Variation in grouping patterns, mating systems and social structure: what socio-ecological models attempt to explain

Socio-ecological models aim to predict the variation in social systems based on a limited number of ecological parameters. Since the 1960s, the original model has taken two paths: one relating to grouping patterns and mating systems and one relating to grouping patterns and female social structure. Here, we review the basic ideas specifically with regard to non-human primates, present new results and point to open questions. While most primates live in permanent groups and exhibit female defence polygyny, recent studies indicate more flexibility with cooperative male resource defence occurring repeatedly in all radiations. In contrast to other animals, the potential link between ecology and these mating systems remains, however, largely unexplored. The model of the ecology of female social structure has often been deemed successful, but has recently been criticized. We show that the predicted association of agonistic rates and despotism (directional consistency of relationships) was not supported in a comparative test. The overall variation in despotism is probably due to phylogenetic grade shifts. At the same time, it varies within clades more or less in the direction predicted by the model. This suggests that the model's utility may lie in predicting social variation within but not across clades

Positive evidence for neonatal imitation:A general response, adaptive engagement

The study employed four gestural models using frame-by-frame microanalytic methods, and followed how the behaviours unfolded over time. Forty-two human newborns (0-3 days) were examined for their imitation of tongue protrusion, 'head tilt with looking up', three-finger and two-finger gestures. The results showed that all three gesture groups were imitated. Results of the temporal analyses revealed an early and a later, second stage of responses. Later responses were characterized by a suppression of similar, but non-matching movements. Perinatal imitation is not a phenomenon served by a single underlying mechanism; it has at least two different stages. An early phase is followed by voluntary matching behaviour by the neonatal infant

Making sense of social pretense: The effect of the dyad, sex and language ability in a large observational study of children’s behaviors in a social pretend play context

Pretend play with peers is purportedly an important driver of social development in the preschool period, however, fundamental questions regarding the features of children’s pretend play with a peer, and the effect of the dyad for pretend play, have been overlooked. The current study undertook detailed behavioral coding of social pretend play in 134 pairs of 5-year-old children (54% boys) in order to address three main aims: (i) describe the duration and proportion of children engaging in key social pretend play behaviors, namely, calls for attention, negotiation (comprising role assignment and joint proposals) and enactment of pretend play, (ii) examine the effect of the dyad in influencing the occurrence of different social pretend play behaviors, and (iii) assess the independent and combined effect of individual child characteristics (i.e., language ability and sex) that may influence social pretend play behaviors beyond the influence of the dyad. Results demonstrated the overwhelming effect of the dyad in shaping children’s social pretend play behaviors, with language ability and sex explaining relatively little of the total variability in play behaviors. Results are discussed considering the contribution that this type of study can make to theories of associations between children’s social development and social pretend play.LEGO Foundatio

Measuring Behavior in the Home Cage : Study Design, Applications, Challenges, and Perspectives

FUNDING This research was supported by NIH grants R00AG056662, P20GM125528, AG057424 to WS and SLPeer reviewedPublisher PD

Causal structures and causal boundaries

We give an up-to-date perspective with a general overview of the theory of causal properties, the derived causal structures, their classification and applications, and the definition and construction of causal boundaries and of causal symmetries, mostly for Lorentzian manifolds but also in more abstract settings.Comment: Final version. To appear in Classical and Quantum Gravit

High-Resolution Positional Tracking for Long-Term Analysis of Drosophila Sleep and Locomotion Using the “Tracker” Program

Drosophila melanogaster has been used for decades in the study of circadian behavior, and more recently has become a popular model for the study of sleep. The classic method for monitoring fly activity involves counting the number of infrared beam crosses in individual small glass tubes. Incident recording methods such as this can measure gross locomotor activity, but they are unable to provide details about where the fly is located in space and do not detect small movements (i.e. anything less than half the enclosure size), which could lead to an overestimation of sleep and an inaccurate report of the behavior of the fly. This is especially problematic if the fly is awake, but is not moving distances that span the enclosure. Similarly, locomotor deficiencies could be incorrectly classified as sleep phenotypes. To address these issues, we have developed a locomotor tracking technique (the “Tracker” program) that records the exact location of a fly in real time. This allows for the detection of very small movements at any location within the tube. In addition to circadian locomotor activity, we are able to collect other information, such as distance, speed, food proximity, place preference, and multiple additional parameters that relate to sleep structure. Direct comparisons of incident recording and our motion tracking application using wild type and locomotor-deficient (CASK-β null) flies show that the increased temporal resolution in the data from the Tracker program can greatly affect the interpretation of the state of the fly. This is especially evident when a particular condition or genotype has strong effects on the behavior, and can provide a wealth of information previously unavailable to the investigator. The interaction of sleep with other behaviors can also be assessed directly in many cases with this method

Incipient Social Groups: An Analysis via In-Vivo Behavioral Tracking

Social psychology is fundamentally the study of individuals in groups, yet there remain basic unanswered questions about group formation, structure, and change. We argue that the problem is methodological. Until recently, there was no way to track who was interacting with whom with anything approximating valid resolution and scale. In the current study we describe a new method that applies recent advances in image-based tracking to study incipient group formation and evolution with experimental precision and control. In this method, which we term "in vivo behavioral tracking," we track individuals' movements with a high definition video camera mounted atop a large field laboratory. We report results of an initial study that quantifies the composition, structure, and size of the incipient groups. We also apply in-vivo spatial tracking to study participants' tendency to cooperate as a function of their embeddedness in those crowds. We find that participants form groups of seven on average, are more likely to approach others of similar attractiveness and (to a lesser extent) gender, and that participants' gender and attractiveness are both associated with their proximity to the spatial center of groups (such that women and attractive individuals are more likely than men and unattractive individuals to end up in the center of their groups). Furthermore, participants' proximity to others early in the study predicted the effort they exerted in a subsequent cooperative task, suggesting that submergence in a crowd may predict social loafing. We conclude that in vivo behavioral tracking is a uniquely powerful new tool for answering longstanding, fundamental questions about group dynamics

Quick, accurate, smart: 3D computer vision technology helps assessing confined animals' behaviour

Mankind directly controls the environment and lifestyles of several domestic species for purposes ranging from production and research to conservation and companionship. These environments and lifestyles may not offer these animals the best quality of life. Behaviour is a direct reflection of how the animal is coping with its environment. Behavioural indicators are thus among the preferred parameters to assess welfare. However, behavioural recording (usually from video) can be very time consuming and the accuracy and reliability of the output rely on the experience and background of the observers. The outburst of new video technology and computer image processing gives the basis for promising solutions. In this pilot study, we present a new prototype software able to automatically infer the behaviour of dogs housed in kennels from 3D visual data and through structured machine learning frameworks. Depth information acquired through 3D features, body part detection and training are the key elements that allow the machine to recognise postures, trajectories inside the kennel and patterns of movement that can be later labelled at convenience. The main innovation of the software is its ability to automatically cluster frequently observed temporal patterns of movement without any pre-set ethogram. Conversely, when common patterns are defined through training, a deviation from normal behaviour in time or between individuals could be assessed. The software accuracy in correctly detecting the dogs' behaviour was checked through a validation process. An automatic behaviour recognition system, independent from human subjectivity, could add scientific knowledge on animals' quality of life in confinement as well as saving time and resources. This 3D framework was designed to be invariant to the dog's shape and size and could be extended to farm, laboratory and zoo quadrupeds in artificial housing. The computer vision technique applied to this software is innovative in non-human animal behaviour science. Further improvements and validation are needed, and future applications and limitations are discussed.</p