Dynamic Relationships between Information Transmission and Social Connections

Female social dynamics as viewed from grooming networks in the Central Himalayan Langur (Semnopithecus schistaceus)

Enhanced survival and reproduction are associated with an individual's direct and indirect social connections with members of a group. Yet, the role of these connections is little known in a vast range of primate species. We studied female Central Himalayan Langur (CHL) to investigate the link between four specific attributes (dominance rank, age, genetic relatedness, and the presence of females carrying infants) and a female's direct and indirect social relationships. By analyzing grooming networks, we revealed different behavioral strategies: high-ranking females form relationships with many females (high degree), whereas females with dependent infants have strong relationships (high strength and eigenvector). Subadult females are important individuals that hold the social network together (high betweenness), while an immigrant female strategy is to integrate herself into the group by forming strong bonds with females who themselves have strong bonds (high eigenvector). Our study sheds light on how behavioral strategies shape female CHL grooming networks, which may help them to secure fitness and survival advantages.

Testing the information centre hypothesis in a multilevel society

In various animal species conspecifics aggregate at sleeping sites. Such aggregations can act as information centres where individuals acquire up-to-date knowledge about their environment. In some species, communal sleeping sites comprise individuals from multiple groups, where each group maintains stable membership over time. We used GPS tracking to simultaneously record group movement in a population of wild vulturine guineafowl (Acryllium vulturinum) to investigate whether communal sleeping sites can facilitate the transfer of information among individuals across distinct groups. These birds live in large and stable groups that move both together and apart, often forming communal roosts containing up to five groups. We first test whether roosts provide the opportunity for individuals to acquire information from members of other groups by examining the spatial organization at roosts. The GPS data reveal that groups intermix, thereby providing an opportunity for individuals to acquire out-group information. We next conduct a field experiment to test whether naïve groups can locate novel food patches when co-roosting with knowledgeable groups. We find that co-roosting substantially increases the chances for the members of a naïve group to discover a patch known to individuals from other groups at the shared roost. Further, we find that the discovery of food patches by naïve groups subsequently shapes their space use and inter-group associations. We also draw on our long-term tracking to provide examples that demonstrate natural cases where communal roosting has preceded large-scale multi-group collective movements that extend into areas beyond the groups' normal ranges. Our findings support the extension of the information centre hypothesis to communal sleeping sites that consist of distinct social groups.

The role of social attraction and social avoidance in shaping modular networks

How interactions between individuals contribute to the emergence of complex societies is a major question in behavioural ecology. Nonetheless, little remains known about the type of immediate social structure (i.e. social network) that emerges from relationships that maximize beneficial interactions (e.g. social attraction towards informed individuals) and minimize costly relationships (e.g. social avoidance of infected group mates). We developed an agent-based model where individuals vary in the degree to which individuals signal benefits versus costs to others and, on this basis, choose with whom to interact depending on simple rules of social attraction (e.g. access to the highest benefits) and social avoidance (e.g. avoiding the highest costs). Our main findings demonstrate that the accumulation of individual decisions to avoid interactions with highly costly individuals, but that are to some extent homogeneously beneficial, leads to more modular networks. On the contrary, individuals favouring interactions with highly beneficial individuals, but that are to some extent homogeneously costly, lead to less modular networks. Interestingly, statistical models also indicate that when individuals have multiple potentially beneficial partners to interact with, and no interaction cost exists, this also leads to more modular networks. Yet, the degree of modularity is contingent upon the variability in benefit levels held by individuals. We discuss the emergence of modularity in the systems and their consequences for understanding social trade-offs.

How self-disclosure of negative experiences shapes prosociality?

People frequently share their negative experiences and feelings with others. Little is known, however, about the social outcomes of sharing negative experiences and the underlying neural mechanisms. We addressed this dearth of knowledge by leveraging functional near-infrared spectroscopy (fNIRS) hyperscanning: while dyad participants took turns to share their own (self-disclosure group) or a stranger's (non-disclosure group) negative and neutral experiences, their respective brain activity was recorded simultaneously by fNIRS. We observed that sharing negative (relative to neutral) experiences enhanced greater mutual prosociality, emotional empathy and interpersonal neural synchronization (INS) at the left superior frontal cortex in the self-disclosure group compared to the non-disclosure group. Importantly, mediation analyses further revealed that in the self-disclosure (but not non-disclosure) group, the increased emotional empathy and INS elicited by sharing negative experiences relative to sharing neutral experiences promoted the enhanced prosociality through increasing interpersonal liking. These results indicate that self-disclosure of negative experiences can promote prosocial behaviors via social dynamics (defined as social affective and cognitive factors, including empathy and liking) and shared neural responses. Our findings suggest that when people express negative sentiments, they incline to follow up with positive actions.

