Archive for the ‘Anthropology’ Category

Stiffness and plasticity in social learning strategies. An idea of interpretation.

In Anthropology, Di Paolo, Philosophy of Cognitive Sciences on March 19, 2013 at 6:11 PM

Several useful behaviours that an individual must apprehend for growing up require the presence of “friendly” co-specifics in a social context. In primates, various strategies of Social Learning are present, mostly relying on an individual’s ability to solve problems by trial-and-error, but some of apes are able to show imitative learning, considered pivotal for cumulative culture. Chimpanzees have been recognized, even if not by all the scholars, able to switch between an individual, plastic but less accurate method of learning (both a trial-and-error strategy properly and emulative learning), and true imitation, depending on the quantity of relevant information at disposal in a causality task (Whiten et al, 2005; 2009). Rather, human children are incredibly stiff in copying adults, doing it not only when it is useful, but also when it is wasteful, disadvantageous and harmful. Later in their development they become able to choose more plastic and individual strategies. Some authors (Tomasello in primis, e.g. Tomasello, 2005; 2009) have pointed to this fully developed imitative behaviour as the main cause of human uniqueness, but this idea seems quite strange considering the vast amount of data we have at disposal on non-human culture and the use of imitation by some enculturated apes (e.g. McGrew, 2004; Byrne, 2007; Whiten, 2011; Tomasello & Call,2004; Call, 2011); . How is it possible, indeed, that these latter (even if, as usually recognized, not all captive apes) are able to imitate, if imitation appeared suddenly in humans, as a human adaptation, founding our “overbearing” life-style? Data on human-raised/enculturated chimpanzees demonstrate that imitation is something that can be exhibited by other species as well, meaning that it is something already present in the repertoire of these other species (Call & Tomasello, 1996; Bering, 2004; Tomasello & Call, 2004; Call, 2011). Consequently we are allowed to think that somehow imitation developed at least before the separation between hominid lineages and chimpanzee/bonobo ancestors. Imitative behaviour is usually displayed by enculturated/human raised apes  and that because in the cultural context it seems more useful, or only more probable. However then, another interesting question comes up and it concerns the use of imitation by human children, that they do pedantically at least till they start to speak fluently. Probably, an economical explanation could be that humans only re-use same learning strategies inherited from their ancestors, shared with their evolutionary relatives, but they do it differently. Together with social explanations, the preponderance of imitative learning in humans is probably due to the open environment in which hominins evolved: in this environment, in fact, reaching food was more difficult than in forests. Because of this difficulty, probably copying faithfully successful actions was better than trying to reach the same goal with an individual strategy. And they did so again and again. Therefore, the rigid use of imitation by human children may be derived exactly from that: humans become very good to firstly learn necessary information by means of imitation, and only later and over this ground, each individual can add something personal, using a trial-and-error process. Cumulative culture, so, could not depend on a specific learning strategy, but more on differences in using already existing strategies, spreading them over different developmental steps.

Laura Desirée Di Paolo

Call, J. (2011) How Artificial Communication Affects the Communication and Cognition of the Great Apes. Mind and Language, 26, 1: 1-20.

Call, J. & Tomasello, M. (1996) The effect of humans on the cognitive development of apes. In A.E. Russon, K.A. Bard & S.T. Parker (Eds). Reaching into thought (pp. 371-403); Cambridge: Cambridge University Press.

Bering, J. (2004) A critical review of the “enculturation hypothesis”: the effects of human rearing on great ape social cognition; Animal Cognition, 7, 4: 201-212.

Byrne, R W. (2007) Culture in great apes: Using intricate complexity in feeding skills to trace the evolutionary origin of human technical prowess. Phil. Trans. R. Soc. B,. 362: 577-585

McGrew,W.C. (2004) The Cultured Chimpanzee: Reflections on Cultural Primatology. Cambridge University Press, 248 pp.

Tomasello, M. & Call, J. (1997) Primate Cognition. New York-Oxford: Oxford University Press.

                                           (2004) The role of humans in the cognitive development of apes revisited. Animal Cognition, 7:213-215.

Tomasello, M., Savage-Rumbaugh, S., Kruger, A.C. (1993) Imitative learning of actions on objects by children, chimpanzees, and encultured chimpanzees. Child Development, 64: 1688-1705.

