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The Social Brain Hypothesis
Abstract
Conventional wisdom over the past 160 years in the cognitive and neurosciences has assumed that brains evolved to process factual information about the world. Most attention has therefore been focused on such features as pattern recognition, color vision, and speech perception. By extension, it was assumed that brains evolved to deal with essentially ecological problem-solving tasks. © 1998 Wiley-Liss, Inc.
... Indeed, its structure is prevalent across an extremely diverse range of social communities; including traditional hunter-gatherer groups, small-scale horticultural societies, ancient Roman armies and modern-day military units [4]. The ENM is so prevalent that it can even be observed in many non-human primate species, although with smaller group sizes [5]. The Social Brain Hypothesis proposed by Dunbar explains this pervasiveness, positing that primates have a cognitive limit that restricts the size and complexity of social groups they can maintain. ...
... As previously mentioned, the ENM is centred around an individual Ego, who is surrounded by their Alters, organised in a series of concentric circles. The ENM stems from the anthropological Social Brain Hypothesis [5], which posits that the social capabilities of primates are constrained by the sizes of their neocortices. Based on the size of our own neocortex, the maximum social group size that can be maintained by a human is estimated to be around 150 (the famous Dunbar's number). ...
... Each of these directed Tweets corresponds to an interaction between an Ego and an Alter. While some of these interactions may involve the wider network beyond the specific Alter, they nonetheless reflect a cognitive involvement of the Ego towards the Alter, which is the most critical characteristic for mapping an interaction to a specific social relationship [5]. ...
The Ego Network Model (ENM) is a model for the structural organisation of relationships, rooted in evolutionary anthropology, that is found ubiquitously in social contexts. It takes the perspective of a single user (Ego) and organises their contacts (Alters) into a series of (typically 5) concentric circles of decreasing intimacy and increasing size. Alters are sorted based on their tie strength to the Ego, however, this is difficult to measure directly. Traditionally, the interaction frequency has been used as a proxy but this misses the qualitative aspects of connections, such as signs (i.e. polarity), which have been shown to provide extremely useful information. However, the sign of an online social relationship is usually an implicit piece of information, which needs to be estimated by interaction data from Online Social Networks (OSNs), making sign prediction in OSNs a research challenge in and of itself. This work aims to bring the ENM into the signed networks domain by investigating the interplay of signed connections with the ENM. This paper delivers 2 main contributions. Firstly, a new and data-efficient method of signing relationships between individuals using sentiment analysis and, secondly, we provide an in-depth look at the properties of Signed Ego Networks (SENs), using 9 Twitter datasets of various categories of users. We find that negative connections are generally over-represented in the active part of the Ego Networks, suggesting that Twitter greatly over-emphasises negative relationships with respect to “offline” social networks. Further, users who use social networks for professional reasons have an even greater share of negative connections. Despite this, we also found weak signs that less negative users tend to allocate more cognitive effort to individual relationships and thus have smaller ego networks on average. All in all, even though structurally ENMs are known to be similar in both offline and online social networks, our results indicate that relationships on Twitter tend to nurture more negativity than offline contexts.
... According to Zipf [6], some of these structural regularities are the result of a compromise that minimizes the effort spent in communication for both the sender-who prefers to use frequent words to minimize the word retrieval time-and the receiver-who prefers less used words to minimize ambiguity. Previous work has shown the existence of a new set of structural [7] and semantic [8] invariants in language production using an egocentric model inspired by the social ego network model [9], which in turns originates from the social brain hypothesis from anthropology [10]. This model organizes a person's (the ego) social relationships into concentric circles (between four and five on average) according to their intensity [a toy example is provided in Fig. 1(a)]. ...
... Language production, just like the socialization process, consumes cognitive capacities that are limited, despite the power of the human brain. These two human activities are closely connected, as postulated by the "social gossip theory of language evolution" [10], which establishes a causal link between the sudden increase in the number of active relationships in humans (from 50 for the closest nonverbal primates to 150 for humans) and the appearance of language that would have optimized the activity Fig. 1. Social ego network is constructed by first calculating the frequency of contact between a person (the ego) and the individuals the ego has a social relationship with (the alters). ...
... The social ego network model organizes the interpersonal relationships of a person (the ego) into concentric circles. This is an empirical model derived from the work of anthropologist Robin Dunbar on the number of active relationships that a human can maintain on average over time [10]. To do this, he established a correlation between the relative size of a part of the brain dedicated to sociability (the neocortex) and the typical group size in primates, then deduced what the equivalent number would be for humans. ...
The “ego network of words” model captures structural properties in language production associated with cognitive constraints. While previous research focused on the layer-based structure and its semantic properties, this article argues that an essential element, the concept of an
active network
, is missing. The
active
part of the ego network of words only includes words that are regularly used by individuals, akin to the ego networks in the social domain, where the active part includes relationships regularly nurtured by individuals, and hence demanding cognitive effort. In this work, we define a methodology for extracting the active part of the ego network of words and validate it using interview transcripts and tweets. The robustness of our method to varying input data sizes and temporal stability is demonstrated. We also demonstrate that without the active network concept (and a tool for properly extracting the active network from data), the “ego network of words” model is not able to properly estimate the cognitive effort involved and it becomes vulnerable to the amount of data considered (leading to the disappearance of the layered structure in large datasets). Our results are well-aligned with prior analyses of the ego network of words, where the limitation of the data collected led automatically (and implicitly) to approximately consider the active part of the network only. Moreover, the validation on the transcripts dataset (MediaSum) highlights the generalizability of the model across diverse domains and the ingrained cognitive constraints in language usage.
... Cognition can be defined as the mental processes by which animals collect, retain and use information from their environment to guide their behaviour (Shettleworth, 2001). The Social Intelligence Hypothesis (SIH) has emerged as one of the leading theories to explain the evolution of cognition, predicting that the demands of social interactions are an important selective factor (Dunbar, 1998;Jolly, 1966;Humphrey, 1976;Chance & Mead, 1953). The link between cognition and sociality dates back to Darwin (1871), however the SIH was initially proposed by Chance & Mead (1953) and Jolly (1966), and then formalised by Humphrey (1976). ...
... The link between cognition and sociality dates back to Darwin (1871), however the SIH was initially proposed by Chance & Mead (1953) and Jolly (1966), and then formalised by Humphrey (1976). The SIH has since taken various forms, such as the Machiavellian Intelligence Hypothesis (Byrne & Whiten, 1988) and the Social Brain Hypothesis (Dunbar, 1998), but the central tenet remains the same: that cognition has evolved in response to the demands of living in complex social groups, in which individuals interact in different contexts with multiple different individuals, and often repeatedly with the same individuals over time (Freeberg, Dunbar & Ord, 2012). Maintaining and coordinating multiple relationships, monitoring both intra-and intergroup individuals, and recognising suitable cooperative partners, are a few of the many cognitive demands required of social animals that are hypothesised to require a high degree of informational processing (Dunbar, 1998;Jolly, 1966;Humphrey, 1976;Chance & Mead, 1953). ...
... The SIH has since taken various forms, such as the Machiavellian Intelligence Hypothesis (Byrne & Whiten, 1988) and the Social Brain Hypothesis (Dunbar, 1998), but the central tenet remains the same: that cognition has evolved in response to the demands of living in complex social groups, in which individuals interact in different contexts with multiple different individuals, and often repeatedly with the same individuals over time (Freeberg, Dunbar & Ord, 2012). Maintaining and coordinating multiple relationships, monitoring both intra-and intergroup individuals, and recognising suitable cooperative partners, are a few of the many cognitive demands required of social animals that are hypothesised to require a high degree of informational processing (Dunbar, 1998;Jolly, 1966;Humphrey, 1976;Chance & Mead, 1953). Most research has investigated the relationship between cognition and sociality from an evolutionary perspective by comparing neuroanatomy and sociality across species (e.g. ...
The Social Intelligence Hypothesis (SIH) is one of the leading explanations for the evolution of cognition. Since its inception a vast body of literature investigating the predictions of the SIH has accumulated, using a variety of methodologies and species. However, the generalisability of the hypothesis remains unclear. To gain an understanding of the robustness of the SIH as an explanation for the evolution of cognition, we systematically searched the literature for studies investigating the predictions of the SIH. Accordingly, we compiled 103 studies with 584 effect sizes from 17 taxonomic orders. We present the results of four meta‐analyses which reveal support for the SIH across interspecific, intraspecific and developmental studies. However, effect sizes did not differ significantly between the cognitive or sociality metrics used, taxonomy or testing conditions. Thus, support for the SIH is similar across studies using neuroanatomy and cognitive performance, those using broad categories of sociality, group size and social interactions, across taxonomic groups, and for tests conducted in captivity or the wild. Overall, our meta‐analyses support the SIH as an evolutionary and developmental explanation for cognitive variation.
... These close relationships are associated with high emotional intensity and they are surrounded by a larger number of weaker ties. The emergence of this characteristic structural pattern has been associated with constraints on maintaining social relationships, which include limited information processing capacity 11 , social cognition [12][13][14] , and time availability [15][16][17] . ...
... The cumulative advantage mechanism that drives the dispersion of tie strength can be thought to effectively result from people putting more emphasis on their closest relationships, which arise in part due to similarities in any number of sociodemographic, behavioral, and intrapersonal characteristics 59 . Generally, the heterogeneity of tie strengths in ego networks has been attributed to cognitive, temporal, and other constraints [11][12][13][15][16][17] , and different personality traits 60,61 and their relative stability have been proposed as one possible reason for the persistent individual variation in this heterogeneity 20 . ...
... One possibility is that our brain is simply wired to consistently shape our social networks in similar ways, independent of the specific medium of communication 13,63 . Alternatively, the reason may lie in the mechanisms of tie strength reinforcement: cumulative advantage may arise, e.g., because we have already participated in an online conversation with someone and it is easier to continue interacting with the same alter. ...
Tie strengths in social networks are heterogeneous, with strong and weak ties playing different roles at the network and individual levels. Egocentric networks, networks of relationships around an individual, exhibit few strong ties and more weaker ties, as evidenced by electronic communication records. Mobile phone data has also revealed persistent individual differences within this pattern. However, the generality and driving mechanisms of social tie strength heterogeneity remain unclear. Here, we study tie strengths in egocentric networks across multiple datasets of interactions between millions of people during months to years. We find universality in tie strength distributions and their individual-level variation across communication modes, even in channels not reflecting offline social relationships. Via a simple model of egocentric network evolution, we show that the observed universality arises from the competition between cumulative advantage and random choice, two tie reinforcement mechanisms whose balance determines the diversity of tie strengths. Our results provide insight into the driving mechanisms of tie strength heterogeneity in social networks and have implications for the understanding of social network structure and individual behavior.
... Several hypotheses have been proposed for the expected phylogenetic distribution of reliance on social information. The first and most popular hypothesis (social intelligence) is that social species evolve to take advantage of the greater amount of social information available to them and are thus expected to rely more on social information than solitary species [8,9]. A second non-mutually exclusive hypothesis ( predation risk) suggests species more at risk for predation rely more on social information because the costs of using individual information are increased [5]. ...
... Social interaction has been suggested to drive the evolution of intelligence and brain size [8,9], with supporting evidence coming from a comparative primate study associating group size with brain size [8]. However, this relationship is often not supported, leading to calls for more nuanced investigation of the relationship between sociality and social intelligence (e.g. ...
... Social interaction has been suggested to drive the evolution of intelligence and brain size [8,9], with supporting evidence coming from a comparative primate study associating group size with brain size [8]. However, this relationship is often not supported, leading to calls for more nuanced investigation of the relationship between sociality and social intelligence (e.g. ...