Octopus vulgaris Exhibits Interindividual Differences in Behavioural and Problem-Solving Performance

By presenting individual Octopus vulgaris with an extractive foraging problem with a puzzle box, we examined the possible correlation between behavioural performances (e.g., ease of adaptation to captive conditions, prevalence of neophobic and neophilic behaviours, and propensity to learn individually or by observing conspecifics), biotic (body and brain size, age, sex) and abiotic (seasonality and place of origin) factors. We found more neophilic animals showing shorter latencies to approach the puzzle box and higher probability of solving the task; also, shorter times to solve the task were correlated with better performance on the individual learning task. However, the most neophilic octopuses that approached the puzzle box more quickly did not reach the solution earlier than other individuals, suggesting that strong neophilic tendency may lead to suboptimal performance at some stages of the problem-solving process. In addition, seasonal and environmental characteristics of location of origin appear to influence the rate of expression of individual traits central to problem solving. Overall, our analysis provides new insights into the traits associated with problem solving in invertebrates and highlights the presence of adaptive mechanisms that promote population-level changes in octopuses' behavioural traits.

Individual and Population Age Impact Social Behavior and Network Structure in a Long-Lived Insect

AbstractSocial behaviors vary among individuals, and social networks vary among groups. Understanding the causes of such variation is important for predicting or altering ecological processes such as infectious disease outbreaks. Here, we ask whether age contributes to variation in social behavior at multiple levels of organization: within individuals over time, among individuals of different ages, among local social environments, and among populations. We used experimental manipulations of captive populations and a longitudinal dataset to test whether social behavior is associated with age across these levels in a long-lived insect, the forked fungus beetle (Bolitotherus cornutus). In cross-sectional analyses, we found that older beetles were less connected in their social networks. Longitudinal data confirmed that this effect was due in part to changes in behavior over time; beetles became less social over 2 years, possibly because of increased social selectivity or reproductive investment. Beetles of different ages also occupied different local social neighborhoods. The effects of age on behavior scaled up: populations of older individuals had fewer interactions, fewer but more variable relationships, longer network path lengths, and lower clustering than populations of young individuals. Age therefore impacted not only individual sociality but also the network structures that mediate critical population processes.

Preferential associations in an unstable social network: applying social network analysis to a dynamic sow herd

Preferential associations are fitness-enhancing ties between individuals, documented in a range of taxa. Despite this, research into preferential associations remains underrepresented in commercial species, particularly pigs. This study investigates the development of preferential associations in a dynamic sow herd. Preferential associations were defined as approaching a resting sow and then sitting or lying with physical contact with the selected sow, separated by < 1 m from the head or directly next to her, with interaction tolerated for > 60 s. For individual identification, each sow was marked with colored dots, stripes, or both, corresponding to their ear-tag number. Preferential associations were measured over one production cycle of 21 days. Behavioral observations took place on 7 days of the study, with 3 h of behavior per day recorded during peak activity times (08:00-09:00, 15:00-16:00, 20:00-21:00 h). Behaviors were recorded using five cameras, each positioned within the barn to provide coverage of the functional areas. The network metrics applied included in-degree centrality (received ties), out-degree centrality (initiated ties), centralization (the extent to which an individual is central within the network), clustering coefficient (a measure of tie strength), and the E-I Index (a measure of assortment by trait: parity, familiarity, and sociality). Individuals were added and removed during the study, so the centrality metrics of missing sows were weighted. To describe the structure of the network, brokerage typologies were applied. Brokerage typologies include five positions, including coordinators, gatekeepers, representatives, consultants, and liaisons. The results revealed social discrimination in assortment by connectedness even when ties were not reciprocal, and the most connected sows were significantly more likely to be approached than less connected individuals. The most connected sows had significantly higher in-degree and out-degree centrality. With the application of brokerage typologies, the results showed a relationship between connectedness and brokering type, with the most connected sows predominantly engaging in coordinating behavior. The results suggest that the motivation for discrimination in the unstable preferential association network was not founded upon bidirectional interactions. These findings highlight the complexities involved when forming social preferences and present a platform for further exploring the motivations for preferential associations among intensively farmed pigs.

