:1360–66.CrossRefGoogle ScholarPubMed
Herrmann, E., Hare, B., Call, J. & Tomasello, M. (2010a) Differences in the cognitive skills of bonobos and chimpanzees. PLoS One 5(8):e12438.Google Scholar
Herrmann, E., Hernandez-Lloreda, M. V., Call, J., Hare, B. & Tomasello, M. (2010b) The structure of individual differences in the cognitive abilities of children and chimpanzees. Psychological Science 21(1):102–10.Google Scholar
Heyes, C. (2003) Four routes of cognitive evolution. Psychological Review 110(4):713–27.Google Scholar
Heyes, C. (2012) What's social about social learning? Journal of Comparative Psychology 126(2):193–202.Google Scholar
Heyes, C. (2016) Who knows? Metacognitive social learning strategies. Trends in Cognitive Sciences 20:204–13.Google Scholar
Heyes, C. M. (1994) Social learning in animals: Categories and mechanisms. Biological Reviews 69(2):207–31.Google Scholar
Holekamp, K. E. (2007) Questioning the social intelligence hypothesis. Trends in Cognitive Sciences 11(2):65–69.Google Scholar
Holekamp, K. E., Dantzer, B., Stricker, G., Yoshida, K. C. S. & Benson-Amram, S. (2015) Brains, brawn and sociality: A hyaena's tale. Animal Behaviour 103:237–48.CrossRefGoogle ScholarPubMed
Hopkins, W. D., Russel, J. L. & Schaeffer, J. (2014) Chimpanzee intelligence is heritable. Current Biology 24:1649–52.Google Scholar
Hoppitt, W. & Laland, K. N. (2013) Social learning: An introduction to mechanisms, methods, and models. Princeton University Press.Google Scholar
Hrdy, S. (2009) Mothers & others: The evolutionary origins of mutual understanding. Harvard University Press.Google Scholar
Hufendiek, R. & Wild, M. (2015) Faculties and Modularity. In: The faculties: A history, ed. Perler, D., pp. 254–99. Oxford University Press.Google Scholar
Humphrey, N. K. (1976) The social function of intellect. In: Growing points in ethology, ed. Bateson, P. P. G. & Hinde, R. A., pp. 303–17. Cambridge University Press.Google Scholar
Husby, A. & Husby, M. (2014) Interspecific analysis of vehicle avoidance behavior in birds. Behavioral Ecology 25(3):504–508.Google Scholar
Isden, J., Panayi, C., Dingle, C. & Madden, J. (2013) Performance in cognitive and problem-solving tasks in male spotted bowerbirds does not correlate with mating success. Animal Behaviour 86(4):829–38. doi: 10.1016/j.anbehav.2013.07.024.Google Scholar
Isler, K. & van Schaik, C. P. (2014) How humans evolved large brains: Comparative evidence. Evolutionary Anthropology: Issues, News, and Reviews 23(2):65–75.Google Scholar
Jaeggi, A. V., Dunkel, L. P., Van Noordwijk, M. A., Wich, S. A., Sura, A. A. & van Schaik, C. P. (2010) Social learning of diet and foraging skills by wild immature Bornean orangutans. American Journal of Primatology 72:62–71.Google Scholar
Jensen, A. R. & Weng, L.-J. (1994) What is a good g? Intelligence 18(3):231–58.Google Scholar
Johansen-Berg, H. (2007) Structural plasticity: Rewiring the brain. Current Biology 17(4):R141–44.CrossRefGoogle ScholarPubMed
Johnson, V. E., Deaner, R. O. & van Schaik, C. P. (2002) Bayesian analysis of rank data with application to primate intelligence experiments. Journal of the American Statistical Association 97(457):8–17.Google Scholar
Jolly, A. (1966) Lemur social behaviour and primate intelligence. Science 153(3735):501–506.Google Scholar
Joshi, P. K., Esko, T., Mattsson, H., Eklund, N., Gandin, I., Nutile, T., Jackson, A. U., Schurmann, C., Smith, A. V., Zhang, W., Okada, Y., Stančáková, A., Faul, J. D., Zhao, W., Bartz, T. M., Concas, M. P., Franceschini, N., Enroth, S., Vitart, V., Trompet, S. & 340 others (2015) Directional dominance on stature and cognition in diverse human populations. Nature 523(7561):459–62.Google Scholar
