Cultures in chimpanzees

Whiten, Andrew; Goodall, Jane; McGrew, William C.; Nishida, Toshisada; Reynolds, Vernon; Sugiyama, Yukimaru; Tutin, Caroline E. G.; Wrangham, Richard W.; Boesch, Christophe

doi:10.1038/21415

Cited by 2,010 publications

(1,218 citation statements)

References 21 publications

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“…In the world of humans, obvious candidates include financial investments or a communication or entertainment technology whose utility grows with more users. In animal culture we might see this be the case, as in chimpanzee tool culture, with our model implying that social learning among even a few or several different options could bring about a rugged fitness landscape and hence multiple regions of different cultural traditions (e.g., Whiten et al, 1999 …”

Section: Resultsmentioning

confidence: 95%

Fitness landscapes among many options under social influence

Caiado

Brock

Bentley

et al. 2016

Journal of Theoretical Biology

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Additional information:Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractWe use discrete-choice theory to construct a fitness-landscape function for a bi-axial decisionmaking map that plots the magnitude of social influence in the learning process against the costs and payoffs of decisions. Specifically, we use econometric and statistical methods to estimate not only the fitness function but also movements along the map axes. In terms of a Sewell Wright fitness-landscape function, cultural learning represents a novel problem in that an optimal decision depends not only on intrinsic utility of the decision/behavior but also on transparency of costs and benefits, the degree of social versus individual learning, and the relative popularity of each possible choice in a population. This recursive relationship means that multiple equilibria can exist. To search for these we employ a hillclimbing algorithm that leads to the expected values of optimal decisions, which we define as peaks on the fitness landscape. We illustrate how estimation of a measure of transparency, a measure of social influence, and the associated fitness landscape can be accomplished using panel data sets.

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Section: Resultsmentioning

confidence: 95%

Fitness landscapes among many options under social influence

Caiado

Brock

Bentley

et al. 2016

Journal of Theoretical Biology

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“…Most work on how cultural factors influence behavior has focused on the spread of species-atypical behavior patterns within a population (Boyd & Richerson, 1985;Galef, 1990;Rendell & Whitehead, 2001;Whiten et al, 1999). This is done because focusing on species-atypical behavior reduces the likelihood that the behavior of interest may have spread without being learned socially.…”

Section: Discussionmentioning

confidence: 99%

Constructing culture in cowbirds (Molothrus ater).

White¹,

Gros‐Louis²,

King³

et al. 2007

Journal of Comparative Psychology

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In past work, the authors produced divergent patterns of courtship and communication in juvenile male cowbirds (Molothrus ater) by providing them with different social experiences during their 1st year. Here the authors determined whether these different social patterns could be transmitted to new generations of juvenile males. In Experiment 1, the authors exposed groups of juveniles to adult males who differed in the amount of male-male competition they produced. In Experiment 2, they gave groups of juveniles either social access to adult males or only visual and acoustic access to those males. In both experiments, juvenile males developed patterns of courtship and competition similar to those expressed by the adult males with whom they had social contact. The juveniles never had the opportunity to observe some of the adults' behaviors that they came to replicate. This suggests that the role of the adults was to establish the social structure in the groups, modifying juveniles' early social interactions. Juveniles were then "cultured" within these different learning environments, constructing social behavior similar to the adult males' behavior in their 1st year.

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“…This study of cultural change has advanced rapidly in recent years, part of a more general scientific focus on cultural evolution (Boyd & Richerson, 1996;Fitch, 2011c;Laland et al, 2010;Mesoudi et al, 2004). This research has recently taken a strong empirical turn both in humans (Kirby et al, 2008;Morgan et al, 2015;Smith & Kirby, 2008) and animals (Fehér, 2016;Fehér, Wang, Saar, Mitra, & Tchernichovski, 2009;Whiten et al, 1999). Because the term Blanguage evolution^can be interpreted either in terms of biological evolution of the language faculty or the cultural evolution of specific languages, Jim Hurford introduced the useful term Bglossogeny^to denote the latter specifically (Hurford, 1990).…”

Section: Cultural Aspects Of Language Evolutionmentioning

confidence: 99%

Empirical approaches to the study of language evolution

2017

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The study of language evolution, and human cognitive evolution more generally, has often been ridiculed as unscientific, but in fact it differs little from many other disciplines that investigate past events, such as geology or cosmology. Well-crafted models of language evolution make numerous testable hypotheses, and if the principles of strong inference (simultaneous testing of multiple plausible hypotheses) are adopted, there is an increasing amount of relevant data allowing empirical evaluation of such models. The articles in this special issue provide a concise overview of current models of language evolution, emphasizing the testable predictions that they make, along with overviews of the many sources of data available to test them (emphasizing comparative, neural, and genetic data). The key challenge facing the study of language evolution is not a lack of data, but rather a weak commitment to hypothesistesting approaches and strong inference, exacerbated by the broad and highly interdisciplinary nature of the relevant data. This introduction offers an overview of the field, and a summary of what needed to evolve to provide our species with language-ready brains. It then briefly discusses different contemporary models of language evolution, followed by an overview of different sources of data to test these models. I conclude with my own multistage model of how different components of language could have evolved.

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Cultures in chimpanzees

Cited by 2,010 publications

References 21 publications

Fitness landscapes among many options under social influence

Fitness landscapes among many options under social influence

Constructing culture in cowbirds (Molothrus ater).

Empirical approaches to the study of language evolution

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