Whiten, A. (2005). Chimpanzee cultures. In J. Caldecott. & L. Miles (Eds) The World Atlas of Great Apes and their Conservation (United Nations Environment Programme). Berkeley & Los Angeles: University of California Press.

                         (2005). The second inheritance system of chimpanzees and humans. Nature, 437, 52-55.


What is cultural complexity?

In Anthropology, Vegvari on February 11, 2013 at 11:55 AM

Carolin Vegvari

Cultural anthropologists have long noted and described differences in the level of cultural complexity of different human groups. The first discussions about cultural systems and complexity were centred on a notion of linear progress from simple to more complex cultural systems considering modern Western cultures as the furthest advanced (see e.g. Tylor 1920). Although modern anthropologists have realised nowadays that this simplistic notion of cultural complexity discredits the adaptational value of some of the most long-lived cultural systems of human history, it is still the prevailing one in much of  the research on human cultural evolution today. To gain a less ideologically motivated and more analytically useful view of these concepts, we first have to define what we mean by “culture” and by “complexity”.

In the Encyclopedia of Evolution, Mitchell and Newman define a complex system as “a group or organization which is made up of many interacting parts”. If we then accept the definition of culture as socially transmitted information (Boyd & Richerson 2005), this means that the complexity of a cultural system lies somehow in the number of items of information that it contains and the number of interactions among these items. Depending on our interests, we may stress different typologies of information and different sets of interactions: cultural complexity becomes a “multidimensional variable”.

Without taking the analogy too far, a cultural system can be compared with the code base of a computer game. The code base of a game holds its rule set or informational content. A more complex game has a bigger code base, because more information needs to be stored for each possible decision-making point, game assets and interactions among subsystems and objects within the game. The more different agents or players there are in a game, the more different variables each agent owns, and the higher the number of possible interactions between them is, the more complex the code base will become. Equally, a more complex game-environment will increase the code base, because there are more possible interactions between the players and their environment. Similarly, human agents in cultural systems hold information about tool-use, knowledge about their biotic and abiotic environment and also about social interaction rules. All these items of information together constitute a cultural system and its complexity.

Obviously, the game code itself will be hidden from the human player (= observer), and only its effects will become apparent during the game. The same relationship applies to individual cultural traits, which we can define as individual pieces of cultural information, and the properties of cultural systems that we can observe. We may consider observable cultural properties and artefacts as the product of modular recipes of cultural traits (Mesoudi & O’Brien 2008). Therefore, when asking questions about cultural complexity, it is important to operationalise the concept, even if this means that we will lose some aspects of cultural complexity for the purpose of our analysis.

For example, we can look at the technological complexity of different cultural groups. Technology, as a prominent part of material culture, is relatively easy to observe. Measures of technological complexity vary, but mostly they take into account the number of different tool types and/or the number of distinct subunits of each type (the latter are also referred to as technounits, after Oswalt 1976). Thus, we can assess the number of different parts at different scales of a technological system and the number of functional interactions among these parts (in the case of technounits). Culture, however, is not restricted to technology or even material culture. The number of levels of social stratification and the degree of social heterogeneity both represent different aspects of cultural complexity (McGuire 1983). It may also be reflected in the number of different cultural roles which an individual can adopt within a community.

Once we have clarified what we mean by cultural complexity and what aspects of cultural complexity we are investigating, we can start asking more interesting questions, such as the following:

Why are some human cultures more complex than others? In what aspects are some human cultures more complex than others? How is complexity at the individual level (e.g. the number of cultural traits, rules and relationships held by individuals) related to the complexity at a higher collective level (e.g. the total set of cultural traits or rules in a population, the levels of social hierarchy, or the number or different relationships between individuals)? In how far is cultural complexity affected by chance effects, such as fluctuations in population size? And in how far is the amount of complexity found in a specific cultural community an adaptive response to social and environmental circumstances?





Boyd, R. & Richerson, P. 2005. The origin and evolution of cultures. Oxford University Press, Oxford.

McGuire, R. 1983. Breaking down cultural complexity: inequality and heterogeneity. Advances in Archaeological Method and Theory 6: 91-142.