Jung, R. E. & Haier, R. J. (2007) The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence. Behavioral and Brain Sciences 30(02):135–54.CrossRefGoogle ScholarPubMed
Kan, K.-J., Kievit, R. A., Dolan, C. & van der Maas, H. V. (2011) On the interpretation of the CHC factor Gc. Intelligence 39(5):292–302.CrossRefGoogle Scholar
Kaufman, S. B., DeYoung, C. G., Reis, D. L. & Gray, J. R. (2011) General intelligence predicts reasoning ability even for evolutionarily familiar content. Intelligence 39:311–22.Google Scholar
Keagy, J., Savard, J. F. & Borgia, G. (2011) Complex relationship between multiple measures of cognitive ability and male mating success in satin bowerbirds, Ptilonorhynchus violaceus. Animal Behaviour 81(5):1063–70.Google Scholar
Kendal, R. L., Hopper, L. M., Whiten, A., Brosnan, S. F., Lambeth, S. P., Schapiro, S. J. & Hoppitt, W. (2015) Chimpanzees copy dominant and knowledgeable individuals: Implications for cultural diversity. Evolution and Human Behavior 36(1):65–72.Google Scholar
Kievit, R. A., Frankenhuis, W. E., Waldorp, L. J. & Borsboom, D. (2013) Simpson's Paradox in psychological science: A practical guide. Frontiers in Psychology 4:Article 513, 1–14.Google Scholar
Kline, M. A. (2015) How to learn about teaching: An evolutionary framework for the study of teaching behavior in humans and other animals. Behavioral and Brain Sciences 38:e31.Google Scholar
Klingberg, T. (2010) Training and plasticity of working memory. Trends in Cognitive Sciences 14(7):317–24.Google Scholar
Koenig, A. (1998) Visual scanning by common marmosets (Callithrix jacchus): Functional aspects and the special role of adult males. Primates 39:85–90.Google Scholar
Kolata, S., Light, K., Grossman, H. C., Hale, G. & Matzel, L. D. (2007) Selective attention is a primary determinant of the relationship between working memory and general learning ability in outbred mice. Learning & Memory 14(1–2):22–28.Google Scholar
Kolata, S., Light, K. & Matzel, L. D. (2008) Domain-specific and domain-general learning factors are expressed in genetically heterogeneous CD-1 mice. Intelligence 36(6):619–29.Google Scholar
Kolata, S., Light, K., Townsend, D. A., Hale, G., Grossman, H. C. & Matzel, L. D. (2005) Variations in working memory capacity predict individual differences in general learning abilities among genetically diverse mice. Neurobiology of Learning and Memory 84:241–46.Google Scholar
Kolata, S., Light, K., Wass, C. D., Colas-Zelin, D., Roy, D. & Matzel, L. D. (2010) A dopaminergic gene cluster in the prefrontal cortex predicts performance indicative of general intelligence in genetically heterogeneous mice. PLoS One 5(11):e14036.Google Scholar
Kolb, B. & Gibb, R. (2015) Plasticity in the prefrontal cortex of adult rats. Frontiers in Cellular Neuroscience 9:15.Google Scholar
Kolodny, O., Edelman, S. & Lotem, A. (2015) Evolved to adapt: A computational approach to animal innovation and creativity. Current Zoology 61:350–67.Google Scholar
Koops, K., Furuichi, T. & Hashimoto, C. (2015) Chimpanzees and bonobos differ in intrinsic motivation for tool use. Scientific Reports 5:11356.Google Scholar
Korman, J., Voiklis, J. & Malle, B. F. (2015) The social life of cognition. Cognition 135:30–35.CrossRefGoogle ScholarPubMed
Krakauer, E. B. (2005) Development of Aye-Aye (Daubentonia madagascariensis) foraging skills: Independent exploration and social learning. Duke University.Google Scholar
Kuzawa, C. W., Chugani, H. T., Grossman, L. I., Lipovich, L., Muzik, O., Hof, P. R., Wildman, D. E., Sherwood, C. C., Leonard, W. R. & Lange, N. (2014) Metabolic costs and evolutionary implications of human brain development. Proceedings of the National Academy of Sciences USA 111(36):13010–15.Google Scholar
Lefebvre, L. (2013) Brains, innovations, tools and cultural transmission in birds, non-human primates, and fossil hominins. Frontiers in Human Neuroscience 7:245.Google Scholar
