Vocal responsiveness in male wild chimpanzees: implications for the evolution of language

Several captive chimpanzees and bonobos have learned to use symbols and to comprehend syntax. Thus, compared with other nonhumans, these animals appear to have unusual cognitive powers that can be recruited for communicative behavior. This raises the possibility that wild chimpanzee vocal communication is more complex than heretofore demonstrated. To examine this possibility, I investigated whether wild chimpanzee vocal exchanges exhibit uniquely human conversational attributes. The results indicate that wild chimpanzees vocalize at low rates, tend not to respond to calls that they hear, and, when they do respond, tend to give calls that are similar to the ones they have heard. Thus, chimpanzee vocal interactions resemble those of other primate species, and show no special similarity to human conversations. The results support the view that we need to explore cognitive and social continuities and discontinuities with nonhuman primates to understand the origin and evolution of language, but also emphasize the need for fine-grained analyses of wild chimpanzee vocal interactions.     

Cooperation and the evolution of intelligence

The high levels of intelligence seen in humans, other primates, certain cetaceans and birds remain a major puzzle for evolutionary biologists, anthropologists and psychologists. It has long been held that social interactions provide the selection pressures necessary for the evolution of advanced cognitive abilities (the 'social intelligence hypothesis'), and in recent years decision-making in the context of cooperative social interactions has been conjectured to be of particular importance. Here we use an artificial neural network model to show that selection for efficient decision-making in cooperative dilemmas can give rise to selection pressures for greater cognitive abilities, and that intelligent strategies can themselves select for greater intelligence, leading to a Machiavellian arms race. Our results provide mechanistic support for the social intelligence hypothesis, highlight the potential importance of cooperative behaviour in the evolution of intelligence and may help us to explain the distribution of cooperation with intelligence across taxa.     

Big brains, small worlds: material culture and the evolution of the mind

New developments in neuroimaging have demonstrated that the basic capacities underpinning human social skills are shared by our closest extant primate relatives. The challenge for archaeologists is to explain how complex human societies evolved from this shared pattern of face-to-face social interaction. We argue that a key process was the gradual incorporation of material culture into social networks over the course of hominin evolution. Here we use three long-term processes in hominin evolution-encephalization, the global human diaspora and sedentism/agriculture-to illustrate how the cultural transmission of material culture allowed the 'scaling up' of face-to-face social interactions to the global societies known today. We conclude that future research by neuroimagers and archaeologists will need to investigate the cognitive mechanisms behind human engagement with material culture as well as other persons.     

Group Size Predicts Social but Not Nonsocial Cognition in Lemurs

The social intelligence hypothesis suggests that living in large social networks was the primary selective pressure for the evolution of complex cognition in primates. This hypothesis is supported by comparative studies demonstrating a positive relationship between social group size and relative brain size across primates. However, the relationship between brain size and cognition remains equivocal. Moreover, there have been no experimental studies directly testing the association between group size and cognition across primates. We tested the social intelligence hypothesis by comparing 6 primate species (total N = 96) characterized by different group sizes on two cognitive tasks. Here, we show that a species’ typical social group size predicts performance on cognitive measures of social cognition, but not a nonsocial measure of inhibitory control. We also show that a species’ mean brain size (in absolute or relative terms) does not predict performance on either task in these species. These data provide evidence for a relationship between group size and social cognition in primates, and reveal the potential for cognitive evolution without concomitant changes in brain size. Furthermore our results underscore the need for more empirical studies of animal cognition, which have the power to reveal species differences in cognition not detectable by proxy variables, such as brain size.     

