Network cohesion, group size and neocortex size in female-bonded Old World primates

Lehmann, Julia; Dunbar, Robin

doi:10.1098/rspb.2009.1409

Cited by 76 publications

(64 citation statements)

References 29 publications

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“…an individual grooms a fixed number of partners), we carried out simulations with two numbers of groomed partners, n 1 ¼5 and n 2 ¼10. These corre spond to the average and to the maximum numbers, respectively, of groomed partners found in experimental studies regardless of the group size or the species (Berman et al, 2008;Cords, 2001;Lin et al, 2008;Nakamachi and Shizawa, 2003;Silk et al, 1999;Watts 2000a,b;Kudo and Dunbar, 2001;Lehmann and Dunbar, 2009). These studies revealed that the time taken by an individual to groom a non preferred group member could be considered unimportant compared to the time taken to groom its preferred partners.…”

Section: Definitions Of Parametersmentioning

confidence: 52%

“…Indeed, large groups seem to be more sub structured. This sub grouping might be because animals delib erately invest their grooming in core coalition partners (Kudo and Dunbar, 2001;Lehmann and Dunbar, 2009). Indeed, a theoretical study on social network graphs showed a similar decrease of connec tivity according to nodes' number (Wu, 2005).…”

Section: Discussionmentioning

confidence: 99%

“…This hypothesis implies that an individual tries to develop and maintain bonds with every group member, or at least, the most of conspe cifics. However, other studies have shown that whatever the group size, an individual mainly interacts only with certain grooming partners, and does so much more than with other potential partners (Kudo and Dunbar, 2001;Lehmann and Dunbar, 2009). Individuals can therefore be considered to have a relatively fixed number of grooming partners.…”

Section: Introductionmentioning

confidence: 99%

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Group size, grooming and fission in primates: A modeling approach based on group structure

Sueur

Deneubourg²,

Petit

et al. 2011

Journal of Theoretical Biology

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a b s t r a c tIn social animals, fission is a common mode of group proliferation and dispersion and may be affected by genetic or other social factors. Sociality implies preserving relationships between group members. An increase in group size and/or in competition for food within the group can result in decrease certain social interactions between members, and the group may split irreversibly as a consequence. One individual may try to maintain bonds with a maximum of group members in order to keep group cohesion, i.e. proximity and stable relationships. However, this strategy needs time and time is often limited. In addition, previous studies have shown that whatever the group size, an individual interacts only with certain grooming partners. There, we develop a computational model to assess how dynamics of group cohesion are related to group size and to the structure of grooming relationships. Groups' sizes after simulated fission are compared to observed sizes of 40 groups of primates. Results showed that the relationship between grooming time and group size is dependent on how each individual attributes grooming time to its social partners, i.e. grooming a few number of preferred partners or grooming equally or not all partners. The number of partners seemed to be more important for the group cohesion than the grooming time itself. This structural constraint has important consequences on group sociality, as it gives the possibility of competition for grooming partners, attraction for high ranking individuals as found in primates' groups. It could, however, also have implications when considering the cognitive capacities of primates.

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Section: Definitions Of Parametersmentioning

confidence: 52%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Group size, grooming and fission in primates: A modeling approach based on group structure

Sueur

Deneubourg²,

Petit

et al. 2011

Journal of Theoretical Biology

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“…We did indeed find that the mean eigenvector centrality coefficient of groups was linked to their size, in accordance with theoretical (Bonacich 1998) and empirical (Kasper & Voelkl 2009) studies in primates. Given the different availability of potential partners, the centrality of individuals appears to decrease when group size increases (Kudo & Dunbar 2001;Lehmann & Dunbar 2009). The kinecontact coefficient was correlated with the proportion of females in groups, which is consistent with the fact that female kinship bonds in macaques are stronger than those of males.…”