Lefebvre, L. (2014) Should neuroecologists separate Tinbergen's four questions? Behavioural Processes 117:92–96.CrossRefGoogle ScholarPubMed
Lefebvre, L., Reader, S. M. & Sol, D. (2004) Brains, innovations and evolution in birds and primates. Brain, Behavior and Evolution 63:233–46.Google Scholar
Lefebvre, L., Reader, S. M. & Sol, D. (2013) Innovating innovation rate and its relationship with brains, ecology and general intelligence. Brain, Behavior and Evolution 81:143–45.Google Scholar
Lefebvre, L., Whittle, P., Lascaris, E. & Finkelstein, A. (1997) Feeding innovations and forebrain size in birds. Animal Behaviour 53:549–60.CrossRefGoogle Scholar
Lesage, E., Navarrete, G. & De Neys, W. (2013) Evolutionary modules and Bayesian facilitation: The role of general cognitive resources. Thinking & Reasoning 19(1):27–53.Google Scholar
Light, K. R., Grossman, Y., Kolata, S., Wass, C. D. & Matzel, L. D. (2011) General learning ability regulates exploration through its influence on rate of habituation. Behavioral Brain Research 223:297–309.Google Scholar
Light, K. R., Kolata, S., Hale, G., Grossman, H. & Matzel, L. D. (2008) Up-regulation of exploratory tendencies does not enhance general learning abilities in juvenile or young-adult outbred mice. Neurobiology of Learning and Memory 90:317–29.Google Scholar
Light, K. R., Kolata, S., Wass, C., Denman-Brice, A., Zagalsky, R. & Matzel, L. D. (2010) Working memory training promotes general cognitive abilities in genetically heterogeneous mice. Current Biology 20:777–82.Google Scholar
Locurto, C. (1997) On the comparative generality of g . In: Advances in cognition and education, vol. 4: Reflections on the concept of intelligence, ed. Tomic, W. & Kigman, J., pp. 79–100. JAI Press.Google Scholar
Locurto, C. & Scanlon, C. (1998) Individual differences and a spatial learning factor in two strains of mice (Mus musculus). Journal of Comparative Psychology 112(4):344–52.Google Scholar
Locurto, C., Benoit, A., Crowley, C. & Miele, A. R. (2006) The structure of individual differences in batteries of rapid acquisition tasks in mice. Journal of Comparative Psychology 120:378–88.Google Scholar
Locurto, C., Fortin, E. & Sullivan, R. (2003) The structure of individual differences in heterogeneous stock mice across problem types and motivational systems. Genes, Brain and Behavior 2(1):40–55.Google Scholar
Lotem, A. & Halpern, J. Y. (2012) Coevolution of learning and data-acquisition mechanisms: A model for cognitive evolution. Philosophical Transactions of the Royal Society of London B: Biological Sciences 367(1603):2686–94.CrossRefGoogle Scholar
Luncz, L. V. & Boesch, C. (2014) Tradition over trend: Neighboring chimpanzee communities maintain differences in cultural behavior despite frequent immigration of adult females. American Journal of Primatology 76(7):649–57.Google Scholar
MacLean, E. L., Hare, B., Nunn, C. L., Addessi, E., Amici, F., Anderson, R. C., Aureli, F., Baker, J. M., Bania, A. E., Barnard, A. M., Boogert, N. J., Brannon, E. M., Bray, E. E., Bray, J., Brent, L. J. N., Burkart, J. M., Call, J., Cantlon, J. F., Cheke, L. G., Clayton, N. S., Delgado, M. M., DiVinventi, L. J., Fujita, K., Herrmann, E., Hiramatsu, C., Jacobs, L. F., Jordan, K. E., Laude, J. R., Leimgruber, K. L., Messer, E. J. E., Moura, A. C. de, A., Ostojic, L., Picard, A., Platt, M. L., Plotnik, J. M., Range, F., Reader, S. M., Reddy, R. B., Sandel, A. A., Santos, L. R., Schumann, K., Seed, A. M., Sewall, K. B., Shaw, R. C., Slocombe, K. E., Yanjie, S., Takimoto, A., Tan, J., Tao, R., van Schaik, C. P., Viranyi, Z., Visalberghi, E., Wade, J. C., Watanabe, A., Widness, J., Young, J. K., Zentall, T. R. & Zhao, Y. (2014) The evolution of self-control. Proceedings of the National Academy of Sciences USA 111:E2140–48.Google Scholar