Communicative roots of complex sociality and cognition

Mammals living in more complex social groups typically have large brains for their body size and many researchers have proposed that the primary driver of the increase in brain size through primate and hominin evolution was the selection pressures associated with sociality. Many mammals, and especially primates, use flexible signals that show a high degree of voluntary control and these signals may play an important role in forming and maintaining social relationships between group members. However, the specific role that cognitive skills play in this complex communication, and how in turn this relates to sociality, is still unclear. The hypothesis for the communicative roots of complex sociality and cognition posits that cognitive demands behind the communication needed to form and maintain bonded social relationships in complex social settings drives the link between brain size and sociality. We review the evidence in support of this hypothesis and why key features of cognitively complex communication such as intentionality and referentiality should be more effective in forming and maintaining bonded relationships as compared with less cognitively complex communication. Exploring the link between cognition, communication and sociality provides insights into how increasing flexibility in communication can facilitate the emergence of social systems characterised by bonded social relationships, such as those found in non‐human primates and humans. To move the field forward and carry out both within‐ and among‐species comparisons, we advocate the use of social network analysis, which provides a novel way to describe and compare social structure. Using this approach can lead to a new, systematic way of examining social and communicative complexity across species, something that is lacking in current comparative studies of social structure.     

Does the Type of Event Influence How User Interactions Evolve on Twitter?

The number of people using on-line social networks as a new way of communication is continually increasing. The messages that a user writes in these networks and his/her interactions with other users leave a digital trace that is recorded. Thanks to this fact and the use of network theory, the analysis of messages, user interactions, and the complex structures that emerge is greatly facilitated. In addition, information generated in on-line social networks is labeled temporarily, which makes it possible to go a step further analyzing the dynamics of the interaction patterns. In this article, we present an analysis of the evolution of user interactions that take place in television, socio-political, conference, and keynote events on Twitter. Interactions have been modeled as networks that are annotated with the time markers. We study changes in the structural properties at both the network level and the node level. As a result of this analysis, we have detected patterns of network evolution and common structural features as well as differences among the events.     

From social network (centralized vs. decentralized) to collective decision-making (unshared vs. shared consensus)

Relationships we have with our friends, family, or colleagues influence our personal decisions, as well as decisions we make together with others. As in human beings, despotism and egalitarian societies seem to also exist in animals. While studies have shown that social networks constrain many phenomena from amoebae to primates, we still do not know how consensus emerges from the properties of social networks in many biological systems. We created artificial social networks that represent the continuum from centralized to decentralized organization and used an agent-based model to make predictions about the patterns of consensus and collective movements we observed according to the social network. These theoretical results showed that different social networks and especially contrasted ones--star network vs. equal network--led to totally different patterns. Our model showed that, by moving from a centralized network to a decentralized one, the central individual seemed to lose its leadership in the collective movement's decisions. We, therefore, showed a link between the type of social network and the resulting consensus. By comparing our theoretical data with data on five groups of primates, we confirmed that this relationship between social network and consensus also appears to exist in animal societies.     

Anatomical Network Analysis Shows Decoupling of Modular Lability and Complexity in the Evolution of the Primate Skull

Modularity and complexity go hand in hand in the evolution of the skull of primates. Because analyses of these two parameters often use different approaches, we do not know yet how modularity evolves within, or as a consequence of, an also-evolving complex organization. Here we use a novel network theory-based approach (Anatomical Network Analysis) to assess how the organization of skull bones constrains the co-evolution of modularity and complexity among primates. We used the pattern of bone contacts modeled as networks to identify connectivity modules and quantify morphological complexity. We analyzed whether modularity and complexity evolved coordinately in the skull of primates. Specifically, we tested Herbert Simon’s general theory of near-decomposability, which states that modularity promotes the evolution of complexity. We found that the skulls of extant primates divide into one conserved cranial module and up to three labile facial modules, whose composition varies among primates. Despite changes in modularity, statistical analyses reject a positive feedback between modularity and complexity. Our results suggest a decoupling of complexity and modularity that translates to varying levels of constraint on the morphological evolvability of the primate skull. This study has methodological and conceptual implications for grasping the constraints that underlie the developmental and functional integration of the skull of humans and other primates.     