Individuals can reduce sampling costs and increase foraging efficiency by using information provided by others. One simple form of social information use is delayed local enhancement or increased interest in a location because of the past presence of others. We tested for delayed local enhancement in two ecomorphs of stickleback fish, benthic and limnetic, from three different lakes with putative independent evolutionary origins. Two of these lakes have reproductively isolated ecomorphs (species-pairs), whereas in the third, a previously intact species-pair recently collapsed into a hybrid swarm. Benthic fish in both intact species-pair lakes were more likely to exhibit delayed local enhancement despite being more solitary than limnetic fish. Their behaviour and morphology suggest their current perceived risk and past evolutionary pressure from predation did not drive this difference. In the hybrid swarm lake, we found a reversal in patterns of social information use, with limnetic-looking fish showing delayed local enhancement rather than benthic-looking fish. Together, our results strongly support parallel differentiation of social learning differences in recently evolved fish species, although hybridization can apparently erode and possibly even reverse these differences.
... Other possible explanations for patterns in brain size diversity were outlined by the social brain hypothesis, suggesting that the development of social factors, such as the size of the social group, mating system, deception, and cooperation, drive the enlargement of the brain (Dunbar 1998). Within the species included in our dataset, minnow is genuinely gregarious species (Ward and Krause 2001), trout establishes social hierarchy (Jenkins 1969), while bullhead is solitary (Mills and Mann 1983;Ladich 1990). ...
... Based on the observed pattern of brain size minnow > trout > bullhead, with nonsignificant differences between the minnow and trout, can be suggested that differences in fish brain sizes could also be influenced by the complexity of their sociality. It is important to note that the social brain hypothesis was originally based on the size of neocortex in primates as a proxy for cognition associated with sociality (Dunbar 1998). Thus, the comparison between mammals and fish should be cautious in this respect as their telencephalon has developed differently (Rodríguez et al 2002), and the search for structures homologous to the neocortex is still in progress in fish. ...
Differences in brain size among homeothermic vertebrates are known to have important ecological and evolutionary consequences, involving trade-offs between the cognitive benefits of larger brains and the associated energetic costs. Nonetheless, other poikilothermic vertebrate groups have been largely overlooked in this context, challenging the broad applicability of the proposed theories for vertebrates more generally. Fish brains are highly plastic organs that adapt to environmental conditions, so we focused on local-scale validation based on comparisons of species from the undisturbed headwaters of Šumava National Park, Czech Republic. The brains of common minnows (Phoxinus phoxinus L.), brown trout (Salmo trutta m. fario L.) and European bullheads (Cottus gobio L.) were scanned via computed tomography. Our aim was to determine whether the brain size patterns of these three species, which are unrelated at the level of phylogenetic order and occur naturally in a single locality without significant anthropogenic pressures, follow general predictions. The cognitive buffer hypothesis, which suggests that large brains provide a behavioural buffer facilitating successful introduction to new environments, was confirmed, as brown trout and minnows, i.e., species with invasive potential, had larger brains than non-invasive, stationary bullheads. This confirmation provides new support for the general validity of the cognitive buffer hypothesis across vertebrates. However, our results were not in alignment with the parental brain hypothesis. The patterns of sensory areas of the brain also measured in the present study (i.e., the olfactory bulb, optic tectum and eminentia granularis) indicate that minnows invest more in the development of the sensory areas of the brain and, thus, primary sensory processing, whereas trout invest in cognitive and integrative processing. The present study emphasises that general evolutionary predictions and theories regarding brain size, especially in fish, should also be verified at a local scale with comparable ecological conditions across species.
... Social networks are created based on (1) being in the same household, (2) working in the same place, or (3) attending the same educational site. Household networks are fully connected, while their family members' educational and work networks are generated using a small-world network theory [28] and ideas from Dunbar [9] with respect to group sizes. Fig. 4(A) shows a sample record extracted from the synthetic population dataset and Fig. 4(B) shows the sample of the synthetic social networks extracted from the household network. ...
... Table 1 provides the basic information related to each resulting dataset. One point that should be noted is the value of n in each social network dataset is different depending on the size of a specific person's social network, where the minimum size is zero and the maximum size is 14 based on notions from Dunbar [9]. According to 2010 United States Census [22], there were 19,387,102 people and 7,317,755 households in New York State. ...
Over the last two decades, there has been a growth in the applications of geographically-explicit agent-based models. One thing such models have in common is the creation of synthetic populations to initialize the artificial worlds in which the agents inhabit. One challenge such models face is that it is often difficult to create reusable geographically-explicit synthetic populations with social networks. In this paper, we introduce a Python based method that generates a reusable geographically-explicit synthetic population dataset along with its social networks. In addition, we present a pipeline for using the population datasets for model initialization. With this pipeline, multiple spatial and temporal scales of geographically-explicit agent-based models are presented focusing on Western New York. Such models not only demonstrate the utility of our synthetic population on commuting patterns but also how social networks can impact the simulation of disease spread and vaccination uptake. By doing so, this pipeline could benefit any modeler wishing to reuse synthetic populations with realistic geographic locations and social networks.
... An active yet problematic approach to the question is based on correlational analyses. In that approach, hypotheses are formulated, which often emphasize ecological [10][11][12][13], social [14][15][16][17], or cultural [18][19][20][21][22] factors as selecting for larger brains. Then, proxy variables are chosen as being relevant to each hypothesis, such as diet type [23,24], environment productivity and precipitation variability [25], group size [16], or social learning frequency [26], and they are tested for whether they correlate with brain size or the size of particular brain regions. ...
... In that approach, hypotheses are formulated, which often emphasize ecological [10][11][12][13], social [14][15][16][17], or cultural [18][19][20][21][22] factors as selecting for larger brains. Then, proxy variables are chosen as being relevant to each hypothesis, such as diet type [23,24], environment productivity and precipitation variability [25], group size [16], or social learning frequency [26], and they are tested for whether they correlate with brain size or the size of particular brain regions. Finally, if the proxy variable of a hypothesis correlates with the brain variable, or if it is more strongly correlated than the other proxy variables, then the correlations are interpreted as supporting the hypothesis. ...
Why the human brain size evolved has been a major evolutionary puzzle since Darwin but addressing it has been challenging. A key reason is the lack of research tools to infer the causes of a unique event for which experiments are not possible. We describe how the analogous problem of why there is day and night has been successfully addressed in physics and learning from that experience, we outline a strategy to address why the human brain size evolved: hypotheses are expressed in mechanistic models that yield quantitative predictions for evolutionary and developmental trajectories of brain and body sizes, the predicted trajectories are compared to data, and models are chosen by their ability to explain the data. By pursuing this strategy, we present results from one model that predicts evolutionary and developmental trajectories for six hominin species. We compare these predictions to data, finding that the model recovers multiple but not all aspects of hominin evolution and development. Counterintuitively, the human brain size evolves in this model as a spandrel, that is, as a byproduct of selection for something else, specifically, preovulatory ovarian follicles. Our analysis describes an alternative way forward to infer why the human brain size evolved.
... One approach to tackle the potential genetic patterns underlying the complex language network is by examining its relations with other cognitive functions that are hypothesized to coevolve with language in biological evolution. Language evolution has been hypothesized to be linked to several key cognitive abilities (though not in mutually exclusive manner; Dunbar, 1998Dunbar, , 2003Fitch et al., 2010;Vaesen, 2012). One is complex tool use, with theories assuming that language evolved with complex tool use, sharing a key cognitive component of hierarchical processing of information sequences. ...
... One is gesturing, a specific way of social communication that is considered a precursor or foundation for the evolution of language (Sterelny, 2012;Hobaiter and Byrne, 2014;Graham and Hobaiter, 2023). Finally, and not mutually exclusively, language evolution has been proposed to be motivated and intertwined with social interaction, with language relieving the pressure of social survival by replacing grooming behavior and sharing a cognitive mechanism with social cognition such as the theory of mind (Dunbar, 1998(Dunbar, , 2003(Dunbar, , 2017Fitch et al., 2010;Oesch and Dunbar, 2017;Rajimehr et al., 2022). Investigating whether and how the genetic effects underlying neural activities in language processing are related to the genetic effects underlying these processes is one way to parse the potential genetic patterns underlying language neural networks. ...
Language is an evolutionarily salient faculty for humans that relies on a distributed brain network spanning across frontal, temporal, parietal, and subcortical regions. To understand whether the complex language network shares common or distinct genetic mechanisms, we examined the relationships between the genetic effects underlying the brain responses to language and a set of object domains that have been suggested to coevolve with language: tools, faces (indicating social), and body parts (indicating social and gesturing). Analyzing the twin datasets released by the Human Connectome Project that had functional magnetic resonance imaging data from human twin subjects (monozygotic and dizygotic) undergoing language and working memory tasks contrasting multiple object domains (198 females and 144 males for the language task; 192 females and 142 males for the working memory task), we identified a set of cortical regions in the frontal and temporal cortices and subcortical regions whose activity to language was significantly genetically influenced. The heterogeneity of the genetic effects among these language clusters was corroborated by significant differences of the human gene expression profiles (Allen Human Brain Atlas dataset). Among them, the bilateral basal ganglia (mainly dorsal caudate) exhibited a common genetic basis for language, tool, and body part processing, and the right superior temporal gyrus exhibited a common genetic basis for language and tool processing across multiple types of analyses. These results uncovered the heterogeneous genetic patterns of language neural processes, shedding light on the evolution of language and its shared origins with tools and bodily functions.
... First, we discuss the implications of "collective living": how competition between agents creates novel data by disrupting local equilibria, often generating naturally emergent sequences of learning opportunities that stimulate behavioural innovation [25,24,26,27,28,29,30]. Second, we examine how social relationships facilitate cooperation between individuals and contribute to forms of cognition relevant to human-like behaviours, including social learning [31,32,33] and Machiavellian selection [34,35]. Finally, we discuss major evolutionary transitions [36,37] and their role in human cultural evolution via language [38]. ...
... Cognition that incorporates awareness of group structure and relationships allows for division of labor, reciprocity and coalition formation, but also creates social dilemmas, as individuals can benefit from cooperating selectively. The social brain (or Machiavellian intelligence) hypothesis [34] proposes that the interplay of competitive and cooperative interactions arising in such relationships creates positive feedbacks in cognitive evolution. Theoretically, improved social cognition could enable an individual to better predict and control others, whilst making that individual harder to predict itself, thus creating a cognitive arms race [67]. ...
Traditionally, cognitive and computer scientists have viewed intelligence solipsistically, as a property of unitary agents devoid of social context. Given the success of contemporary learning algorithms, we argue that the bottleneck in artificial intelligence (AI) progress is shifting from data assimilation to novel data generation. We bring together evidence showing that natural intelligence emerges at multiple scales in networks of interacting agents via collective living, social relationships and major evolutionary transitions, which contribute to novel data generation through mechanisms such as population pressures, arms races, Machiavellian selection, social learning and cumulative culture. Many breakthroughs in AI exploit some of these processes, from multi-agent structures enabling algorithms to master complex games like Capture-The-Flag and StarCraft II, to strategic communication in Diplomacy and the shaping of AI data streams by other AIs. Moving beyond a solipsistic view of agency to integrate these mechanisms suggests a path to human-like compounding innovation through ongoing novel data generation.
... Neuroimaging studies have provided evidence of the specific brain regions responsible for the executive control and emotional salience of ToM capabilities, finding that the most relevant regions are the medial prefrontal and orbitofrontal cortex in 93% of studies, temporoparietal junction in 58% of studies, and the anterior cingulate cortex in 55% of studies. Dunbar (1998) found a significant correlation between the neocortex size between different primates and their average group size. ...
... Shows the comparison between the size of the neocortex in gorillas, chimpanzees and humans. As discovered by Dunbar (1998), the size of the neocortex has a positive relationship with the species group size which suggests a physiological link to the theory of mind (ToM) hypothesis. ...