Macphail, E. M. (1982) Brain and intelligence in vertebrates. Clarendon Press.Google Scholar
Mahon, B. Z. & Cantlon, J. F. (2011) The specialization of function: Cognitive and neural perspectives. Cognitive Neuropsychology 28(3–4):147–55.Google Scholar
Major, J. T., Johnson, W. & Deary, I. J. (2012) Comparing models of intelligence in Project TALENT: The VPR model fits better than the CHC and extended Gf–Gc models. Intelligence 40(6):543–59.Google Scholar
Matsunaga, E., Nambu, S., Oka, M., Tanaka, M., Taoka, M. & Iriki, A. (2015) Identification of tool use acquisition-associated genes in the primate neocortex. Development, Growth & Differentiation 57(6):484–95.Google Scholar
Matzel, L. D., Grossman, H., Light, K., Townsend, D. & Kolata, S. (2008) Age-related declines in general cognitive abilities of Balb/C mice are associated with disparities in working memory, body weight, and general activity. Learning & Memory 15(10):733–46.Google Scholar
Matzel, L. D., Han, Y. R., Grossmann, H., Karnik, M. S., Patel, D., Scott, N., Specht, S. M. & Gandhi, C. C. (2003) Individual differences in the expression of a “general” learning ability in mice. The Journal of Neuroscience 23(16):6423–33.Google Scholar
Matzel, L. D., Light, K. R., Wass, C., Colas-Zelin, D., Denman-Brice, A., Waddel, A. C. & Kolata, S. (2011a) Longitudinal attentional engagement rescues mice from age-related cognitive declines and cognitive inflexibility. Learning and Memory 18(5):345–56.Google Scholar
Matzel, L. D., Sauce-Silva, B. & Wass, C. (2013) The architecture of intelligence: Converging evidence from studies of humans and animals. Current Directions in Psychological Science 22:342–48.Google Scholar
Matzel, L. D., Townsend, D. A., Grossman, H., Han, Y. R., Hale, G., Zappulla, M., Light, K. & Kolata, S. (2006) Exploration in outbred mice covaries with general learning abilities irrespective of stress reactivity, emotionality, and physical attributes. Neurobiology of Learning and Memory 86:228–40.Google Scholar
Matzel, L. D., Wass, C. & Kolata, S. (2011b) Individual differences in animal intelligence: Learning, reasoning, selective attention and inter-species conservation of a cognitive trait. International Journal of Comparative Psychology 24:36–59.Google Scholar
McGrew, K. S. (2009) CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research. Intelligence 37(1):1–10. doi: 10.1016/j.intell.2008.08.004.Google Scholar
Melnick, M. D., Harrison, B. R., Park, S., Bennetto, L. & Tadin, D. (2013) A strong interactive link between sensory discriminations and intelligence. Current Biology 23(11):1013–17.Google Scholar
Meulman, E. J. M., Sanz, C. M., Visalberghi, E. & van Schaik, C. P. (2012) The role of terrestriality in promoting primate technology. Evolutionary Anthropology: Issues, News, and Reviews 21(2):58–68.Google Scholar
Meulman, E. J. M., Seed, A. M. & Mann, J. (2013) If at first you don't succeed … Studies of ontogeny shed light on the cognitive demands of habitual tool use. Philosophical Transactions of the Royal Society of London B: Biological Sciences 368(1630):20130050Google Scholar
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A. & Wager, T. D. (2000) The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology 41(1):49–100.Google Scholar
Moll, H. & Tomasello, M. (2007) Cooperation and human cognition: The Vygotskian intelligence hypothesis. Philosophical Transactions of the Royal Society of London B: Biological Sciences 362(1480):639–48.Google Scholar
Morrison, A. B. & Chein, J. M. (2011) Does working memory training work? The promise and challenges of enhancing cognition by training working memory. Psychonomic Bulletin & Review 18(1):46–60.Google Scholar