Baboon (Papio anubis) social complexity--a network approach

Although many studies have analyzed the causes and consequences of social relationships, few studies have explicitly assessed how measures of social relationships are affected by the choice of behaviors used to quantify them. The use of many behaviors to measure social relationships in primates has long been advocated, but it was analytically difficult to implement this framework into primatological work. However, recent advances in social network analysis (SNA) now allow the comparison of multiple networks created from different behaviors. Here we use our database of baboon social behavior (Papio anubis, Gashaka Gumti National Park, Nigeria) to investigate (i) to what extent social networks created from different behaviors overlap, (ii) to what extent individuals occupy similar social positions in these networks and (iii) how sex affects social network position in this population of baboons. We used data on grooming, aggression, displacement, mounting and presenting, which were collected over a 15-month period. We calculated network parameters separately for each behavior. Networks based on displacement, mounting and presenting were very similar to each other, whereas grooming and aggression networks differed both from each other and from mounting, displacement and presenting networks. Overall, individual network positions were strongly affected by sex. Individuals central in one network tended to be central in most other networks as well, whereas other measures such as clustering coefficient were found to vary depending on the behavior analyzed. Thus, our results suggest that a baboon's social environment is best described by a multiplex network based on affiliative, aggressive and sexual behavior. Modern SNA provides a number of useful tools that will help us to better understand animals' social environment. We also discuss potential caveats related to their use.     

The function and mechanism of vocal accommodation in humans and other primates

The study of non‐human animals, in particular primates, can provide essential insights into language evolution. A critical element of language is vocal production learning, i.e. learning how to produce calls. In contrast to other lineages such as songbirds, vocal production learning of completely new signals is strikingly rare in non‐human primates. An increasing body of research, however, suggests that various species of non‐human primates engage in vocal accommodation and adjust the structure of their calls in response to environmental noise or conspecific vocalizations. To date it is unclear what role vocal accommodation may have played in language evolution, in particular because it summarizes a variety of heterogeneous phenomena which are potentially achieved by different mechanisms. In contrast to non‐human primates, accommodation research in humans has a long tradition in psychology and linguistics. Based on theoretical models from these research traditions, we provide a new framework which allows comparing instances of accommodation across species, and studying them according to their underlying mechanism and ultimate biological function. We found that at the mechanistic level, many cases of accommodation can be explained with an automatic perception–production link, but some instances arguably require higher levels of vocal control. Functionally, both human and non‐human primates use social accommodation to signal social closeness or social distance to a partner or social group. Together, this indicates that not only some vocal control, but also the communicative function of vocal accommodation to signal social closeness and distance must have evolved prior to the emergence of language, rather than being the result of it. Vocal accommodation as found in other primates has thus endowed our ancestors with pre‐adaptations that may have paved the way for language evolution.     

Using multilayer network analysis to explore the temporal dynamics of collective behavior

Social organisms often show collective behaviors such as group foraging or movement.Collective behaviors can emerge from interactions between group members and may depend on the behavior of key individuals.When social interactions change over time,collective behaviors may change because these behaviors emerge from interactions among individuals.Despite the importance of,and growing interest in,the temporal dynamics of social interactions,it is not clear how to quantify changes in interactions over time or measure their stability.Furthermore,the temporal scale at which we should observe changes in social networks to detect biologically meaningful changes is not always apparent.Here we use multilayer network analysis to quantify temporal dynamics of social networks of the social spider Stegodyphus dumicola and determine how these dynamics relate to individual and group behaviors.We found that social interactions changed over time at a constant rate.Variation in both network structure and the identity of a keystone individual was not related to the mean or variance of the collective prey attack speed.Individuals that maintained a large and stable number of connections,despite changes in network structure,were the boldest individuals in the group.Therefore,social interactions and boldness are linked across time,but group collective behavior is not influenced by the stability of the social network.Our work demonstrates that dynamic social networks can be modeled in a multilayer framework.This approach may reveal biologically important temporal changes to social structure in other systems.     

Social network modeling: a powerful tool for the study of group scale phenomena in primates

Social Network Analysis is now a valuable tool to study social complexity in many animal species, including primates. However, this framework has rarely been used to implement quantitative data on the social structure of a group within computer models. Such approaches allow the investigation of how social organization constrains other traits and also how these traits can impact the social organization in return. In this commentary, we discuss the powerful potential of social network modeling as a way to study group scale phenomena in primates. We describe the advantages of using such a method and we focus on the specificity of this approach in primates, given the particularities of their social networks compared with those of other taxa. We also give practical considerations and a list of examples as for the choice of parameters that can be used to implement the social layer within the models.     