In this paper we analyze diverse theories about the workings of the mind and the evolutionary trajectory of brain physiology, giving rise to species-typical mechanisms in human cognition. Evolutionary psychology has shed light on how a computational theory of the mind elucidates the development of specialized psychological programs, enhancing our fitness based on ancestral conditions. An example of such adaptation is the expansion of the prefrontal cortex relative to body size, particularly among primates. This enlargement fosters the formation of intricate social structures, leading to more extensive groups and refined social dynamics. Interestingly, this positive link between brain size and social structure holds true for both humans and non-human primates. Recent strides in neuroscience and brain technology have enabled us to uncover the primary brain regions influencing social cognition, executive function, and emotional processing. Brain areas including the frontal lobe, prefrontal cortex, insular cortex, cingulate cortex, hypo-thalamus, and others intricately shape learning, emotion regulation, and decision-making processes. Therefore, the evidence for the evolutionary theory of the mind and its implications for behavioral neuroscience are undeniable.
... These ideas are encapsulated by the highly influential but controversial Social Intelligence (or Social Brain) Hypothesis (SIH or SBH) (12)(13)(14)(15)(16); for critiques see (17)(18)(19)(20)(21)(22)(23)(24)(25)(26). While variants of the hypothesis differ in their emphasis (e.g., on "Machiavellian" manipulations (14), social learning (27) or cooperation (28)), they share a common focus on the importance of navigating social relationships as a central driver of cognitive and brain evolution. ...
... Accordingly, there is evidence that primate species that live in bigger groups (with a greater number of potential social partners) tend to have bigger brains (15,17,30), but see (26). The fundamental logic of the SIH may be extended to other taxa. ...
The need to maintain strong social bonds is widely held to be a key driver of cognitive evolution. This assumes that the maintenance of strong bonds is a stable trait that is cognitively demanding but generates fitness benefits, and so can come under selection. However, these fundamental micro-evolutionary tenets have yet to be tested together within a single study system. Combining observational and experimental behavioural data with long-term breeding records, we tested four key assumptions in wild jackdaws (Corvus monedula), corvids whose long-term pair-bonds exemplify the putative social drivers of cognitive evolution in birds. We found support for three assumptions: (1) pair-bond strength varies across the population, (2) is consistent within pairs over time and (3) is positively associated with a measure of socio-cognitive performance. However, we did not find evidence that stronger pair-bonds lead to better fitness outcomes (prediction 4). While strongly bonded pairs were better able to adjust hatching synchrony to environmental conditions, they did not fledge more or higher quality offspring. Together, these findings provide important evidence that the maintenance of strong pair bonds is linked to socio-cognitive performance and facilitates effective coordination between partners. However, they also imply that these benefits may not be sufficient to explain how selection acts on social cognition. We argue that evaluating how animals navigate trade-offs between investing in long-term relationships versus optimising interactions in their wider social networks will be a crucial avenue for future research.
... ties that are not strong), migration is not deterred. Such evidence suggests that there may be rivalry in information sharing in networks, which leads migrants to value connections to people for whom there is less competition for attention (as in Dunbar, 1998;Banerjee et al., 2012). We also find that while the average migrant is not drawn to locations where her friends have more friends (as in G 3 ), such structure does attract several less common types of migrants. ...
... This heterogeneity is consistent with the notion, proposed by Dunbar (1998) and others, that people might have a capacity constraint in the number of friendships they can effectively support, which in turn might induce a degree of rivalry for the attention of a friend. In our context, migrants may be drawn to places where they receive their friends ' undivided attention. ...
How do social networks influence the decision to migrate? Prior work suggests two distinct mechanisms that have historically been difficult to differentiate: as a conduit of information, and as a source of social and economic support. We disentangle these mechanisms using a massive ‘digital trace’ dataset that allows us to observe the migration decisions made by millions of individuals over several years, as well as the complete social network of each person in the months before and after migration. These data allow us to establish a new set of stylized facts about the relationship between social networks and migration. Our main analysis indicates that the average migrant derives more social capital from ‘interconnected’ networks that provide social support than from ‘extensive’ networks that efficiently transmit information.
... First, we discuss the implications of 'collective living': how competition between agents creates novel data by disrupting local equilibria, often generating naturally emergent sequences of learning opportunities that stimulate behavioural innovation [24][25][26][27][28][29][30] . Second, we examine how social relationships facilitate cooperation between individuals and contribute to forms of cognition relevant to human-like behaviours, including social learning [31][32][33] and Machiavellian selection 34,35 . Finally, we discuss major evolutionary transitions 36,37 and their role in human cultural evolution via language 38 . ...
... Cognition that incorporates awareness of group structure and relationships allows for division of labour, reciprocity and coalition formation, but also creates social dilemmas, as individuals can benefit from cooperating selectively. The social brain (or Machiavellian intelligence) hypothesis 34 proposes that the interplay of competitive and cooperative interactions arising in such relationships creates positive feedbacks in cognitive evolution. Theoretically, improved social cognition could enable an individual to better predict and control others, while making that individual harder to predict itself, thus creating a cognitive arms race 67 . ...
... Distributed cognition and related terms were subsequently presented as elements of cognitive ecosystem analysis (Hutchins 2010). O'Donnell et al. (2015) presented a distributed cognition model as an alternative to the social brain hypothesis developed for primates (Dunbar 1998). The distributed cognition model predicts a reduction rather than increase in individual brain investment. ...
... "Social intelligence" enables coping with the challenges of group living; related selective forces may favor increased brain size and dedicated neuroarchitectures to monitor, store, and respond adaptively to information in contexts of social bonding and reproductive conflict. As predicted by the social brain hypothesis (Dunbar 1998) originally formulated for primates, group size and concomitant selection for greater cognitive skills needed to manage more numerous and complex social relationships drive the evolution of a larger brain. The application of this hypothesis to social insects has been questioned and empirical support has been inconsistent. ...
Descriptions of types of intelligence or cognition that conceptualize and categorize behavioral capabilities of workers and cooperative groups of eusocial insects have proliferated. Individual workers are described as having cognition, or less frequently, intelligence, and emergent colony-level behavior is typically described as collective intelligence, swarm intelligence, and distributed intelligence (or cognition). These concepts and terms have historical roots in psychology, education, economics, politics, computer science, artificial intelligence, and robotics, and have varied connotations and denotations that often are inconsistent with their initial context of use. Although integration and hybridization among disciplines can be productive, imprecise and potentially misleading applications may limit the ability to accurately describe or conceptualize social insect behavioral phenomena, generate testable hypotheses, and communicate accurately and broadly within the scientific community and with the media and public. Here, we aim to clarify the origins, meanings, and relevance of terms associated with social insect intelligence and cognition. An historical, semantic, and mechanistic analysis suggests that terms may lack relevant conceptual significance and should be carefully evaluated before applying them free-hand to attempt to inform our understanding of social insect cognition at multiple levels. We provide rationale and recommendations for retaining or discontinuing the use of terms.
... Our assumption of bounded communities is supported by empirical evidence that suggests the "best" communities contain small sets of actors, which are almost disconnected from the rest of the network (Leskovec et al., 2009) and by psychologists and primatologists who have proposed a limit on the size of human social networks (e.g. Dunbar (1998)). This fact allows us to strategically allocate modeling effort within a large graph to be concentrated on a relatively small portion of dyads. ...
Many existing statistical and machine learning tools for social network analysis focus on a single level of analysis. Methods designed for clustering optimize a global partition of the graph, whereas projection based approaches (e.g. the latent space model in the statistics literature) represent in rich detail the roles of individuals. Many pertinent questions in sociology and economics, however, span multiple scales of analysis. Further, many questions involve comparisons across disconnected graphs that will, inevitably be of different sizes, either due to missing data or the inherent heterogeneity in real-world networks. We propose a class of network models that represent network structure on multiple scales and facilitate comparison across graphs with different numbers of individuals. These models differentially invest modeling effort within subgraphs of high density, often termed communities, while maintaining a parsimonious structure between said subgraphs. We show that our model class is projective, highlighting an ongoing discussion in the social network modeling literature on the dependence of inference paradigms on the size of the observed graph. We illustrate the utility of our method using data on household relations from Karnataka, India.
... In short, we learn our basics and how to adapt mostly by imitation all along our life. It seems that imitation has evolved as an evolutionary advantageous trait, and may even have promoted the development of our anomalously large brain (compared with other mammals) [1]. It is actually "rational" to imitate when lacking sufficient time, energy and information to take a decision based only on private information and processing, that is..., most of the time. ...
We tested 45 indices and common stocks traded in the South African stock market for the possible existence of a bubble over the period from Jan. 2003 to May 2006. A bubble is defined by a faster-than-exponential acceleration with significant log-periodic oscillations. The faster-than-exponential acceleration characteristics are tested with several different metrics, including nonlinearity on the logarithm of the price and power law fits. The log-periodic properties are investigated in detail using the first-order log-periodic power-law (LPPL) formula, the parametric detrending method, the (H,q)-analysis, and the second-order Weierstrass-type model, resulting in a consistent and robust estimation of the fundamental angular log-frequency , in reasonable agreement with previous estimations on many other bubbles in developed and developing markets. Sensitivity tests of the estimated critical times and of the angular log-frequency are performed by varying the first date and the last date of the stock price time series. These tests show that the estimated parameters are robust. With the insight of 6 additional month of data since the analysis was performed, we observe that many of the stocks on the South Africa market experienced an abrupt drop mid-June 2006, which is compatible with the predicted for several of the stocks, but not all. This suggests that the mini-crash that occurred around mid-June of 2006 was only a partial correction, which has resumed into a renewed bubbly acceleration bound to end some times in 2007, similarly to what happened on the S&P500 US market from Oct. 1997 to Aug. 1998.
... Survivors are rationally efficient from an ecological perspective. The extensive cooperation within human societies, the biological development of a human "social brain" (Dunbar, 1998) and the adjustment of reward-punishment to a fine-tuned level constitute co-evolutionary processes, strengthening human groups in a Darwinian selection process. Evolutionary feedback selection as we understand it in terms of a self-organizing attracting dynamical equilibrium bypasses by construction the second-order free-rider problem (Panchanathan and Boyd, 2004). ...
Strong reciprocity is a fundamental human characteristic associated with our extraordinary sociality and cooperation. Laboratory experiments on social dilemma games and many field studies have quantified well-defined levels of cooperation and propensity to punish/reward. The level of cooperation is observed to be strongly dependent on the availability of punishments and/or rewards. Here, we suggest that the propensity for altruistic punishment and reward is an emergent property that has co-evolved with cooperation by providing an efficient feedback mechanism through both biological and cultural interactions. By favoring high survival probability and large individual gains, the propensity for altruistic punishment and rewards reconciles self- and group interests. We show that a simple cost/benefit analysis at the level of a single agent, who anticipates the action of her fellows, determines an optimal level of altruistic punishment, which explains quantitatively experimental results on the third-party punishment game, the ultimatum game and altruistic punishment games. We also report numerical simulations of an evolutionary agent-based model of repeated agent interactions with feedback-by-punishments, which confirms that the propensity to punish is a robust emergent property selected by the evolutionary rules of the model.
... Despite their promise, we argue that state-of-the-art lifelong learning agents like Voyager face a crucial limitation: they learn in isolation, neglecting a fundamental aspect of human intelligence-the social context. So central is the social context to our existence, that the Social Intelligence Hypothesis posits that our cognitive capabilities evolved primarily to navigate the complexities of social life (Humphrey, 1976;Dunbar, 1998). This isolated learning becomes particularly problematic when coupled with these agents' reliance on closed LLM) like GPT-4. ...
Contemporary embodied agents, such as Voyager in Minecraft, have demonstrated promising capabilities in open-ended individual learning. However, when powered with open large language models (LLMs), these agents often struggle with rudimentary tasks, even when fine-tuned on domain-specific knowledge. Inspired by human cultural learning, we present \collabvoyager, a novel framework that enhances Voyager with lifelong collaborative learning through explicit perspective-taking. \collabvoyager introduces three key innovations: (1) theory of mind representations linking percepts, beliefs, desires, and actions; (2) natural language communication between agents; and (3) semantic memory of task and environment knowledge and episodic memory of collaboration episodes. These advancements enable agents to reason about their and others' mental states, empirically addressing two prevalent failure modes: false beliefs and faulty task executions. In mixed-expertise Minecraft experiments, \collabvoyager agents outperform Voyager counterparts, significantly improving task completion rate by for collecting one block of dirt and for collecting one wood block. They exhibit emergent behaviors like knowledge transfer from expert to novice agents and collaborative code correction. \collabvoyager agents also demonstrate the ability to adapt to out-of-distribution tasks by using their previous experiences and beliefs obtained through collaboration. In this open-ended social learning paradigm, \collabvoyager paves the way for the democratic development of embodied AI, where agents learn in deployment from both peer and environmental feedback.