Section: Discussionmentioning

confidence: 99%

A comparative network analysis of social style in macaques

et al. 2011

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In group-living species, individuals gain significant advantages from establishing an extensive network of social relationships. This results in complex organizations that are difficult to quantify in a comprehensive manner. In this respect, network analyses are an ideal means to pinpoint the overall properties of social structures, and the place of each individual within these structures. We used network measurements to investigate cross-species variations in the social style of macaques, and studied 12 groups from four species. Two species (Macaca mulatta, Macaca fuscata) were characterized by a relatively weak social tolerance, a steep gradient of dominance and a strong preference for kin. The other two species (Macaca nigra, Macaca tonkeana) were known to display higher levels of tolerance, relaxed dominance and low kinship bias. We used a centrality index based on eigenvector centrality to show that in a comparison of intolerant and tolerant species, top-ranking individuals were more central than other group members in the former species than the latter. We also found that networks had higher modularity in intolerant species, indicating that kinrelated partners interacted more frequently in subgroups of these species than in those of tolerant species. Consistently, the matrix of body contacts was more strongly correlated with the kinship matrix in intolerant species. This study demonstrates the efficiency of network methodology in detecting fine and overall contrasts in social structures, and also reveals novel dimensions in the social style of macaques.Crown

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“…For example, childhood SES predicts brain structure (46) and function (45). Likewise, the size of our social networks relates to brain structure (93,94). Given that the social environment is known to affect a wide array of biological responses (5,17,19,95), a next important goal for neuroscience will be to further understand how experience at multiple levels (e.g., culture, family, social networks, SES) affects neural structure and function (46,(96)(97)(98)(99)(100)(101).…”

Section: )mentioning

confidence: 99%

What is a representative brain? Neuroscience meets population science

Falk

Hyde

Mitchell³

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

227

191

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The last decades of neuroscience research have produced immense progress in the methods available to understand brain structure and function. Social, cognitive, clinical, affective, economic, communication, and developmental neurosciences have begun to map the relationships between neuro-psychological processes and behavioral outcomes, yielding a new understanding of human behavior and promising interventions. However, a limitation of this fast moving research is that most findings are based on small samples of convenience. Furthermore, our understanding of individual differences may be distorted by unrepresentative samples, undermining findings regarding brain-behavior mechanisms. These limitations are issues that social demographers, epidemiologists, and other population scientists have tackled, with solutions that can be applied to neuroscience. By contrast, nearly all social science disciplines, including social demography, sociology, political science, economics, communication science, and psychology, make assumptions about processes that involve the brain, but have incorporated neural measures to differing, and often limited, degrees; many still treat the brain as a black box. In this article, we describe and promote a perspective-population neuroscience-that leverages interdisciplinary expertise to (i) emphasize the importance of sampling to more clearly define the relevant populations and sampling strategies needed when using neuroscience methods to address such questions; and (ii) deepen understanding of mechanisms within population science by providing insight regarding underlying neural mechanisms. Doing so will increase our confidence in the generalizability of the findings. We provide examples to illustrate the population neuroscience approach for specific types of research questions and discuss the potential for theoretical and applied advances from this approach across areas.neuroimaging | life course | statistics | survey methodology | physics Why Population Neuroscience? How do biology, social situations, and the broader environmental context interact to guide behavior, health, and development? This question is fundamental to most, if not all, social and behavioral sciences. We argue that to effectively address the many topics that stem from this larger question across disciplines, it is necessary to (i) bring a "population perspective" to neuroscience and (ii) leverage neuroscience tools within population sciences, which are subdisciplines of many fields, areas, and departments focused on documenting and understanding the dynamics of human populations, including outcomes such as health, well-being, behavior, etc.

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Network cohesion, group size and neocortex size in female-bonded Old World primates

Cited by 76 publications

References 29 publications

Group size, grooming and fission in primates: A modeling approach based on group structure

Group size, grooming and fission in primates: A modeling approach based on group structure

A comparative network analysis of social style in macaques

What is a representative brain? Neuroscience meets population science

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