Mesoudi, A. & O’Brien, M. J. 2008. The learning and transmission of hierarchical cultural recipies. Biological Theory 3: 63–72.

Mitchel, M. & Newman, M. 2002. Complex systems theory and evolution. In ed. Pagel, M. Encyclopedia of Evolution. Oxford University Press, New York.

Oswalt, W. H. 1976 An anthropological analysis of food-getting technology. Wiley, New York.

Tylor, E.B. 1920. Primitive Culture: Researches into the Development of Mythology, Philosophy, Religion, Language, Art, and Custom. Murray, London.


Networks, updates and real people. Are theoretical studies saying the right thing?

In Anthropology, d'Almeida on December 6, 2012 at 4:44 PM

André F. d’Almeida

Evolutionary Game Theory (EGT) has given several accounts on how cooperation is maintained by a population’s network structure (Ohtsuki, H., et al., 2006). These studies are based on several assumptions, namely that individuals only take into account benefits and costs and that they decide to update their strategy by comparing pay-offs with random members of the population (Roca, C.P. et al., 2009). Up until now, experimental game theory had only been able to study interactions in small networks, a world away from the thousands of nodes networks used in theoretical research. This proved difficult to accurately test theoretical models experimentally. Recently, a study where 1229 subjects play a Prisoner’s Dilemma (PD) game simultaneously (Gracia-Lázaro, C., et al., 2012) demonstrated that there are no differences in cooperation levels in homogeneous vs. heterogeneous networks. Unlike what was suggested in a Public Goods Game context (Santos, F.C. et al., 2008), where network diversity increased cooperation. Furthermore, individuals did not compare pay-offs with their neighbours but only accounted for their actions in order to make decisions, meaning that they acted reciprocally.Does this mean theoretical studies are not saying the right things? Yes and no. Yes, because theoretical studies make plenty assumptions regarding human behaviour, over-simplifying it to the level of particles with only two choices and strict rules on how individuals update strategies. No, because theoretical research only provides guidelines on the evolution of cooperation, of ultimate causation alternatives of a behaviour. It is the experimenters who must test which alternatives are proximally exhibited by real individuals, both human and non-human and provide guidelines for better theoretical models, mainly how people decide and react to social dilemmas.



Ohtsuki, H., et al. (2006) A simple rule for the evolution of cooperation on graphs and social networks. Nature, 441, 7092: 502-505. 

Roca, C.P., J.A. Cuesta, and A. Sánchez (2009) Evolutionary game theory: Temporal and spatialeffects beyond replicator dynamics. Physics of Life Reviews; 6,4: 208-249. 

Gracia-Lázaro, C., et al. (2012) Heterogeneous networks do not promote cooperation when humans play a Prisoner‚Äôs Dilemma. Proceedings of the National Academy of Sciences; 109, 32: 12922-12926. 

 Santos, F.C., M.D. Santos, and J.M. Pacheco (2008) Social diversity promotes the emergence of cooperation in public goods games. Nature; 454, 7201: 213-216.

Shaping language faculty.

In Anthropology, Di Vincenzo, Philosophy of Cognitive Sciences on November 26, 2012 at 10:04 PM

Fabio di Vincenzo

Language and social learning appear to be closely related biological phenomena. The cortical areas of the left hemisphere that lies around the fissure of Sylvius are related to the phenomenon of social learning both in man and apes. This cortical areas are the same devoted to the faculty of language in modern humans. Furthermore social learning exhibit a functional coupling of both semantic and syntactic aspects that pre-date the origin of language itself. The extensive and fast-growing of the left perisylvian cortical areas since early Homo more than 2 milions years ago, can be properly linked to the individual advantage to possess a much more efficient and accurate non-verbal system for an early learning by imitation of the know-how and technical skills to have access to food resources, including nutrients essential to support the development of the brain not otherwise available. From a Darwinian point of view, the increased capabilities of social learning in Plio-Pleistocene hominins provides the key adaptations for the further evolution of language.



Di Vincenzo,F. (2011). Toward a neuro-archaeology of the faculty of language. Atti del IV convegno 2010 del CODISCO, 255-266

Di Vincenzo, F.& Manzi, G. (2012). MicroMega. Almanacco della Scienza 1, 2012, 147-167