... Tomasello (2009) proporciona una visión de cómo y por qué las habilidades sociales y la inteligencia evolucionaron en los humanos. Como lo sugiere Dunbar (1998), el desarrollo y crecimiento del cerebro en los homínidos fue el resultado de la necesidad de procesar, manejar y recordar relaciones sociales complejas. Lo qué a su vez impulsó el desarrollo de la capacidad intelectual. ...
Los coordinadores estamos seguros de que los lectores encontrarán en
esta obra material que, aunque de carácter divulgativo, tendrá la profundidad
suficiente para permitir vislumbrar las múltiples implicaciones sociales
que traen consigo las modernas tecnologías de la inteligencia artificial.
Como hemos señalado, en su conjunto, el contenido de los diversos capítulos
va más allá de la dicotomía entre tecnofilia y tecnofobia que, aunque
simplifica el discurso, lo vuelve simplista y binario, sin ofrecer los matices
que se encuentran en el mundo y la vida real. La visión que aquí se ofrece
es matizada también por su origen multidisciplinario.
En esta época donde la IA ha cobrado nuevos bríos, no son pocas las
publicaciones donde tecnólogos optimistas tratan de justificar a ultranza
los usos de la tecnología, ofreciendo una miope visión de los alcances
sociales. Tampoco faltan las publicaciones de estudiosos de las Ciencias
Sociales que plantean de forma adecuada las implicaciones sociales pero
que tienen una óptica distorsionada sobre los alcances reales y el funcionamiento
actual de las tecnologías en cuestión. El carácter multidisciplinario,
contrastado, del material de este libro lo convierte en rara avis y lo distingue
de otras muchas publicaciones que se podrán encontrar en torno a la
IA. Invitamos entonces a los lectores a explorar este mundo de contrastes,
de posibilidades, de fuentes de inspiración, de importantes advertencias
y de potenciales futuros, que ofrece la inteligencia artificial en nuestras
sociedades.
... Even within the same group, individuals experience different social environments depending on the number of social partners, the frequency of interaction with them, and the properties of the partners' social network (i.e., friends of friends) 24,25 . If, as predicted by the SIH 6,7 , social lives impose cognitive demands on animals, then differences in sociality at the individual level would also affect cognitive abilities. Notably, researchers have found that such individual variations in sociality are associated with cognitive abilities in humans. ...
The Social Intelligence Hypothesis predicts that complex social environments promote higher cognitive capacities. This hypothesis is often tested by comparing species or conspecific groups with varying group sizes or social structures. However, individual social environments differ not only among species or groups but also within the same group. We examined the relationship between social centrality and cognitive ability in wild Japanese macaques (Macaca fuscata). We created a grooming network using data from 196 adult macaques and calculated social centrality for each individual. We then tested the macaques with a cognitive test battery to assess their abilities in social, physical, and inhibitory control domains. Our findings revealed that social centrality was uniquely associated with inhibitory control performance, particularly in the behavioral inhibition task, but not with other cognitive domains. This suggests that inhibitory control, a key component of executive functions, plays a pivotal role in the social lives of wild Japanese macaques.
... In contrast, several theories [22][23][24] propose that EV and behavioral diversity do not necessarily drive human encephalization. These theories emphasize the role of social contexts, as suggested by the social brain hypothesis (SBH) [17,[25][26][27][28][29][30][31], and consider focus such as dietary influences [32,33]. The SBH argues that human intellectual abilities evolved in response to the selection pressures of complex social environments, which required the effective management of social relationships within and between groups. ...
The evolutionary process that led to the emergence of modern human behaviors during the Middle Stone Age in Africa remains enigmatic. While various hypotheses have been proposed, we offer a new perspective that integrates the variability selection hypothesis (VSH) with the evolution of cooperation among human groups. The VSH suggests that human adaptability to fluctuating environments was a primary force driving the development of key evolutionary traits. However, the mechanisms by which environmental variability (EV) influenced human evolution, particularly the emergence of large-scale and complex cooperative behaviors, are not yet fully understood. To explore the connection between intensified EV and the evolution of intergroup cooperation, we analyzed three stochastic models of EV: (i) Regional Variability (RV), where resource-rich areas shift while overall resource levels remain stable; (ii) Universal Variability (UV), where overall resource levels fluctuate but resource-rich areas remain stable; and (iii) Combined Variability (CV), where both resource-rich areas shift and overall resource levels fluctuate. Our results show that RV strongly promotes cooperation, while UV has a comparatively weaker effect. Additionally, our findings indicate that the coevolution of cooperation and network structures is crucial for EVs to effectively promote cooperation. This study proposes a novel causal link between EV and the evolution of cooperation, potentially setting a new direction for both theoretical and empirical research in this field.
... Tomasello (2009) proporciona una visión de cómo y por qué las habilidades sociales y la inteligencia evolucionaron en los humanos. Como lo sugiere Dunbar (1998), el desarrollo y crecimiento del cerebro en los homínidos fue el resultado de la necesidad de procesar, manejar y recordar relaciones sociales complejas. Lo qué a su vez impulsó el desarrollo de la capacidad intelectual. ...
El trabajo explora cómo las iniciativas de descolonización de las tecnologías digitales pueden transformar la forma en que concebimos la inteligencia artificial. Por ejemplo, al imaginar una interfaz inspirada en la milpa mesoamericana en lugar de la tradicional oficina occidental, planteamos nuevas posibilidades para la innovación y la comunicación.
... From an evolutionary perspective, human intelligence has evolved through natural selection, which has favored traits that enhance survival and reproductive success. This evolutionary process has notably resulted in the development of a large brain capable of sophisticated cognitive functions, including complex thought and social interaction (Dunbar, 1998). Cultural evolution, on the other hand, has further shaped human intelligence through practices such as education, language development, and social norms. ...
This study delves into the intricate relationship between human intelligence and artificial intelligence (AI) within the realm of contemporary education. It examines the core concepts that define both forms of intelligence and explores how they intersect and complement each other in educational settings. By integrating insights from recent studies, including the impact of AI technology on environmental education, and the role of AI in enhancing cognitive development and human memory, this article highlights the transformative potential of AI in education. Additionally, it considers current trends and future prospects in AI education, emphasizing the necessity for educators to adapt and leverage these technologies to foster a more dynamic and effective learning environment. This study explores intelligence and AI through a literature review across SCOPUS, Science Direct, Google Scholar, and ERIC, using keywords like "intelligence" and "artificial intelligence." Qualitative insights are gathered from focus groups with educators and AI experts, ensuring ethical standards and employing content analysis for thematic insights. In finding of the study, AI integration in Indian education enhances personalized learning via platforms like DreamBox, predicting student performance and aiding at-risk individuals. Chatbots streamline admin tasks, democratize access to education globally, and address ethical concerns like privacy and bias, potentially transforming.
... These partners are however not randomly selected: in several species, partners of contact call exchanges are also recurrent grooming partners suggesting an affiliative bonding functions (squirrel monkeys Saimiri sciureus [12], spider monkeys Ateles geoffroyi [13], lemurs Lemur catta [14], Japanese macaques Macaca fuscata [15], bonobos Pan paniscus [16]), in some other species elders individuals are preferred and receive more responses (Campbell's monkeys Cercopithecus campbelli [17], common marmosets Callithrix jacchus [11]). These contact call exchanges are therefore often described as possible precursors to human conversations [7,18], and the parallel is even more striking when it comes to their temporal structure qualified as "turn-taking" [6]. Turn-taking in human conversations consists in the smooth exchange of short utterances between several speakers that self-select themselves to intervene while avoiding overlaps and minimizing gaps between turns [19]. ...
Several non-human primate species engage in vocal exchanges of contact calls, throughout the day in peaceful contexts. These vocal exchanges have been compared to human conversations because vocalizations are uttered in turn-taking: a temporal pattern where interlocutors minimize silences and avoid overlaps. But observing such a pattern in the spontaneous production of a species, as is the case with red-capped mangabeys (Cercocebus torquatus), is not enough to make it a rule. Another prerequisite is that the pattern is expected by the animal. Here, we conducted a playback experiment using the violation-of-expectation paradigm to test whether captive red-capped mangabeys react differently to usual vs unusual interactive temporal patterns. We played back vocal exchanges with usual minimized response time (0.5 sec), with unusual longer response time (1.5 sec) and with unusual call overlap to 12 adult captive male mangabeys. For each individual, we measured the occurrences and durations of head orientation toward the loudspeaker after the stimuli. The interest of individuals varied according to the vocal exchange temporal pattern in interaction with their age. Indeed, the older (and thus more socially experienced) an individual was, the less interested he became after an unusual vocal exchange, i.e. a vocal exchange with call overlap or with a delayed response time. These findings suggest that experience shapes attention towards more socially relevant situations, and thus that turn-taking can be qualified as a social rule.
... Primates are social beings who live in complex cooperative groups (Tomasello, 2014). The primate brain evolved in response to selective pressures exerted by the need to function in social societies (Dunbar, 1998). Pressure from the requirements to deal with complex social situations explains the presence of brain mechanisms specialized in processing social information (Deen et al., 2023). ...
Primates, as social beings, have evolved complex brain mechanisms to navigate intricate social environments. This review explores the neural bases of body perception in both human and nonhuman primates, emphasizing the processing of social signals conveyed by body postures, movements, and interactions. Early studies identified selective neural responses to body stimuli in macaques, particularly within and ventral to the superior temporal sulcus (STS). These regions, known as body patches, represent visual features that are present in bodies but do not appear to be semantic body detectors. They provide information about posture and viewpoint of the body. Recent research using dynamic stimuli has expanded the understanding of the body-selective network, highlighting its complexity and the interplay between static and dynamic processing. In humans, body-selective areas such as the extrastriate body area (EBA) and fusiform body area (FBA) have been implicated in the perception of bodies and their interactions. Moreover, studies on social interactions reveal that regions in the human STS are also tuned to the perception of dyadic interactions, suggesting a specialized social lateral pathway. Computational work developed models of body recognition and social interaction, providing insights into the underlying neural mechanisms. Despite advances, significant gaps remain in understanding the neural mechanisms of body perception and social interaction. Overall, this review underscores the importance of integrating findings across species to comprehensively understand the neural foundations of body perception and the interaction between computational modeling and neural recording.
... The differences in the social brain circuitries can be tied to the social brain hypothesis, which postulates that the size of the neocortex tends to increase with the size of social groups across humans and other primate species (Dunbar, 1998(Dunbar, , 2016Dunbar & Shultz, 2007). The human brain's size and complexity likely evolved to support advanced social information processing (Dunbar, 2009). ...
Social networks are fundamental for social interactions, with the social brain hypothesis positing that the size of the neocortex evolved to meet social demands. However, the role of fractional anisotropy (FA) in white matter (WM) tracts relevant to mentalizing, empathy, and social networks remains unclear. In this study, we investigated the relationships between FA in brain regions associated with social cognition (superior longitudinal fasciculus (SLF), cingulum (CING), uncinate fasciculus, inferior fronto-occipital fasciculus), social network characteristics (diversity, size, complexity), and empathy (cognitive, affective). We employed diffusion tensor imaging, tract-based spatial statistics, and mediation analyses to examine these associations. Our findings revealed that increased social network size was positively correlated with FA in the left SLF. Further, our mediation analysis showed that lower FA in left CING was associated with increased social network size, mediated by cognitive empathy. In summary, our findings suggest that WM tracts involved in social cognition play distinct roles in social network size and empathy, potentially implicating affective brain regions. In conclusion, our findings offer new perspectives on the cognitive mechanisms involved in understanding others' mental states and experiencing empathy within supportive social networks, with potential implications for understanding individual differences in social behavior and mental health.