Muthukrishna, M. & Henrich, J. (2016) Innovation in the collective brain. Philosophical Transactions of the Royal Society B: Biological Sciences.Google Scholar
Nippak, P. M. & Milgram, N. W. (2005) An investigation of the relationship between response latency across several cognitive tasks in the beagle dog. Progress in Neuro-psychopharmacology & Biological Psychiatry 29(3):371–77.Google Scholar
Nisbett, R. E., Aronson, J., Blair, C., Dickens, W., Flynn, J., Halpern, D. F. & Turkheimer, E. (2012) Intelligence: New findings and theoretical developments. American Psychologist 67(2):130–59.Google Scholar
Ortiz, S. O. (2015) CHC theory of intelligence. In: Handbook of intelligence: Evolutionary theory, historical perspective, and current concepts, ed. Goldstein, S., Princiotta, D. & Naglieri, J.A., pp. 209–27. Springer.Google Scholar
Parker, S. T. (2015) Re-evaluating the extractive foraging hypothesis. New Ideas in Psychology 37:1–12.Google Scholar
Parker, S. T. & Gibson, K. R. (1977) Object manipulation, tool use and sensorimotor intelligence as feeding adaptations in Cebus monkeys and great apes. Journal of Human Evolution 6(7):623–41.Google Scholar
Patton, B. W. & Braithwaite, V. A. (2015) Changing tides: Ecological and historical perspectives on fish cognition. Wiley Interdisciplinary Reviews: Cognitive Science 6(2):159–76.Google Scholar
Pavlicev, M. & Wagner, G. P. (2012) Coming to grips with evolvability. Evolution: Education and Outreach 5(2):231–44.Google Scholar
Pietschnig, J., Penke, L., Wicherts, J. M., Zeiler, M. & Voracek, M. (2015) Meta-analysis of associations between human brain volume and intelligence differences: How strong are they and what do they mean? Neuroscience and Biobehavioral Reviews 57:411–32.Google Scholar
Pinker, S. (2010) The cognitive niche: Coevolution of intelligence, sociality, and language. Proceedings of the National Academy of Sciences USA 107(Supplement 2):8993–99.Google Scholar
Ploeger, A. & Galis, F. (2011) Evo devo and cognitive science. Wiley Interdisciplinary Reviews: Cognitive Science 2:429–40. doi: 10.1002/wcs.137.Google Scholar
Plomin, R. (2001) The genetics of g in human and mouse. Nature Reviews Neuroscience 2(2):136–41.Google Scholar
Pravosudov, V. V. & Roth, T. C. II (2013) Cognitive ecology of food hoarding: The evolution of spatial memory and the hippocampus. Annual Review of Ecology, Evolution, and Systematics 44:173–93.Google Scholar
Prinz, J. J. (2006) Is the mind really modular? In: Contemporary Debates in Cognitive Science, ed. Stainton, R. J., pp. 22–36. Blackwell.Google Scholar
Quartz, S. (2003) Toward a developmental evolutionary psychology: Genes, development and the evolution of cognitive architecture. In: Evolutionary psychology: Alternative approaches, ed. Scher, S. J. & Rauscher, F., pp. 185–210. Kluwer.Google Scholar
Rabipour, S. & Raz, A. (2012) Training the brain: Fact and fad in cognitive and behavioral remediation. Brain and Cognition 79(2):159–79.Google Scholar
Reader, S. M. (2003) Innovation and social learning: Individual variation and brain evolution. Animal Biology 53:147–58.Google Scholar
Reader, S. M., Hager, Y. & Laland, K. N. (2011) The evolution of primate general and cultural intelligence. Philosophical Transactions of the Royal Society B 366:1017–27.Google Scholar
Reader, S. M. & Laland, K. N. (2002) Social intelligence, innovation and enhanced brain size in primates. Proceedings of the National Academy of Sciences USA, 99:4436–41.Google Scholar
Reeve, C. L. (2004) Differential ability antecedents of general and specific dimensions of declarative knowledge: More than g . Intelligence 32(6):621–52.Google Scholar