Topology Analysis of Social Networks Extracted from Literature

In a world where complex networks are an increasingly important part of science, it is interesting to question how the new reading of social realities they provide applies to our cultural background and in particular, popular culture. Are authors of successful novels able to reproduce social networks faithful to the ones found in reality? Is there any common trend connecting an author’s oeuvre, or a genre of fiction? Such an analysis could provide new insight on how we, as a culture, perceive human interactions and consume media. The purpose of the work presented in this paper is to define the signature of a novel’s story based on the topological analysis of its social network of characters. For this purpose, an automated tool was built that analyses the dialogs in novels, identifies characters and computes their relationships in a time-dependent manner in order to assess the network’s evolution over the course of the story.     

Social traits,social networks and evolutionary biology

The social environment is both an important agent of selection for most organisms, and an emergent property of their interactions. As an aggregation of interactions among members of a population, the social environment is a product of many sets of relationships and so can be represented as a network or matrix. Social network analysis in animals has focused on why these networks possess the structure they do, and whether individuals’ network traits, representing some aspect of their social phenotype, relate to their fitness. Meanwhile, quantitative geneticists have demonstrated that traits expressed in a social context can depend on the phenotypes and genotypes of interacting partners, leading to influences of the social environment on the traits and fitness of individuals and the evolutionary trajectories of populations. Therefore, both fields are investigating similar topics, yet have arrived at these points relatively independently. We review how these approaches are diverged, and yet how they retain clear parallelism and so strong potential for complementarity. This demonstrates that, despite separate bodies of theory, advances in one might inform the other. Techniques in network analysis for quantifying social phenotypes, and for identifying community structure, should be useful for those studying the relationship between individual behaviour and group‐level phenotypes. Entering social association matrices into quantitative genetic models may also reduce bias in heritability estimates, and allow the estimation of the influence of social connectedness on trait expression. Current methods for measuring natural selection in a social context explicitly account for the fact that a trait is not necessarily the property of a single individual, something the network approaches have not yet considered when relating network metrics to individual fitness. Harnessing evolutionary models that consider traits affected by genes in other individuals (i.e. indirect genetic effects) provides the potential to understand how entire networks of social interactions in populations influence phenotypes and predict how these traits may evolve. By theoretical integration of social network analysis and quantitative genetics, we hope to identify areas of compatibility and incompatibility and to direct research efforts towards the most promising areas. Continuing this synthesis could provide important insights into the evolution of traits expressed in a social context and the evolutionary consequences of complex and nuanced social phenotypes.     

Plain faces are more expressive: comparative study of facial colour,mobility and musculature in primates

Facial colour patterns and facial expressions are among the most important phenotypic traits that primates use during social interactions. While colour patterns provide information about the sender''s identity, expressions can communicate its behavioural intentions. Extrinsic factors, including social group size, have shaped the evolution of facial coloration and mobility, but intrinsic relationships and trade-offs likely operate in their evolution as well. We hypothesize that complex facial colour patterning could reduce how salient facial expressions appear to a receiver, and thus species with highly expressive faces would have evolved uniformly coloured faces. We test this hypothesis through a phylogenetic comparative study, and explore the underlying morphological factors of facial mobility. Supporting our hypothesis, we find that species with highly expressive faces have plain facial colour patterns. The number of facial muscles does not predict facial mobility; instead, species that are larger and have a larger facial nucleus have more expressive faces. This highlights a potential trade-off between facial mobility and colour patterning in primates and reveals complex relationships between facial features during primate evolution.     