... Complex environments are likely to drive selection for greater learning and memory because of increased cognitive demands and memory loads (Mettke-Hofmann, 2014). Increased physical complexity of the environment or increased social complexity stimulates and thus enhances both general and social learning and memory (Dunbar, 1998;van Praag et al., 2000). Structurally complex environments result in better memories, most likely because of the increased cognitive demand of navigating through the environment (Mettke-Hofmann, 2014). ...
Different environments place different cognitive demands on constituent taxa. Learning and memory involve cognitive processes with associated costs, and it is expected that different levels of learning will occur in taxa from different environments. Greater memory loads linked to increased environmental complexity require greater learning and memory capacities. We investigated the variation in learning and memory in sister taxa of striped mice (genus Rhabdomys ). We studied two populations each of the mesic grassland‐occurring R. d. chakae and the mostly arid‐occurring R. pumilio. We conducted two sets of experiments. (1) In a novel object recognition (NOR) test, we assessed memory by recording the duration of exploration of similar and novel objects by test mice. (2) In an associative learning task, we assessed whether mice could associate specific scents with or without a food incentive or with different quantities of the food incentive in previous training phases. We measured the latency of mice to contact scents in a two‐sample choice in the test phase. In the NOR test, R. pumilio spent less time investigating similar objects in a training trial than R. d. chakae but increased absolute exploration of the novel object when presented with a novel and a familiar object in the retention trial, suggesting a sensitization to the novel object by R. pumilio . In the associative learning experiments, R. pumilio approached the stimuli faster than R. d. chakae , whereas mice from both taxa preferred scents associated with a seed versus no seed and scents associated with 5 seeds versus 1 seed. The data provide evidence of taxon‐level differences in learning and memory, likely related to environmentally modulated personality differences between the taxa.
... Cacioppo and Patrick (2008) propose that loneliness persists due to its role in motivating individuals to establish, repair, and maintain social relationships. This theory is supported by research on primates, where larger brains were favoured in more social species (Dunbar, 1998), and on humans, where neocortex size correlated with social group size (Lewis et al., 2011). ...
Visualization, as a major approach of visual analytics, involves many human interaction techniques, especially in terms of how individuals communicate, comprehend, and interpret information. Creating visualizations is a tedious process and requires skill, but automatic data visualization technologies have made it easier to create visualizations. They completely changed the landscape of data analysis and decision-making processes. As the demand for effective and efficient visualization solutions grows across diverse sectors, researchers and practitioners have developed a plethora of autonomous systems aimed at transforming raw data into meaningful visual representations. This paper investigates the methodologies utilized by these systems, categorizing them based on machine learning approaches combined with various data inputs, template-based approach, and other technique/algorithm-based approach. We collected 31 top-tier journal papers in the field and shed light on the diverse techniques employed in generating visualizations automatically, enhancing our understanding of their capabilities, compatibility, and usability across various contexts. Our survey aims to provide insights into the strengths, limitations, and potential areas for future exploration in automatic data visualization, offering guidance to practitioners, researchers, and developers in selecting appropriate techniques for their specific needs and datasets. By systematically examining these systems and pinpointing areas for improvement, we contribute to the advancement and refinement of automatic data visualization methodologies, fostering progress in this dynamically evolving domain.
... While it is often stated that long-distance vocal communication facilitates inter-group spacing and prevents aggressive encounters (Ydenberg et al. 1988), studies demonstrating the existence of such socio-spatial cognitive abilities associated to voice recognition skills remain rare. If applied comparatively to more captive and field settings, notably with species living in different social systems, this paradigm could enhance our understanding of the forces driving the coevolution of communicative and socio-spatial cognitive capacities in animals, as predicted by the "social brain" hypothesis (Dunbar 1998). ...
Abstract Recognizing individuals auditorily is of primal importance
in maintaining socio-spatial cohesion among conspecifics
within a social group as well as for regulating space
use among neighbours, particularly for species dwelling in
forests where visual communication is constrained. This study
evaluates the capacity of black howler monkeys (Alouatta
pigra) in the Palenque National Park, Mexico, to recognize
the voices of individual neighbours, using a violation-ofexpectation
paradigm based on the spatial congruence of
voices. First, we assessed intra- vs inter-individual acoustic
variations by comparing the acoustic structures of the loud
calls of six adult males from three different social groups.
Although the acoustic structures of barks were more individually
discriminative than those of roars, both loud call types
presented significant individual variations. Second, playbacks
of sequences composed of barks and roars were studied in
order to assess the auditory recognition capacity of six
neighbouring groups. Two test situations were presented to
each study group: the spatial location of the speaker was either
congruent (in the appropriate neighbouring territory) or incongruent (in a territory on the opposite side) with the voice
broadcast. Monkeys reacted significantly more (e.g. faster
approach, more vocal responses) in incongruent situations.
Our data suggest that black howler monkeys display individual
acoustic variations and are capable of recognizing the
voices of non-group members. Our experimental paradigm
is an easily replicable way to investigate inter-group voice
recognition in animals and to test the extent of socio-spatial
cognitive abilities.
... Key words: ecosystem services, human well-being, millennium ecosystem assessment, socio-ecological approach, international comparison, structural equation modeling 2008;2009;Costanza et al., 2014;2016199820112011;Costanza et al., 2014Benjamin et al., 2012Millennium Ecosystem Assessment, 2005: Fig. 1 Dunbar, 1998Oishi and Graham, 2010;Schug et al., 2010; Millennium Ecosystem As- 2. Result of structural equation modeling applied to analyze linkages among five factors of human well-being. All data from three countries n 1208 was pooled for the analysis to examine basic structure of linkages among the five factors of human well-being. ...
In order to evaluate how the marine ecosystems and social environments affect human well-being, feeling of satisfaction according to the five components of human well-being defined by the Millennium Ecosystem Assessment (Security, Basic material for good life, Health, Good social relations, and Freedom of choice and action) was examined by means of questionnaires. Structural Equation Modeling (SEM) analysis was applied to visualize the basic structure of human well-being and to compare among three Asian countries (Japan, Korea and Indonesia) which are highly dependent on fisheries. The SEM analysis showed that the three countries shared a common basic structure of the human well-being with the five components interacting with each other. However, the intensity of interaction between each component differed among the three countries. “Good social relationship” strongly influences “Freedom of choice and action” as the most important component in Japan and Korea, while “Health” does in Indonesia. Consideration of the differences in the structure of human well-being among the countries is suggested to be important for better conservation and management of marine ecosystems.
... Further, another consequence of encephalisation, as observed in Anthropoid primates, is a strong correlation between increase in brain capacity and group size (Barton, 1996;Dunbar, 1998) and when this view is expanded to hominins (Aiello & Dunbar, 1993; see also Dunbar, 2009) it appears that there is some proof for the link between encephalisation, group size and hence an increasing order of socialisation. ...
How did our distant ancestors defend themselves from lethal African predators after they moved from the trees to the ground and started sleeping in the open?
Strangely, this important question of human evolutionary history has been largely ignored by scholars. For Charles Darwin, humans did not need to defend themselves from predators, as they evolved via sexual selection in a predator-free environment; For Raymond Dart human ancestors were ruthless killers and cannibals, the apex predators of their entire environment, so the need for a defense from predators seemed irrelevant; Charles Brain proposed that, on the contrary, our ancestors were weak prey species, vulnerable to a large number of predators in Africa. Contemporary scholars mostly argue over two paradigms: (1) our ancestors were big game hunter-gatherers (partly modified Dart’s “Killer Ape” hypothesis), and (2) our ancestors were fearless aggressive scavengers (this idea was developed within the “new archaeology” paradigm of the 1980s, but the questions like how our ancestors managed to take kill away from powerful African predators and sleep on the ground at night, still remain open).
On June 23-26, 2023, an international muti-disciplinary conference “Defense Strategies in Early Human Evolution” took place at the Jim Corbett International Research Centre at the Grigol Robakidze University, Tbilisi, Georgia. The conference brought together behavioural ecologists, primatologists, biologists, cognitivists, philosophers, evolutionary musicologists, and conservationists, who were discussing various issues of this vast topic. The book that you hold in your hands is the result of this meeting.
... For example, the EQ of sperm whales ranges between 0.57 (large males) and 1.01 (females), a difference driven by body size, not brain size (Cozzi et al., 2016). One may also note that female sperm whales lead a social life in communities, whereas adult males do not and are often solitary, which could be hypothesized relevant to brain size in line with ideas about social complexity driving the evolution of bigger brains (Dunbar, 1998). But this must be explored further. ...
Since the early days of neuroanatomy, the brains of dolphins and whales have attracted attention for their large volume, unusual shape, and intense gyrification. Progress toward describing the central nervous system of cetaceans has been aptly summarized in several seminal articles and reviews. While the authors of these papers have been largely in agreement regarding the key features of dolphin neural organization, there is ongoing and unsettled controversy concerning the relationship between dolphin brains and empathy, social organization, and ultimately the intelligence of these fascinating species. The functional characteristics of the cetacean brain, which are central to these sorts of cognitive and behavioral questions, rely not just on settled anatomical understanding but also on ongoing and incomplete exploration into cetacean neurophysiology. In this chapter, we will briefly summarize what uncontroversial facts are known regarding dolphin (and whale) brains and highlight unsolved issues, with a particular attention to neurophysiology.
... The human brain has experienced substantial growth, especially in regions like the neocortex, which is vital for higher cognitive functions including social cognition (93). Evolutionary biologists suggest that the increasing complexity of human social interactions drove the expansion and specialization of these brain regions, coining the term "social brain" (94). ...
This article presents a novel theoretical perspective on the role of cognitive biases within the autism and schizophrenia spectrum by integrating the evolutionary and computational approaches. Against the background of neurodiversity, cognitive biases are presented as primary adaptive strategies, while the compensation of their shortcomings is a potential cognitive advantage. The article delineates how certain subtypes of autism represent a unique cognitive strategy to manage cognitive biases at the expense of rapid and frugal heuristics. In contrast, certain subtypes of schizophrenia emerge as distinctive cognitive strategies devised to navigate social interactions, albeit with a propensity for overdetecting intentional behaviors. In conclusion, the paper emphasizes that while extreme manifestations might appear non-functional, they are merely endpoints of a broader, primarily functional spectrum of cognitive strategies. The central argument hinges on the premise that cognitive biases in both autism and schizophrenia spectrums serve as compensatory mechanisms tailored for specific ecological niches.
... One of the theoretical foundations for such inter-specific studies lies in the field of socio-cognitive research. This area of science has its roots in the 'social brain hypothesis' [20, 21] and examines systems where complex cognitive and social mechanisms are reciprocally connected. The study of pet–human communication is a particularly dynamic example of such research. ...
All social animals influence each other's behaviour. One area of particular interest is the social interaction that occurs between pets and their owners. Within pet–owner dyads, food and feeding are always part of the dyadic ritual. In this review, we hypothesize that feeding can be considered to be a push–pull relationship where pets are, at least in part, able to 'negotiate' with their owner to influence 'when', 'what' and 'how much' they are fed. We examine the evidence that supports this hypothesis by appraising similar studies of other animals and the pre-verbal human infant. First, we review the differences in approaches and methodologies that exist between disciplines within the behavioural sciences. Second, the feeding behaviour of neonatal wild animals and pre-verbal infants is examined in terms of its causation, ontogeny, phylogeny and adaptation. Finally, the resulting knowledge concerning begging as honest signals of need, scramble competition, re-conciliation and consolation is applied to domestic pets with the objective of understanding of how owners are influenced by the feeding behaviour of their pets. Review Methodology: We searched the following sources: Scopus, Google Scholar, Google Books (keyword search terms used: pet, begging, bird and altruism). In addition we used the references from the articles obtained by this method to check for additional relevant material.