Social learning mechanisms shape transmission pathways through replicate local social networks of wild birds

The emergence and spread of novel behaviours via social learning can lead to rapid population-level changes whereby the social connections between individuals shape information flow. However, behaviours can spread via different mechanisms and little is known about how information flow depends on the underlying learning rule individuals employ. Here, comparing four different learning mechanisms, we simulated behavioural spread on replicate empirical social networks of wild great tits and explored the relationship between individual sociality and the order of behavioural acquisition. Our results reveal that, for learning rules dependent on the sum and strength of social connections to informed individuals, social connectivity was related to the order of acquisition, with individuals with increased social connectivity and reduced social clustering adopting new behaviours faster. However, when behavioural adoption depends on the ratio of an individuals' social connections to informed versus uninformed individuals, social connectivity was not related to the order of acquisition. Finally, we show how specific learning mechanisms may limit behavioural spread within networks. These findings have important implications for understanding whether and how behaviours are likely to spread across social systems, the relationship between individuals' sociality and behavioural acquisition, and therefore for the costs and benefits of sociality.

Social network inheritance and differentiation in wild baboons

Immatures' social development may be fundamental to understand important biological processes, such as social information transmission through groups, that can vary with age and sex. Our aim was to determine how social networks change with age and differ between sexes in wild immature baboons, group-living primates that readily learn socially. Our results show that immature baboons inherited their mothers' networks and differentiated from them as they aged, increasing their association with partners of similar age and the same sex. Males were less bonded to their matriline and became more peripheral with age compared to females. Our results may pave the way to further studies testing a new hypothetical framework: in female-philopatric societies, social information transmission may be constrained at the matrilineal level by age- and sex-driven social clustering.

Neurocomputational mechanism of real-time distributed learning on social networks

Social networks shape our decisions by constraining what information we learn and from whom. Yet, the mechanisms by which network structures affect individual learning and decision-making remain unclear. Here, by combining a real-time distributed learning task with functional magnetic resonance imaging, computational modeling and social network analysis, we studied how humans learn from observing others' decisions on seven-node networks with varying topological structures. We show that learning on social networks can be approximated by a well-established error-driven process for observational learning, supported by an action prediction error encoded in the lateral prefrontal cortex. Importantly, learning is flexibly weighted toward well-connected neighbors, according to activity in the dorsal anterior cingulate cortex, but only insofar as social observations contain secondhand, potentially intertwining, information. These data suggest a neurocomputational mechanism of network-based filtering on the sources of information, which may give rise to biased learning and the spread of misinformation in an interconnected society.

A conceptual framework to predict social information use based on food ephemerality and individual resource requirements

Environmental variability poses a range of challenges to foraging animals trying to meet their energetic needs. Where food patches are unpredictable but shareable, animals can use social information to locate patches more efficiently or reliably. However, resource unpredictability can be heterogeneous and complex. The behavioural strategies animals employ to exploit such resources also vary, particularly if, when, and where animals use available social information. We reviewed the literature on social information use by foraging animals and developed a novel framework that integrates four elements - (1) food resource persistence; (2) the relative value of social information use; (3) behavioural context (opportunistic or coordinated); and (4) location of social information use - to predict and characterize four strategies of social information use - (1) local enhancement; (2) group facilitation; (3) following; and (4) recruitment. We validated our framework by systematically reviewing the growing empirical literature on social foraging in bats, an ideal model taxon because they exhibit extreme diversity in ecological niche and experience low predation risk while foraging but function at high energy expenditures, which selects for efficient foraging behaviours. Our framework's predictions agreed with the observed natural behaviour of bats and identified key knowledge gaps for future studies. Recent advancements in technology, methods, and analysis will facilitate additional studies in bats and other taxa to further test the framework and our conception of the ecological and evolutionary forces driving social information use. Understanding the links between food distribution, social information use, and foraging behaviour will help elucidate social interactions, group structure, and the evolution of sociality for species across the animal kingdom.