Reyes-García, V., Pyhälä, A., Díaz-Reviriego, I., Duda, R., Fernández-Llamazares, Á., Gallois, S., Guèze, M. & Napitupulu, L. (2016) Schooling, local knowledge and working memory: A study among three contemporary hunter-gatherer societies. PloS One 11(1):e0145265.Google Scholar
Richerson, P. J., Baldini, R., Bell, A., Demps, K., Frost, K., Hillis, V., Mathew, S., Newton, N., Narr, N., Newson, L., Ross, C., Smaldino, P., Waring, T. & Zefferman, M. (2016) Cultural group selection plays an essential role in explaining human cooperation: A sketch of the evidence. Behavioral and Brain Sciences 39:e30.Google Scholar
Riddell, W. I. & Corl, K. G. (1977) Comparative investigation of the relationship between cerebral indices and learning abilities. Brain, Behavior and Evolution 14:385–98.Google Scholar
Royall, D. R. & Palmer, R. F. (2014) “Executive functions” cannot be distinguished from general intelligence: Two variations on a single theme within a symphony of latent variance. Frontiers in Behavioral Neuroscience 8(369):1–10.Google Scholar
Rumbaugh, D. M. & Washburn, D. A. (2003) Intelligence of apes and other rational beings. Yale University Press.Google Scholar
Saklofske, D. H., van de Vijver, F. J., Oakland, T., Mpofu, E. & Suzuki, L. A. (2014) Intelligence and culture: History and assessment. In: Handbook of intelligence: Evolutionary theory, historical perspective, and current concepts, ed. Goldstein, S., Princiotta, D. & Naglieri, J.A., pp. 341–65. Springer.Google Scholar
Sale, A., Berardi, N. & Maffei, L. (2014) Environment and brain plasticity: Towards an endogenous pharmacotherapy. Physiological Reviews 94(1):189–234.Google Scholar
Samuels, R. (2004) Innateness in cognitive science. Trends in Cognitive Sciences 8(3):136141.CrossRefGoogle ScholarPubMed
Sauce, B., Wass, C., Smith, A., Kwan, S. & Matzel, L. D. (2014) The external-internal loop of interference: Two types of attention and their influence on the learning abilities of mice. Neurobiology of Learning and Memory 116:181–92.Google Scholar
Savage-Rumbaugh, S., Fields, W. M., Segerdahl, P. & Rumbaugh, D. (2005) Culture prefigures cognition in Pan/Homo bonobos. Theoria. Revista de Teoría, Historia y Fundamentos de la Ciencia 20(3):311–28.Google Scholar
Schlosser, G. & Wagner, G. P. (2004) Modularity in development and evolution. University of Chicago Press.Google Scholar
Schubiger, M. N., Kissling, A. & Burkart, J. B. (2016) How task format affects cognitive performance: A memory test with two species of New World monkeys. Animal Behaviour 121:33–39.Google Scholar
Schubiger, M. N., Wüstholz, F. L., Wunder, A. & Burkart, J. M. (2015) High emotional reactivity toward an experimenter affects participation, but not performance, in cognitive tests with common marmosets (Callithrix jacchus). Animal Cognition 18(3):701–12.Google Scholar
Schuppli, C., Isler, K. & van Schaik, C. P. (2012) How to explain the unusually late age at skill competence among humans. Journal of Human Evolution 63(6):843–50.Google Scholar
Schuppli, C., Meulman, E., Forss, S. F., van Noordwijk, M. & van Schaik, C. P. (2016) Observational social learning and socially induced practice of routine skills in wild immature orang-utans. Animal Behaviour 119:87–98.Google Scholar
Shah, P., Happé, F., Sowden, S., Cook, R. & Bird, G. (2015) Orienting toward face-like Stimuli in early childhood. Child Development 86(6):1693–700.Google Scholar
Shaw, R. C., Boogert, N. J., Clayton, N. S. & Burns, K. C. (2015) Wild psychometrics: Evidence for “general” cognitive performance in wild New Zealand robins, Petroica longipes. Animal Behaviour 109:101–11. doi: 10.1016/j.anbehav.2015.08.001.Google Scholar
Shepherd, S. V. (2010) Following gaze: Gaze-following behavior as a window into social cognition. Frontiers in Integrative Neuroscience 4:5.Google Scholar