... Up to now, most of the birds tested for self-recognition have been social species, such as magpies and crows (Prior et al., 2008;Soler et al., 2014;Buniyaadi et al., 2020), trained pigeons (Uchino & Watanabe, 2014), sparrows (Kraft et al., 2017), and the Kea and Goffin's cockatoos (van Buuren et al., 2019), as well as the recent studies of African grey parrots (Lin et al., 2021) and Adélie penguins (Dastidar et al., 2022). In general, a capacity for Mirror Self-Recognition (MSR) is considered to be more likely in animals with well-developed social skills, in line with Dunbar's (1998) Social Brain Hypothesis. Some authors nevertheless believe that the Encephalisation Quotient (EQ) also plays an important role in cognitive development (Shultz & Dunbar, 2010) and, of all the animals that passed the test for MSR, magpies have the highest EQ, with a brain that corresponds to approximately 3% of its body weight (Prior et al., 2008). ...
Self-recognition is the ability of an animal to identify itself when observing its reflected image. Although many species have been tested, self-recognition has only been confirmed conclusively in a few taxa. We presented five Rosy-faced lovebirds, Agapornis roseicollis, with their own image using a mirror and applied the mark test, attaching a black sticker to each bird’s throat. We evaluated the potential tactile effect of the mark by attaching a transparent sticker to the bird’s throat. The results were analysed using Generalised Linear Mixed Models, which showed that four of five birds touched the black mark more than the transparent mark. There was no evidence that the birds could see the mark without the assistance of the mirror. The results of the study provide encouraging evidence that Agapornis roseicollis is able to recognise itself in a mirror and is the first parrot species to pass the mark test.
... Sociability, or increased social interactions which required navigation of complex social networks, has been proposed as the primary driver behind the increase in brain size in the Pleistocene (Dunbar, 1998). Other scholars argue for other key factorsdespecially diet (Agam and Barkai, 2016). ...
... Thus, even for H. sapiens there are really several Dunbar numbers. Dunbar (2020) develops the point and modifies the "series of values" given in Dunbar (1998). He now gives a benchmark value of 1,500 for tribe size. ...
A long tradition explains technological change as recombination. Within this tradition, this Element develops an innovative combinatorial model of technological change and tests it with 2,000 years of global GDP data and with data from US patents filed between 1835 and 2010. The model explains 1) the pace of technological change for a least the past two millennia, 2) patent citations and 3) the increasing complexity of tools over time. It shows that combining and modifying pre-existing goods to produce new goods generates the observed historical pattern of technological change. A long period of stasis was followed by sudden super-exponential growth in the number of goods. In this model, the sudden explosion of about 250 years ago is a combinatorial explosion that was a long time in coming, but inevitable once the process began at least two thousand years ago. This Element models the Industrial Revolution as a combinatorial explosion.
E-communities, social groups interacting online, have recently become an object of interdisciplinary research. As with face-to-face meetings, Internet exchanges may not only include factual information but also emotional information - how participants feel about the subject discussed or other group members. Emotions are known to be important in affecting interaction partners in offline communication in many ways. Could emotions in Internet exchanges affect others and systematically influence quantitative and qualitative aspects of the trajectory of e-communities? The development of automatic sentiment analysis has made large scale emotion detection and analysis possible using text messages collected from the web. It is not clear if emotions in e-communities primarily derive from individual group members' personalities or if they result from intra-group interactions, and whether they influence group activities. We show the collective character of affective phenomena on a large scale as observed in 4 million posts downloaded from Blogs, Digg and BBC forums. To test whether the emotions of a community member may influence the emotions of others, posts were grouped into clusters of messages with similar emotional valences. The frequency of long clusters was much higher than it would be if emotions occurred at random. Distributions for cluster lengths can be explained by preferential processes because conditional probabilities for consecutive messages grow as a power law with cluster length. For BBC forum threads, average discussion lengths were higher for larger values of absolute average emotional valence in the first ten comments and the average amount of emotion in messages fell during discussions. Our results prove that collective emotional states can be created and modulated via Internet communication and that emotional expressiveness is the fuel that sustains some e-communities.
Have you ever wondered what skills you need to make friends?
How your brain processes the information that you need to make
friends? What features of your daily life make having friends difficult? Primates are the mammals that are most similar to us in the animal kingdom. Primates face similar challenges to humans when it comes to making friends. Primates must understand the goals and intentions of others to make friends. However, the stress they experience in their environments can make understanding others’ goals and intentions difficult. Stress causes primates to switch from understanding goals to understanding behavior alone, meaning they respond only to input from their senses. To overcome this challenge, primates use sounds
and gestures when making friends. These are called intentional
communication, and they motivate animals to figure out the goals
of other animals by using their knowledge of past interactions.
Knowing how primates communicate to make friends can help us to understand how humans make friends, too.
Current societal challenges exceed the capacity of humans operating either alone or collectively. As AI evolves, its role within human collectives will vary from an assistive tool to a participatory member. Humans and AI possess complementary capabilities that, together, can surpass the collective intelligence of either humans or AI in isolation. However, the interactions in human-AI systems are inherently complex, involving intricate processes and interdependencies. This review incorporates perspectives from complex network science to conceptualize a multilayer representation of human-AI collective intelligence, comprising cognition, physical, and information layers. Within this multilayer network, humans and AI agents exhibit varying characteristics; humans differ in diversity from surface-level to deep-level attributes, while AI agents range in degrees of functionality and anthropomorphism. We explore how agents’ diversity and interactions influence the system’s collective intelligence and analyze real-world instances of AI-enhanced collective intelligence. We conclude by considering potential challenges and future developments in this field.
Mirror neurons (MNs) represent a class of neurons that are activated when performing or observing the same action. Given their role in social cognition and previous research in patients with psychiatric disorders, we proposed that the human MN system (MNS) might display different pathways for social and non-social actions. To examine this hypothesis, we conducted a comprehensive meta-analysis of 174 published human functional magnetic resonance imaging studies. Our findings confirmed the proposed hypothesis. Our results demonstrated that the non-social MN pathway exhibited a more classical pattern of frontoparietal activation, whereas the social MN pathway was activated less in the parietal lobe but more in the frontal lobe, limbic lobe, and sublobar regions. Additionally, our findings revealed a modulatory role of the effector (i.e. face and hands) within this framework: some areas exhibited effector-independent activation, while others did not. This novel subdivision provides valuable theoretical support for further investigations into the neural mechanisms underlying the MNS and its related disorders.
Cognition serves to resolve uncertainty. Living in social groups is widely seen as a source of uncertainty driving cognitive evolution, but sociality can also mitigate sources of uncertainty, reducing the need for cognition. Moreover, social systems are not simply external selection pressures, but rather arise from the decisions individuals make regarding who to interact with and how to behave. Thus, an understanding of how and why cognition evolves requires careful consideration of the co-evolutionary feedback loop between cognition and sociality. Here, we adopt ideas from information theory to evaluate how potential sources of uncertainty differ across species and social systems. Whereas cognitive research often focuses on identifying human-like abilities in other animals, we instead emphasise that animals need to make adaptive decisions to navigate socio-ecological trade-offs. These decisions can be viewed as feedback loops between perceiving and acting on information, which shape individuals’ immediate social interactions, and scale up to generate the structure of societies. Emerging group-level characteristics such as social structure, communication networks, and culture in turn produce the context in which decisions are made and so shape selection on the underlying cognitive processes. Thus, minds shape societies and societies shape minds.
Despite decades of comparative studies, puzzling aspects of the relationship between mammalian brain and body mass continue to defy satisfactory explanation. Here we show that several such aspects arise from routinely fitting log-linear models to the data: the correlated evolution of brain and body mass is in fact log-curvilinear. This simultaneously accounts for several phenomena for which diverse biological explanations have been proposed, notably variability in scaling coefficients across clades, low encephalization in larger species and the so-called taxon-level problem. Our model implies a need to revisit previous findings about relative brain mass. Accounting for the true scaling relationship, we document dramatically varying rates of relative brain mass evolution across the mammalian phylogeny, and we resolve the question of whether there is an overall trend for brain mass to increase through time. We find a trend in only three mammalian orders, which is by far the strongest in primates, setting the stage for the uniquely rapid directional increase ultimately producing the computational powers of the human brain.
Brain size varies greatly across and even within lineages. Attempts to explain this variation have mostly focused on the role of specific cognitive demands in the social or ecological domain. However, their predictive power is modest, whereas the effects of additional functions, especially sensory information processing and motor control, on brain size remain underexplored. Here, using phylogenetic comparative models, we show that the socio-cognitive and eco-cognitive demands do not have direct links to relative brain size (that is the residual from a regression against body mass) once morphological features are taken into account. Thus, specific cognitive abilities linked to social life or ecology play a much smaller role in brain size evolution than generally assumed. Instead, parental provisioning, generation length, and especially eye size and beak and leg morphology have a strong direct link to relative brain size. Phylogenetic lability analyses suggest that morphological diversification preceded changes in the rate of brain size evolution and greater visual input, and thus that morphological diversification opened up specialized niches where efficient foraging could produce energy surpluses. Increases in brain size provided general behavioural flexibility, which improved survival by reducing interspecific competition and predation, and was made possible by intense parental provisioning. Indeed, comparative analyses in a subset of species show that thicker beaks are associated with larger size of brain regions involved in behavioural flexibility (telencephalon, pallium). Thus, morphological evolution had a key role in niche diversification, which subsequently may have facilitated the evolution of general cognitive flexibility.
Sociality has been argued to be the main selection pressure for the evolution of large brains and complex behavior on the basis of data from mammals and birds. Coleoid cephalopods have large brains, complex nervous systems and show signs of intelligent behavior comparable to that of birds, cetaceans, and primates. However, many cephalopods live largely solitary, semelparous, and short lives, leaving little to no opportunity for parental care, complex group dynamics, or social learning. A formal model is needed that takes these factors into consideration. Here we test the formal model of the “Asocial Brain Hypothesis” on cephalopod molluscs. We compiled a database of brain size, ecology, behavior, sociality, and life history from 3933 publications on the 79 species of octopus, squid, and cuttlefish for which comparable brain data is available. We analyze these data using an updated phylogeny and Bayesian multilevel models. In a set of pre- registered statistical analyses derived from the predictions of the “Asocial Brain Hypothesis” formal model, we find a large effect of habitat, suggesting ecology as a primary selection pressure on brain size in cephalopods. We also find evidence of a positive relationship between brain size and number of predator groups and no relationship between brain size and sociality.
These results are inconsistent with social explanations for brain evolution but consistent with ecological explanations. They emphasize the need for new theories to explain the evolution of brains more generally, including in the cephalopods, which diverged from vertebrates over 500 million years ago.
The root cause of human conflict needs to be understood but it is currently unknown whether the decision to engage in conflict is an inherited or acquired trait. This article reports two experimental simulations which demonstrate that the level of confrontation in a population of simple organisms can be explained by the evolution of a simulated gene pool. Game theory and evolutionary algorithms were combined in a novel way to examine how six variables influenced the decision to confront in the competition for resources. The main variable was how the genetically determined rate of confrontation evolved as a function of environmental resources and cost of a conflict. The additional modulatory effects of four other variables were also considered in the first round of simulations. Two variables were responsive to the difference between resources and cost. Two other variables were responsive to the organism's health status. Taking a systematic approach, we examined how a population of 1000 organisms were evolving in environments with different levels of reward and punishment. During each cycle, each organism was paired with another organism and thus needed to decide whether to confront or cooperate. We used a genetic algorithm to simulate the evolution of the gene pool over 500 cycles. The first series of simulations demonstrated that the baseline rate of confrontation was very responsive to environmental conditions. Our results also indicate that the decision to confront or cooperate depended not only upon the immediate competitive conditions, in which the organisms evolved, but were also responsive to their own health status. The second series of simulations used zero‐sum games to explore how risk levels varied as a function of the potential cost of engaging in a confrontation. In the second round of simulations, a simple form of memory was implemented. The results indicated that memory had a limited, but significant effect, while the cost of a conflict was highly predictive of the level of risk taken by the organisms. Our two series of simulations show that AI could contribute to answering psychological and societal questions. Our unique combination of techniques has brought to light several new insights into the mechanisms that drive the population towards cooperation and confrontation. The degree of generalizability of our results and future avenues for deepening our understanding of these evolutionary dynamics are discussed.
