Dataset Information

Using Machine Learning to Discover Latent Social Phenotypes in Free-Ranging Macaques.

ABSTRACT: Investigating the biological bases of social phenotypes is challenging because social behavior is both high-dimensional and richly structured, and biological factors are more likely to influence complex patterns of behavior rather than any single behavior in isolation. The space of all possible patterns of interactions among behaviors is too large to investigate using conventional statistical methods. In order to quantitatively define social phenotypes from natural behavior, we developed a machine learning model to identify and measure patterns of behavior in naturalistic observational data, as well as their relationships to biological, environmental, and demographic sources of variation. We applied this model to extensive observations of natural behavior in free-ranging rhesus macaques, and identified behavioral states that appeared to capture periods of social isolation, competition over food, conflicts among groups, and affiliative coexistence. Phenotypes, represented as the rate of being in each state for a particular animal, were strongly and broadly influenced by dominance rank, sex, and social group membership. We also identified two states for which variation in rates had a substantial genetic component. We discuss how this model can be extended to identify the contributions to social phenotypes of particular genetic pathways.

SUBMITTER: Madlon-Kay S

PROVIDER: S-EPMC5532604 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Using Machine Learning to Discover Latent Social Phenotypes in Free-Ranging Macaques.

Madlon-Kay Seth S Brent Lauren L Montague Michael M Heller Katherine K Platt Michael M

Brain sciences 20170721 7

Investigating the biological bases of social phenotypes is challenging because social behavior is both high-dimensional and richly structured, and biological factors are more likely to influence complex patterns of behavior rather than any single behavior in isolation. The space of all possible patterns of interactions among behaviors is too large to investigate using conventional statistical methods. In order to quantitatively define social phenotypes from natural behavior, we developed a machi ...[more]

PMID: 28754001

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Project description:While skin microbes are known to mediate human health and disease, there has been minimal research on the interactions between skin microbiota, social behavior, and year-to-year effects in non-human primates-important animal models for translational biomedical research. To examine these relationships, we analyzed skin microbes from 78 rhesus macaques living on Cayo Santiago Island, Puerto Rico. We considered age, sex, and social group membership, and characterized social behavior by assessing dominance rank and patterns of grooming as compared to nonsocial behaviors. To measure the effects of a shifting environment, we sampled skin microbiota (based on sequence analysis of the 16S rRNA V4 region) and assessed weather across sampling periods between 2013 and 2015. We hypothesized that, first, monkeys with similar social behavior and/or in the same social group would possess similar skin microbial composition due, in part, to physical contact, and, second, microbial diversity would differ across sampling periods. We found significant phylum-level differences between social groups in the core microbiome as well as an association between total grooming rates and alpha diversity in the complete microbiome, but no association between microbial diversity and measures of rank or other nonsocial behaviors. We also identified alpha and beta diversity differences in microbiota and differential taxa abundance across two sampling periods. Our findings indicate that social dynamics interact with yearly environmental changes to shape the skin microbiota in rhesus macaques, with potential implications for understanding the factors affecting the microbiome in humans, which share many biological and social characteristics with these animals. IMPORTANCE Primate studies are valuable for translational and evolutionary insights into the human microbiome. The majority of primate microbiome studies focus on the gut, so less is known about the factors impacting the microbes on skin and how their links affect health and behavior. Here, we probe the impact of social interactions and the yearly environmental changes on food-provisioned, free-ranging monkeys living on a small island. We expected animals that lived together and groomed each other would have more similar microbes on their skin, but surprisingly found that the external environment was a stronger influence on skin microbiome composition. These findings have implications for our understanding of the human skin microbiome, including potential manipulations to improve health and treat disease.

Project description:Animals born with physical impairments may particularly require behavioural flexibility and innovation to survive and carry out social activities, such as grooming. Studies on free-ranging Japanese macaques on Awaji Island, Japan, have shown that individuals with congenital limb malformations exhibited compensatory behaviours while grooming, such as increased mouth and elbow use for removing ectoparasites. The aim of this study is to explore disabled and nondisabled grooming techniques to determine whether and to what extent disabled monkeys develop novel grooming techniques, and if there is disability-associated variation in grooming efficiency. We hypothesized that modified grooming techniques used by disabled monkeys fulfilled the social and relaxing functions of grooming, however, that grooming by manually impaired individuals may still carry a hygienic cost to the recipients. Grooming behavioural data were collected by video in 2007 on 27 adult females (11 with CLMs). With a detailed grooming-related ethogram, we transcribed 216 2-minute continuous grooming video samples. We analyzed the data using generalized linear mixed effects models in R. We found that monkeys with manual impairment were less efficient groomers, as measured by removal and movement efficiency during grooming. However, there were no significant differences associated with the number of grooming movements per sample among the focal animals. Additionally, with a behavioural sequential analysis, we isolated 8 distinct grooming techniques and 3 novel disability-specific movements. Our results indicate that innovation and modification of movement types does not entirely compensate for manual disability, and that manual impairment carries a cost to the hygienic function of grooming. However, for the grooming recipient, the experience of being groomed by a disabled or nondisabled groomer is likely similar, and through movement compensation, disabled monkeys are able to engage in the social aspect of grooming without incurring any disability-associated costs.

Dataset Information

Using Machine Learning to Discover Latent Social Phenotypes in Free-Ranging Macaques.

Publications

Using Machine Learning to Discover Latent Social Phenotypes in Free-Ranging Macaques.

Similar Datasets

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