The evolution of generalized reciprocity on social interaction networks

Generalized reciprocity (help anyone, if helped by someone) is a minimal strategy capable of supporting cooperation between unrelated individuals. Its simplicity makes it an attractive model to explain the evolution of reciprocal altruism in animals that lack the information or cognitive skills needed for other types of reciprocity. Yet, generalized reciprocity is anonymous and thus defenseless against exploitation by defectors. Recognizing that animals hardly ever interact randomly, we investigate whether social network structure can mitigate this vulnerability. Our results show that heterogeneous interaction patterns strongly support the evolution of generalized reciprocity. The future probability of being rewarded for an altruistic act is inversely proportional to the average connectivity of the social network when cooperators are rare. Accordingly, sparse networks are conducive to the invasion of reciprocal altruism. Moreover, the evolutionary stability of cooperation is enhanced by a modular network structure. Communities of reciprocal altruists are protected against exploitation, because modularity increases the mean access time, that is, the average number of steps that it takes for a random walk on the network to reach a defector. Sparseness and community structure are characteristic properties of vertebrate social interaction patterns, as illustrated by network data from natural populations ranging from fish to primates.     

Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction

Large‐scale protein signalling networks are useful for exploring complex biochemical pathways but do not reveal how pathways respond to specific stimuli. Such specificity is critical for understanding disease and designing drugs. Here we describe a computational approach—implemented in the free CNO software—for turning signalling networks into logical models and calibrating the models against experimental data. When a literature‐derived network of 82 proteins covering the immediate‐early responses of human cells to seven cytokines was modelled, we found that training against experimental data dramatically increased predictive power, despite the crudeness of Boolean approximations, while significantly reducing the number of interactions. Thus, many interactions in literature‐derived networks do not appear to be functional in the liver cells from which we collected our data. At the same time, CNO identified several new interactions that improved the match of model to data. Although missing from the starting network, these interactions have literature support. Our approach, therefore, represents a means to generate predictive, cell‐type‐specific models of mammalian signalling from generic protein signalling networks.     

A word in the hand: action, gesture and mental representation in humans and non-human primates

The movements we make with our hands both reflect our mental processes and help to shape them. Our actions and gestures can affect our mental representations of actions and objects. In this paper, we explore the relationship between action, gesture and thought in both humans and non-human primates and discuss its role in the evolution of language. Human gesture (specifically representational gesture) may provide a unique link between action and mental representation. It is kinaesthetically close to action and is, at the same time, symbolic. Non-human primates use gesture frequently to communicate, and do so flexibly. However, their gestures mainly resemble incomplete actions and lack the representational elements that characterize much of human gesture. Differences in the mirror neuron system provide a potential explanation for non-human primates' lack of representational gestures; the monkey mirror system does not respond to representational gestures, while the human system does. In humans, gesture grounds mental representation in action, but there is no evidence for this link in other primates. We argue that gesture played an important role in the transition to symbolic thought and language in human evolution, following a cognitive leap that allowed gesture to incorporate representational elements.     

Entropy of dynamical social networks

Human dynamical social networks encode information and are highly adaptive. To characterize the information encoded in the fast dynamics of social interactions, here we introduce the entropy of dynamical social networks. By analysing a large dataset of phone-call interactions we show evidence that the dynamical social network has an entropy that depends on the time of the day in a typical week-day. Moreover we show evidence for adaptability of human social behavior showing data on duration of phone-call interactions that significantly deviates from the statistics of duration of face-to-face interactions. This adaptability of behavior corresponds to a different information content of the dynamics of social human interactions. We quantify this information by the use of the entropy of dynamical networks on realistic models of social interactions.     

«Active» selection may participate in the evolution of primates

Selection pressures in the evolution of morphological characters which are exclusive to primates were discussed. While the evolutionary change in some morphological characters of primates can be explained by natural or sexual selection, there are also morphological characters of primates, such as some regions of neocortices, which are involved in social interactions and whose evolutionary changes can hardly be explained by natural or sexual selection alone. Furthermore, recent studies have demonstrated that relative sizes of brain, neocortex and some thalamic nuclei of brains differ significantly by social structure in primates. Based on these and other findings, we propose here that “active” selection pressures may have favored a variety of morphological characters related to social interactions, the selection pressures which are derived from social interactions and are operative within animals or troops. The introduction of concept of active selection will be useful in developing conceptual frameworks for understanding of the mechanism of evolution of primates, in particular, of hominids.