This chapter highlights a simple but important principle for understanding the
evolution of cooperation in our species. This principle is that below a certain
population level, societies can make collective decisions without formal institutions
of power. Once a certain threshold is reached, however, more formal
institutions are required in order to signal trust, the basis of sustained cooperation
as articulated by Elinor Ostrom and others in the last few decades.
Data on the number of adults that an individual contacts at least once a month in a set of British populations yield estimates of network sizes that correspond closely to those of the typical "sympathy group" size in humans. Men and women do not differ in their total network size, but women have more females and more kin in their networks than men do. Kin account for a significantly higher proportion of network members than would be expected by chance. The number of kin in the network increases in proportion to the size of the family; as a result, people from large families have proportionately fewer non-kin in their networks, suggesting that there is either a time constraint or a cognitive constraint on network size. A small inner clique of the network functions as a support group from whom an individual is particularly likely to seek advice or assistance in time of need. Kin do not account for a significantly higher proportion of the support clique than they do for the wider network of regular social contacts for either men or women, but each sex exhibits a strong preference for members of their own sex.
Group size covaries with relative neocortical volume in nonhuman primates. This regression equation predicts a group size for modern humans very similar to that for hunter-gatherer and traditional horticulturalist societies. Similar group sizes are found in other contemporary and historical societies. Nonhuman primates maintain group cohesion through social grooming; among the Old World monkeys and apes, social grooming time is linearly related to group size. Maintaining stability of human-sized groups by grooming alone would make intolerable time demands. It is therefore suggested (1) that the evolution of large groups in the human lineage depended on developing a more efficient method for time-sharing the processes of social bonding and (2) that language uniquely fulfills this requirement. Data on the size of conversational and other small interacting groups of humans accord with the predicted relative efficiency of conversation compared to grooming as a bonding process. In human conversations about 60% of time is spent gossiping about relationships and personal experiences. Language may accordingly have evolved to allow individuals to learn about the behavioural characteristics of other group members more rapidly than was feasible by direct observation alone.
This paper examines some of the factors which determine how people know each other and is a preliminary attempt to discover the rules which govern such interactions. An informant-defined experiment was conducted to elicit the information about a person needed by individuals in a small U.S. university town to choose which of their acquaintances was most likely to know that person. We found, as with a previous experiment, that knowledge of the person's location, occupation, hobbies, organizations, age, sex, and marital status was sufficient for this task. These seven facts were then provided for 500 mythical persons spread evenly around the world except that 100 of them supposedly lived in the United States. Forty informants then told us, for each name on the list, whom they knew who was most likely to know that person and why. We found that the data differed little from those of our previous studies in other parts of the United States, suggesting that the instruments is reliable. Of the choices, 86% were friends, 64% male; choices were predominantly made on the basis of the listed person's location or occupation. Factor analysis of similarity matrices based on informant response has allowed categorization for world locations, occupations, and hobbies. Some 23 location categories, 12 ocupation categories, and 13 hobby categories were found. The implications of our findings are discussed in the framework of work in other cultures.
The tacit assumption that relative enlargement and differentiation of brains reflect a progressive evolutionary trend toward greater intelligence is a major impediment to the study of brain evolution. Theories that purport to establish a linear scale for this presumed correlation between brain size and intelligence are undermined by the absence of an unbiased allometric baseline for estimating differences in encephalization, by the incompatibility of allometric analyses at different taxonomic levels, by the nonlinearity of the criterion of subtraction used to partition the somatic and cognitive components of encephalization, and by the failure to independently demonstrate any cognitive basis for the regularity of brain/body allometry. Analyzing deviations from brain/body allometric trends in terms of encephalization obfuscates the complementarity between brain and body size and ignores selection on body size, which probably determines most deviations. By failing to analyze the effects of allometry at many levels of structure, comparative anatomists have mistaken methodological artifacts for progressive evolutionary trends. Many structural changes, which are assumed to demonstrate progression of brain structure from primitive to advanced forms, are the results of allometric processes. Increased brain size turns out to have some previously unappreciated functional disadvantages.
The mental map of wild chimpanzees is analyzed in the context of their transports of clubs and stones used for cracking two
species of nuts of different hardness,Coula edulis andPanda oleosa, in the Tai National Park (Ivory Coast). For the harderPanda nuts, they transport the harder hammers, i.e., almost exclusively stones, hammers of greater weight, and the transports are
longer than forCoula nuts. The analysis made for the transports forPanda nuts shows that they seem to remember the location of stones and to choose the stones so as to keep the transport distance
minimal. The chimpanzees seem to possess an Euclidian space, which allows them to somehow measure and remember distances;
to compare several such distances so as to choose the stone with the shortest distance to a goal tree; to correctly locate
a new stone location with reference to different trees; and to change their reference point so as to measure the distance
to eachPanda tree from any stone location. They also combine the weight and the distance. The wild chimpanzees of the Tai National Park
seem to possess concrete operation abilities in spatial representation.
The visual perspective-taking ability of 4 chimpanzees (Pan troglodytes) was investigated. The subjects chose between information about the location of hidden food provided by 2 experimenters who randomly alternated between two roles (the guesser and the knower). The knower baited 1 of 4 obscured cups so that the subjects could watch the process but could not see which of the cups contained the reward. The guesser waited outside the room until the food was hidden. Finally, the knower pointed to the correct cup while the guesser pointed to an incorrect one. The chimpanzees quickly learned to respond to the knower. They also showed transfer to a novel variation of the task, in which the guesser remained inside the room and covered his head while the knower stood next to him and watched a third experimenter bait the cups. The results are consistent with the hypothesis that chimpanzees are capable of modeling the visual perspectives of others.
In a study of 52 individuals belonging to 35 species or subspecies of passerine birds it was shown that the volume of the hippocampal complex relative to brain and body size is significantly larger in species that store food than in species that do not. Retrieval of stored food relies on an accurate and long-lasting spatial memory, and hippocampal damage disrupts memory for storage sites. The results suggest, therefore, that food-storing species of passerines have an enlarged hippocampal complex as a specialization associated with the use of a specialized memory capacity. Other life-history variables were examined and found not to be correlated with hippocampal volume.
This paper examines relationships between brain size (relative to body size) and differences in ecology and behavior within the order Carnivora. After removing the effects of body size (either body weight or head and body length) significant differences in brain size exist among families. Variation in relative brain size across the order and comparative brain size within families might relate to differences in diet (carnivores and omnivores have larger brain sizes than insectivores) and breeding group type. These findings are discussed and compared with those found in small mammals (rodents, insectivores, lagomorphs), primates and bats.
Two explanations for species differences in neonatal brain size in eutherian mammals relate the size of the brain at birth to maternal metabolic rate. Martin (1981, 1983) argued that maternal basal metabolic rate puts an upper bound on the mother's ability to supply energy to the fetus, thereby limiting neonatal brain size. Hofman (1983) proposed that gestation length in mammals is constrained by maternal metabolic rate, implying an indirect constraint on neonatal brain size. Since individuals of precocial species have much larger neonatal brain sizes and are gestated longer for a given maternal body size than individuals of altricial species, Martin's and Hofman's ideas also require that mothers of precocial offspring have higher metabolic rates for their body sizes than mothers of altricial offspring. Data on 116 mammal species from 13 orders show that neither neonatal brain size nor gestation length is correlated with maternal metabolic rate when maternal body-size effects are removed. For a given maternal size, there is no difference in metabolic rates between precocial and altricial species, despite a two-fold difference between them in average neonatal brain size. However, neonatal brain size is strongly correlated with gestation length and litter size, independently of maternal size and metabolic rate. Analyses conducted within orders replicated the findings for gestation length and suggested that neonatal brain size may be at best only weakly related to metabolic rate. Differences in neonatal brain size appear to have evolved primarily with species differences in gestation length and litter size but not with differences in metabolic rate; large-brained offspring are typically produced from litters of one that have been gestated for a long time relative to maternal size. We conclude that species differences in relative neonatal brain size reflect different life-history tactics rather than constraints imposed by metabolic rate.
In this paper we propose a typology for classifying object manipulation and tool use. We then classify tool use as context specific or intelligent tool use on the basis of criteria drawn from Piaget's Sensorimotor Intelligence Series in human infants. In an extension of Hamilton's hypothesis we argue that intelligent tool use and tertiary sensorimotor intelligence in cebus monkeys and great apes is an adaptation for feeding on a variety of seasonally limited embedded food sources, while context specific tool use is an adaptation for feeding on one class of embedded food sources. We also argue that the evolution of specific object manipulation schemata must be considered separately from the evolution of intelligence.
The hypothesis that intelligence is an adaptation to deal with the complexity of living in semi-permanent groups of conspecifics, a situation that involves the potentially tricky balance of competition and cooperation with the same individuals, has been influential in recent theorizing about human mental evolution. It is important to distinguish among distinct versions of this general idea, for they predict different cognitive consequences and apply to different species of animal. Empirical support is strong in primates for links between (i) social complexity based on evolved tactics that require a good memory for socially relevant information, (ii) neocortical enlargement, and (iii) size of social groupings. However, the evolution of computational thought and the ability to understand other individuals' intentions are not well explained as products of selection for Machiavellian intelligence. Quite different explanations may therefore be required for increases in intelligence that occurred at different times in human ancestry.
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Primates use social grooming to service coalitions and it has been suggested that these directly affect the fitness of their members by allowing them to reduce the intrinsic costs associated with living in large groups. We tested two hypotheses about the size of grooming cliques that derive from this suggestion: (1) that grooming clique size should correlate with relative neocortex size and (2) that the size of grooming cliques should be proportional to the size of the groups they have to support. Both predictions were confirmed, although we show that, in respect of neocortex size, there are as many as four statistically distinct grades within the primates (including humans). Analysis of the patterns of grooming among males and females suggested that large primate social groups often consist of a set of smaller female subgroups (in some cases, matrilinearly based coalitions) that are linked by individual males. This may be because males insert themselves into the interstices between weakly bonded female subgroups rather than because they actually hold these subunits together.
In this paper, the analysis of the factors influencing the evolution of neocortex size in primates given in Dunbar (1992) is extended in three specific ways. (1) An independent test is undertaken of the hypothesis that group size is a function of relative neocortex size in primates by using estimates of neocortex size to predict group size for those species that were not involved in the original analysis. The results confirm the results of the earlier analysis. (2) A more satisfactory test is attempted of the alternative hypothesis that species which differ in the degree of extractive foraging also differ in relative neocortex size. This particular version of the hypothesis is rejected. (3) These results are used to identify the "cognitive" group size for those species of baboons that live in multi-layered social systems.
Our book examines the mechanisms that underlie social behavior and communication in East African vervet monkeys. Our goal is to describe the sophistication of primate intelligence and to probe its limits. We suggest that vervets and other primates make good primatologists. They observe social interactions, recognize the relations that exist among others, and classify relationships into types. Monkeys also use sounds to represent features of their environment and compare different vocalizations according to their meaning. However, while monkeys may use abstract concepts and have motives, beliefs, and desires, their mental states are apparently not accessible: they do not know what they know. In addition, monkeys seem unable to attribute mental states to others: they lack a "theory of mind." Their inability to examine their own mental states or to attribute mental states to others severely constrains their ability to transmit information or to deceive one another. It also limits the extent to which their vocalizations can be called semantic. Finally, the skills that monkeys exhibilt in social behavior are apparently domain specific. For reasons that are presently unclear, vervets exhibit adaptive specializations in social interactions that are not extended to their interactions with other species (although they should be).