Social information use shapes the coevolution of sociality and virulence

Social contacts can facilitate the spread of both survival-related information and infectious diseases, but little is known about how these processes combine to shape host and parasite evolution. Here, we use a theoretical model that captures both infection and information transmission processes to investigate how host sociality (contact effort) and parasite virulence (disease-associated mortality rate) (co)evolve. We show that selection for sociality (and in turn, virulence) depends on both the intrinsic costs and benefits of social information and infection as well as their relative prevalence in the population. Specifically, greater sociality and lower virulence evolve when the risk of infection is either low or high and social information is neither very common nor too rare. Lower sociality and higher virulence evolve when the prevalence patterns are reversed. When infection and social information are both at moderate levels in the population, the direction of selection depends on the relative costs and benefits of being infected or informed. We also show that sociality varies inversely with virulence, and that parasites may be unable to prevent runaway selection for higher contact efforts. Together, these findings provide new insights for our understanding of group living and how apparently opposing ecological processes can influence the evolution of sociality and virulence in a range of ways.

Sharing Happy Stories Increases Interpersonal Closeness: Interpersonal Brain Synchronization as a Neural Indicator

Our lives revolve around sharing emotional stories (i.e., happy and sad stories) with other people. Such emotional communication enhances the similarity of story comprehension and neural across speaker-listener pairs. The theory of Emotions as Social Information Model (EASI) suggests that such emotional communication may influence interpersonal closeness. However, few studies have examined speaker-listener interpersonal brain synchronization (IBS) during emotional communication and whether it is associated with meaningful aspects of the speaker-listener interpersonal relationship. Here, one speaker watched emotional videos and communicated the content of the videos to 32 people as listeners (happy/sad/neutral group). Both speaker and listeners’ neural activities were recorded using EEG. After listening, we assessed the interpersonal closeness between the speaker and listeners. Compared with the sad group, sharing happy stories showed a better recall quality and a higher rating of interpersonal closeness. The happy group showed higher IBS in the frontal cortex and left temporoparietal cortex than the sad group. The relationship between frontal IBS and interpersonal closeness was moderated by sharing happy/sad stories. Exploratory analysis using support vector regression (SVR) showed that the IBS could also predict the ratings of interpersonal closeness. These results suggest that frontal IBS could serve as an indicator of whether sharing emotional stories facilitate interpersonal closeness. These findings improve our understanding of emotional communication among individuals that guides behaviors during interpersonal interactions.

Biosociological ethodiversity in the social system

A comprehensive understanding of human sociality needs to embrace the coevolution of genes and culture. Recent advances in biological research about niche construction by organisms, and the development of the concepts of social niche and ethodiversity, can be integrated into a common approach to understand this coevolution, which implies the interaction between sociology and ecology in an integrative framework of knowledge. In this paper the authors propose such inclusive biosociological and heuristic framework to improve the understanding of the evolution of social niche construction. In addition, it allows a better understanding of the concept of sociotype in non-human organisms and explains some aspects of the social or presocial behavior through the concept of ethodiversity.

Social network position predicts male mating success in a small passerine

Individuals differ in the quantity and quality of their associations with conspecifics. The resulting variation in the positions that individuals occupy within their social environment can affect several aspects of life history, including reproduction. While research increasingly shows how social factors can predict dyadic mating patterns (who will breed with whom), much less is known about how an individual's social position affects its overall likelihood to acquire mating partner(s). We studied social networks of socially monogamous blue tits (Cyanistes caeruleus) to investigate whether the number and strength of connections to opposite-sex conspecifics, the ratio between same- and opposite-sex connections, and the tendency to move between social groups in the months prior to breeding affect individuals' success in acquiring 1) a breeding partner and 2) an extrapair partner. After controlling for differences in spatial location, we show that males that moved more often between social groups were more likely to acquire a breeding partner. Moreover, adult males that associated with more females were more likely to sire extrapair young. The number of female associates also predicted the proportion of familiar female breeding neighbors, suggesting that familiarity among neighbors may facilitate opportunities for extrapair matings. In females, none of the network metrics significantly predicted the likelihood of acquiring a breeding or extrapair partner. Our study suggests that the positioning of males within their social environment prior to breeding can translate into future mating success, adding an important new dimension to studies of (extrapair) mating behavior.