Sheppard, L. D. & Vernon, P. A. (2008) Intelligence and speed of information-processing: A review of 50 years of research. Personality and Individual Differences 44(3):535–51.Google Scholar
Sherry, D. F. (2006) Neuroecology. Annual Review of Psychology 57:167–97.Google Scholar
Shettleworth, S. J. (2012a) Darwin, Tinbergen, and the evolution of comparative cognition. In: The Oxford handbook of comparative evolutionary psychology, ed. Vonk, J. & Shackelford, T. K., pp. 529–46. Oxford University Press.Google Scholar
Shettleworth, S. J. (2012b) Modularity, comparative cognition and human uniqueness. Philosophical Transactions of the Royal Society B 367(1603):2794–802.Google Scholar
Shipstead, Z., Redick, T. & Engle, R. W. (2012) Is working memory training effective? Psychological Bulletin 138(4):628.Google Scholar
Shultz, S. & Dunbar, R. I. M. (2006) Both social and ecological factors predict ungulate brain size. Proceedings of the Royal Society B: Biological Sciences 273(1583):207–15.Google Scholar
Shumway, C. A. (2008) Habitat complexity, brain, and behavior. Brain, Behavior and Evolution 72(2):123–34.Google Scholar
Sol, D. (2009b) The cognitive-buffer hypothesis for the evolution of large brains. In: Cognitive. Ecology II, ed. Dukas, R. & Ratcliffe, J. M. pp. 111–34. University of Chicago Press.Google Scholar
Sol, D., Bacher, S., Reader, S. M. & Lefebvre, L. (2008) Brain size predicts the success of mammal species introduced into novel environments. The American Naturalist 172(S1):S63–71.Google Scholar
Sol, D., Duncan, R. P., Blackburn, T. M., Cassey, P. & Lefebvre, L. (2005) Big brains, enhanced cognition, and response of birds to novel environments. Proceedings of the National Academy of Sciences USA 102(15):5460–65.Google Scholar
Spearman, C. (1927) The abilities of man. Macmillan. xxii 415pp.Google Scholar
Spelke, E. S. & Kinzler, K. D. (2007) Core knowledge. Developmental Science 10(1):89–96.Google Scholar
Sperber, D. (2001) In defense of massive modularity. In: Language, brain and cognitive development: Essays in honor of Jacques Mehler, ed. Dupoux, E., pp. 47–57. MIT Press.Google Scholar
Sternberg, S. (2011) Modular processes in mind and brain. Cognitive Neuropsychology 28(3–4):156–208.Google Scholar
Stevens, J. P. (2012) Applied multivariate statistics for the social sciences. Routledge.Google Scholar
Strasser, A. & Burkart, J. M. (2012) Can we measure brain efficiency? An empirical test with common marmosets (Callithrix jacchus). Brain, Behavior and Evolution 80(1):26–40.Google Scholar
Tapp, P. D., Siwak, C. T., Estrada, J., Head, E., Muggenburg, B. A., Cotman, C. W. & Milgram, N. W. (2003) Size and reversal learning in the beagle dog as a measure of executive function and inhibitory control in aging. Learning & Memory 10(1):64–73.Google Scholar
Teubert, M., Vierhaus, M. & Lohaus, A. (2011) Frühkindliche Untersuchungsmethoden zur Intelligenzprognostik. Psychologische Rundschau 62(2):70–77.Google Scholar
Thorsen, C., Gustafsson, J. E. & Cliffordson, C. (2014) The influence of fluid and crystallized intelligence on the development of knowledge and skills. British Journal of Educational Psychology 84(4):556–70.Google Scholar
Tinbergen, N. (1963) On aims and methods of ethology. Zeitschrift für Tierpsychologie 20(4):410–33.Google Scholar
Toates, F. (2005) Evolutionary psychology–towards a more integrative model. Biology and Philosophy 20(2–3):305–28.Google Scholar
Tomasello, M. (1999) The cultural origins of human cognition. Harvard University Press.Google Scholar
Tomasello, M. & Call, J. (1997) Primate cognition. Oxford University Press.Google Scholar
van de Waal, E., Borgeaud, C. & Whiten, A. (2013) Potent social learning and conformity shape a wild primate's foraging decisions. Science 340(6131):483–85.Google Scholar