The social brain hypothesis predicts that species with relatively larger neocortices should exhibit more complex social strategies than those with smaller neocortices. We test this prediction using data on the correlation between male rank and mating success for polygamous primates. This correlation is negatively related to neocortex size, as would be predicted if males of species with large neocortices are more effective at exploiting social opportunities to undermine the dominant male's power-based monopolisation of peri-ovulatory females than are those with smaller neocortices. This effect is shown to be independent of the influence of male cohort size.
reviews evidence that complex patterns of alliance make primate contests more intellectually demanding than those of other animals and, in arguing that this has led to primates' greater relative brain size, challenges students of non-primates to produce better comparative data (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Tactical deception occurs when an individual is able to use an “honest” act from his normal repertoire in a different context to mislead familiar individuals. Although primates have a reputation for social skill, most primate groups are so intimate that any deception is likely to be subtle and infrequent. Published records are sparse and often anecdotal. We have solicited new records from many primatologists and searched for repeating patterns. This has revealed several different forms of deceptive tactic, which we classify in terms of the function they perform. For each class, we sketch the features of another individual's state of mind that an individual acting with deceptive intent must be able to represent, thus acting as a “natural psychologist.” Our analysis will sharpen attention to apparent taxonomic differences. Before these findings can be generalized, however, behavioral scientists must agree on some fundamental methodological and theoretical questions in the study of the evolution of social cognition.
Mean body weights of baboons differ considerably between populations for both males and females. This paper examines possible environmental causes of these differences. Mean annual rainfall and mean annual temperature are shown to be the two main factors responsible. Mean body weights for both sexes are a quadratic function of rainfall. Possible reasons why this might be so are examined.
Fifty-five million years ago, a furry, hoofed mammal about the size of a dog ventured into the shallow brackish remnant of the Tethys Sea and set its descendants on a path that would lead to their complete abandonment of the land. These early ancestors of cetaceans (dolphins, porpoises, and whales) thereafter set on an evolutionary course that is arguably the most unusual of any mammal that ever lived. Primates and cetaceans, because of their adaptation to exclusively different physical environments, have had essentially nothing to do with each other throughout their evolution as distinct orders. In fact, the closest phylogenetic relatives of cetaceans are even-toed ungulates.
The ability to understand and conceptualize the mental processes of other people is considered to play a vital role in social interactions. Deficits in this area, sometimes known as theory-of-mind (ToM) deficits, have been identified as playing a possible causal role in autism, Asperger's syndrome and schizophrenic disorders, particularly paranoia. Paranoia has also been associated with an abnormal attributional style, an observation that suggests that ToM and attributional processes may be related phenomena. This paper describes a study examining the relationship between attributional processes and ToM deficits. Seventy-seven undergraduate participants completed a ToM task and forty-six also completed the Internal, Personal and Situational Attributions Questionnaire (IPSAQ). ToM deficits were associated with an increased tendency to identify other individuals as responsible for negative social situations. The implications of the observed relationship between attributions and ToM deficits are discussed.
Recent hypotheses that variation in brain size among birds and mammals result from differences in metabolic allocation during ontogeny are tested.
Indices of embryonic and post-embryonic brain growth are defined. Precocial birds and mammals have high embryonic brain growth indices which are compensated for by low post-embryonic indices (with the exception of Homo supiens). In contrast, altricial birds and mammals have low embryonic and high post-embryonic indices. Altricial birds have relatively small brains at hatching and develop relatively large brains as adults, but among mammals there is no equivalent correlation between variation in adult relative brain sizes and state of neonatal development.
Compensatory brain development in both birds and mammals is associated with compensatory parental metabolic allocation. In comparison with altricial development, precocial development is characterized by higher levels of brain growth and parental metabolic allocation prior to hatching or birth and lower levels subsequently. Differences between degrees of postnatal investment by the parents in the young of precocial birds versus precocial mammals may result in the different patterns of adult brain size associated with precociality versus altriciality in the two groups.
The allometric exponent scaling brain on body size differs among taxonomic levels in birds. The exponent is higher for some parts of the brain than others, irrespective of taxonomic level. Unlike mammals, the exponents for birds do not show a general increase with taxonomic level. These pattcrns call into question recent interpretations of the allometric exponent in birds. and the reason for changes in exponent with taxonomic level.
The relationships between the relative size of the neocortex and differences in social structures were examined in prosimians
and anthropoids. The relative size of the neocortex (RSN) of a given congeneric group in each superfamily of primates was
measured based on the allometric relationships between neocortical volume and brain weight for each superfamily, to control
phylogenetic affinity and the effects of brain size. In prosimians, “troop-making” congeneric groups (N=3) revealed a significantly larger RSN than solitary groups (N=6), and there was a significant, positive correlation between RSN and troop size. In the case of anthropoids, polygynous/frugivorous
groups (N=5) revealed a significantly larger RSN than monogynous/frugivorous groups (N=8). Furthermore, a significant, positive correlation between RSN and troop size was found for frugivorous congeneric groups
of the Ceboidea. These results suggest that neocortical development is associated with differences in social structure among
primates.
Two general kinds of theory (one ecological and one social) have been advanced to explain the fact that primates have larger brains and greater congnitive abilities than other animals. Data on neocortex volume, group size and a number of behavioural ecology variables are used to test between the various theories. Group size is found to be a function of relative neocortical volume, but the ecological variables are not. This is interpreted as evidence in favour of the social intellect theory and against the ecological theories. It is suggested that the number of neocortical neurons limits the organism's information-processing capacity and that this then limits the number of relationships that an individual can monitor simultaneously. When a group's size exceeds this limit, it becomes unstable and begins to fragment. This then places an upper limit on the size of groups which any given species can maintain as cohesive social units through time. The data suggest that the information overload occurs in terms of the structure of relationships within tightly bonded grooming cliques rather than in terms of the total number of dyads within the group as a whole that an individual has to monitor. It thus appears that, among primates, large groups are created by welding together sets of smaller grooming cliques. One implication of these results is that, since the actual group size will be determined by the ecological characteristics of the habitat in any given case, species will only be able to invade habitats that require larger groups than their current limit if they evolve larger neocortices.
Understanding of second-order belief structures by 5- and 10-year-old children was assessed in acted stories in which two characters (John and Mary) were independently informed about an object's (ice-cream van's) unexpected transfer to a new location. Hence both John and Mary knew where the van was but there was a mistake in John's second-order belief about Mary's belief: “John thinks Mary thinks the van is still at the old place”. Children's understanding of this second-order belief was tested by asking “Where does John think Mary will go for ice cream?” Correct answers could only be given if John's second-order belief was represented, since all shortcut reasoning based on first-order beliefs would have led to the wrong answer. Results suggested unexpected early competence around the age of 6 and 7 years, shown under optimal conditions when inference of second-order beliefs was prompted.
It is taken for granted in human societies that men
are, on average, slightly taller, larger and heavier than
women, despite a considerable overlap in their respective
weight distributions. However, among mammals in general,
intersexual size differences within a single species do
not always favour males and range from leopard seals, with
the female 20% longer and correspondingly heavier than the
conspecific male, to gorillas with the male almost twice
the size of his mate.
There is ample evidence that body size plays a
fundamental role in relation to an animal's survival.
Consequently, when males and females of the same species
attain different adult body weights, these should be seen
in the overall context of divergent life history
strategies, as emphasised by the typically later
achievement of sexual maturity in the larger bodied sex.
Most explanations of sexual size dimorphism in
primates tend to be male-centred. They typically emphasize
competition between males for females and protection of
the social group by larger bodied males. However, such
accounts are commonly marred by circular arguments and
post hoc rationalisations. They are also self-defeating in
their neglect of the possible effects of natural selection
acting on females. The present research examines the
ontogeny of sexual size dimorphism in terms of the
divergent energetic needs of males and females.
An allometric approach has been adopted, and the
frustrations of circularity overcome by exploiting the
special relation which exists between brain size and body
weight. The results indicate that, at least for simian
primates, body size reduction in females has played a major role in the evolution of sexual size dimorphism. For several
species of larger bodied primates this difference has
apparently been enhanced by body size increase in males. The
scaling of molar tooth area with body weight corroborates
these findings.
Interpersonal spacing and bodily contact in public situations, were observed within the camps of the G/wi San. In an isolated camp composed of one family, the mother was in close proximity with all other members. In the mixed camps, the San were in far more frequent proximity with the same sex than with the opposite sex. The mode of distance between persons of the same sex was 0.1-1.3 m, while it was far longer between males and females other than ones' spouse. Of the body parts, the foot was most frequently involved in unintentional contact-states. Grooming behavior was usually performed by females toward juveniles or other females, while males never groomed females. The primary function of grooming toward juveniles was maternal care or reassurance, while between females, it functioned as a sociable transaction; particularly as a 'service' by the younger toward the elder. Males were in proximity with each other irrespective of kinship, while proximity and contact preferentially occurred between females, or between males and females of consanguineous kin. Proximity and physical contact were avoided between siblings or siblings-in-law of the opposite sex. Physical contact was strongly avoided between in-laws belonging to adjacent generations. However, proximity and contact generally occurred irrespectively of the relationship between generations.
Allometry should be defined broadly as the study of size and its consequences, not narrowly as the application of power functions to the data of growth. Variation in size may be ontogenetic, static or phyletic. Errors of omission and treatment have plagued the study of allometry in primates. Standard texts often treat brain size as an independent measure, ignoring its allometric relation with body size - on this basis, gracile australopithecines have been accorded the mental status of gorillas. Intrinsic allometries of the brain/body are likewise neglected: many authors cite cerebral folding as evidence of man's mental superiority, but folding is a mechanical correlate of brain size itself. Confusion among types of scaling heads errors of treatment in both historical primacy [Dubois' ontogenetic inferences from interspecific curves] and current frequency. The predicted parameters of brain-body plots differ greatly for ontogenetic, intrapopulational, interspecific and phyletic allometries. I then discuss basic trends in bivariate allometry at the ordinal level for internal organ weights, skeletal dimensions, lifespan and fetal weight. In considering the causes of basic bivariate allometries, I examine the reason for differences among types of scaling in brain-body relationships. The interspecific exponent of 0.66 strongly suggests a relationship to body surfaces, but we have no satisfactory explanation for why this should be so. The tripartite ontogenetic plot is a consequence of patterns in neuronal differentiation. We do not know why intraspecific exponents fall between 0.2 and 0.4; several partial explanations have been offered. Multivariate techniques have transcended the pictorial representation of transformed coordinates and offer new, powerful approaches to total allometric patterns. Allometry is most often used as a 'criterion for subtraction'. In order to assess the nature and purpose of an adaptation, we must be able to identify and isolate the aspect of its form that depends both upon its size and the size of the body within which it resides. Cranial indices and limb lengths are misinterpreted when authors apply no correction for body size. The search for a criterion of subtraction has been most diligently pursued in studies of the brain. Clearly, brain size must be assessed by comparison with a 'standard' animal of the same body size. But how shall size be measured, especially in fossils; and how shall a standard animal be construed. I discuss and criticize three methods recently used: RADINSKY'S foramen magnum criterion; Jerison's minimum convex polygons and cephalization quotients; and the indices of progression in comparison with 'basal' insectivores' of BAUCHOT, Stephan and their colleagues.
Some animals have larger brains than others, but it is not yet known why. Species differences in life-style, including dietary
habits and patterns of development of the young, are associated with variation in brain weight, independently of the effects
of body weight and evolutionary history. Taken together with behavioral and neuroanatomical analyses, these studies begin
to suggest the evolutionary pressures that favor different sized brains and brain components.
Social relationships are integral to the behaviour of many mammalian species. Primates are unusual in that their social relationships are extensive within groups, which often contain many reproductively active males and females. Several hypotheses have been forwarded to explain the ultimate causation of primate sociality. While attention has focused on grooming as a proximate factor influencing social relationships, the neural basis of such behaviour has not been investigated in monkeys. This report presents changes in the brain's opioid system contingent on grooming in monkeys. Opiates themselves have a feedback interaction with grooming behaviour, as revealed from the administration of opiate agonists and antagonists. Opiate receptor blockade increases the motivation to be groomed, while morphine administration decreases it. These data support the view that brain opioids play an important role in mediating social attachment and may provide the neural basis on which primate sociality has evolved.