Follow the leader? Orange-fronted conures eavesdrop on conspecific vocal performance and utilise it in social decisions

Animals regularly use social information to make fitness-relevant decisions. Particularly in social interactions, social information can reduce uncertainty about the relative quality of conspecifics, thus optimising decisions on with whom and how to interact. One important resource for individuals living in social environments is the production of information by signalling conspecifics. Recent research has suggested that some species of parrots engage in affiliative contact call matching and that these interactions may be available to conspecific unintended receivers. However, it remains unclear what information third parties may gain from contact call matching and how it can be utilised during flock decisions. Here, using a combined choice and playback experiment, we investigated the flock fusion choices and vocal behaviour of a social parrot species, the orange-fronted conure (Eupsittula canicularis), to a contact call matching interaction between two individuals of different sexes and with different vocal roles. Our results revealed that orange-fronted conures chose to follow vocal leaders more often than vocal followers during fusions. Furthermore, flocks responded with higher call rates and matched the stimulus calls closer when subsequently choosing a vocal leader. Interestingly, orange-fronted conures also showed higher contact call rates and closer matches when choosing males over females. These results suggest that paying attention to conspecific contact call interactions can provide individuals with social information that can be utilised during fission and fusion events, significantly influencing the social dynamics of orange-fronted conures.

Animal cognition in an urbanised world

Explaining how animals respond to an increasingly urbanised world is a major challenge for evolutionary biologists. Urban environments often present animals with novel problems that differ from those encountered in their evolutionary past. To navigate these rapidly changing habitats successfully, animals may need to adjust their behaviour flexibly over relatively short timescales. These behavioural changes, in turn, may be facilitated by an ability to acquire, store and process information from the environment. The question of how cognitive abilities allow animals to avoid threats and exploit resources (or constrain their ability to do so) is attracting increasing research interest, with a growing number of studies investigating cognitive and behavioural differences between urban-dwelling animals and their non-urban counterparts. In this review we consider why such differences might arise, focusing on the informational challenges faced by animals living in urban environments, and how different cognitive abilities can assist in overcoming these challenges. We focus largely on birds, as avian taxa have been the subject of most research to date, but discuss work in other species where relevant. We also address the potential consequences of cognitive variation at the individual and species level. For instance, do urban environments select for, or influence the development of, particular cognitive abilities? Are individuals or species with particular cognitive phenotypes more likely to become established in urban habitats? How do other factors, such as social behaviour and individual personality, interact with cognition to influence behaviour in urban environments? The aim of this review is to synthesise current knowledge and identify key avenues for future research, in order to improve our understanding of the ecological and evolutionary consequences of urbanisation.

Stemming the Flow: Information, Infection, and Social Evolution

Social information and socially transmitted pathogens are governed by social structure, and also shape social interactions. However, information and infection are rarely investigated as interactive factors driving social evolution. We propose exactly such an integrative framework, drawing attention to mechanisms of social phenotypic plasticity for information spread and pathogen control.

An Integrative Dynamic Model of Colombian Population Distribution, Based on the Maximum Entropy Principle and Matter, Energy, and Information Flow

Human society has increased its capacity to exploit natural resources thanks to new technologies, which are one of the results of information exchange in the knowledge society. Many approaches to understanding the interactions between human society and natural systems have been developed in the last decades, and some have included considerations about information. However, none of them has considered information as an active variable or flowing entity in the human–natural/social-ecological system, or, moreover, even as a driving force of their interactions. This paper explores these interactions in socio-ecological systems by briefly introducing a conceptual frame focused on the exchange of information, matter, and energy. The human population is presented as a convergence variable of these three physical entities, and a population distribution model for Colombia is developed based on the maximum entropy principle to integrate the balances of related variables as macro-state restrictions. The selected variables were electrical consumption, water demand, and higher education rates (energy, matter, and information). The final model includes statistical moments for previous population distributions. It is shown how population distribution can be predicted yearly by combining these variables, allowing future dynamics exploration. The implications of this model can contribute to bridging information sciences and sustainability studies.

Cultural selection shapes network structure

Cultural evolution relies on the social transmission of cultural traits along a population's social network. Research indicates that network structure affects information spread and thus the capacity for cumulative culture. However, how network structure itself is driven by population-culture co-evolution remains largely unclear. We use a simple model to investigate how populations negotiate the trade-off between acquiring new skills and getting better at existing skills and how this trade-off shapes social networks. We find unexpected eco-evolutionary feedbacks from culture onto social networks and vice versa. We show that selecting for skill generalists results in sparse networks with diverse skill sets, whereas selecting for skill specialists results in dense networks and a population that specializes on the same few skills on which everyone is an expert. Our model advances our understanding of the complex feedbacks in cultural evolution and demonstrates how individual-level behavior can lead to the emergence of population-level structure.