van der Maas, H. L. J., Dolan, C. V, Grasman, R. P. P. P., Wicherts, J. M., Huizenga, H. M. & Raijmakers, M. E. J. (2006) A dynamical model of general intelligence: The positive manifold of intelligence by mutualism. Psychological Review 113(4):842–61. doi: 10.1037/0033-295X.113.4.842.Google Scholar
van Schaik, C. P. (2016) The primate origins of human nature. Wiley-Blackwell.Google Scholar
van Schaik, C. P., Ancrenaz, M., Borgen, G., Galdikas, B., Knott, C. D., Singleton, I., Suzuki, A., Suci, S. U. & Merrill, M. (2003) Orangutan cultures and the evolution of material culture. Science 299:102–105.Google Scholar
van Schaik, C. P. & Burkart, J. M. (2011) Social learning and evolution: The cultural intelligence hypothesis. Philosophical Transactions of the Royal Society B: Biological Sciences 366(1567):1008–16.Google Scholar
van Schaik, C. P., Burkart, J. M., Damerius, L., Forss, S. I. F., Koops, K., van Noordwijk, M. A. & Schuppli, C. (2016) The reluctant innovator: Orangutans and the phylogeny of creativity. Philosophical Transactions B 371(1690):20150183.Google Scholar
van Schaik, C. P., Deaner, R. O. & Merrill, M. Y. (1999) The conditions for tool use in primates: Implications for the evolution of material culture. Journal of Human Evolution 36:719–41.Google Scholar
van Schaik, C. P., Graber, S. M., Schuppli, C. & Burkart, J. M. (2017) The ecology of social learning in animals and its link with intelligence. Spanish Journal of Comparative Psychology. Published online. doi: https://doi.org/10.1017/sjp.2016.100.Google Scholar
van Schaik, C. P., Isler, K. & Burkart, J. M. (2012) Explaining brain size variation: From social to cultural brain. Trends in Cognitive Sciences 16:277–84.Google Scholar
van Woerden, J. T., van Schaik, C. P. & Isler, K. (2010) Effects of seasonality on brain size evolution: Evidence from strepsirrhine primates. The American Naturalist 176(6):758–67.Google Scholar
van Woerden, J. T., van Schaik, C. P. & Isler, K. (2014) Brief communication: Seasonality of diet composition is related to brain size in New World Monkeys. American Journal of Physical Anthropology 154(4):628–32.Google Scholar
van Woerden, J. T., Willems, E. P., van Schaik, C. P. & Isler, K. (2012) Large brains buffer energetic effects of seasonal habitats in catarrhine primates. Evolution 66(1):191–99.Google Scholar
Voelkl, B., Schrauf, C. & Huber, L. (2006) Social contact influences the response of infant marmosets towards novel food. Animal Behaviour 72:365–72.Google Scholar
Wass, C., Denman-Brice, A., Light, K. R., Kolata, S., Smith, A. M. & Matzel, L. D. (2012) Covariation of learning and “reasoning” abilities in mice: Evolutionary conservation of the operations of intelligence. Journal of Experimental Psychology: Animal Behavior Processes 38(2):109–24.Google Scholar
Whiten, A. & van Schaik, C. P. (2007) The evolution of animal “cultures” and social intelligence. Philosophical Transactions of the Royal Society B: Biological Sciences 362(1480):603–20.Google Scholar
Woodley of Menie, M. A., Fernandes, H. B. F. & Hopkins, W. D. (2015) The more g-loaded, the more heritable, evolvable, and phenotypically variable: Homology with humans in chimpanzee cognitive abilities. Intelligence 50:159–63. Available at: http://doi.org/10.1016/j.intell.2015.04.002.Google Scholar
Wooldridge, D. E. (1968) Mechanical man: The physical basis of intelligent life. McGraw-Hill.Google Scholar
Yamamoto, M. E., Domeniconi, C. & Box, H. (2004) Sex differences in common marmosets (Callithrix jacchus) in response to an unfamiliar food task. Primates 45:249–54.Google Scholar
Yoerg, S. I. (2001) Clever as a fox. Animal intelligence and what it can teach us about ourselves. Bloomsbury.Google Scholar