Social cognitive neuroscience and humanoid robotics

We believe that humanoid robots provide new tools to investigate human social cognition, the processes underlying everyday interactions between individuals. Resonance is an emerging framework to understand social interactions that is based on the finding that cognitive processes involved when experiencing a mental state and when perceiving another individual experiencing the same mental state overlap, both at the behavioral and neural levels. We will first review important aspects of his framework. In a second part, we will discuss how this framework is used to address questions pertaining to artificial agents’ social competence. We will focus on two types of paradigm, one derived from experimental psychology and the other using neuroimaging, that have been used to investigate humans’ responses to humanoid robots. Finally, we will speculate on the consequences of resonance in natural social interactions if humanoid robots are to become integral part of our societies.     

Self-organizing dominance hierarchies in a wild primate population

Linear dominance hierarchies, which are common in social animals, can profoundly influence access to limited resources, reproductive opportunities and health. In spite of their importance, the mechanisms that govern the dynamics of such hierarchies remain unclear. Two hypotheses explain how linear hierarchies might emerge and change over time. The ‘prior attributes hypothesis’ posits that individual differences in fighting ability directly determine dominance ranks. By contrast, the ‘social dynamics hypothesis’ posits that dominance ranks emerge from social self-organization dynamics such as winner and loser effects. While the prior attributes hypothesis is well supported in the literature, current support for the social dynamics hypothesis is limited to experimental studies that artificially eliminate or minimize individual differences in fighting abilities. Here, we present the first evidence supporting the social dynamics hypothesis in a wild population. Specifically, we test for winner and loser effects on male hierarchy dynamics in wild baboons, using a novel statistical approach based on the Elo rating method for cardinal rank assignment, which enables the detection of winner and loser effects in uncontrolled group settings. Our results demonstrate (i) the presence of winner and loser effects, and (ii) that individual susceptibility to such effects may have a genetic basis. Taken together, our results show that both social self-organization dynamics and prior attributes can combine to influence hierarchy dynamics even when agonistic interactions are strongly influenced by differences in individual attributes. We hypothesize that, despite variation in individual attributes, winner and loser effects exist (i) because these effects could be particularly beneficial when fighting abilities in other group members change over time, and (ii) because the coevolution of prior attributes and winner and loser effects maintains a balance of both effects.     

Gonadectomy negatively impacts social behavior of adolescent male primates

Social behavior changes dramatically during primate adolescence. However, the extent to which testosterone and other gonadal hormones are necessary for adolescent social behavioral development is unknown. In this study, we determined that gonadectomy significantly impairs social dominance in naturalistic settings and changes reactions to social stimuli in experimental settings. Rhesus macaques were castrated (n =  6) or sham operated (n = 6) at age 2.4 years, group-housed for 2 years, and ethograms were collected weekly. During adolescence the gonadally intact monkeys displayed a decrease in subordinate behaviors and an increase in dominant behaviors, which ultimately related to a rise in social status and rank in the dominance hierarchy. We measured monkey's reactions to emotional faces (fear, threat, neutral) of conspecifics of three ages (adult, peer, infant). Intact monkeys were faster to retrieve a treat in front of a threatening or infant face, while castrated monkeys did not show a differential response to different emotional faces or ages. No group difference in reaction to an innate fear-eliciting object (snake) was found. Approach and proximity responses to familiar vs unfamiliar conspecifics were tested, and intact monkeys spent more time proximal to a novel conspecific as compared to castrates who tended to spend more time with a familiar conspecific. No group differences in time spent with novel or familiar objects were found. Thus, gonadectomy resulted in the emergence of significantly different responses to social stimuli, but not non-social stimuli. Our work suggests that intact gonads, which are needed to produce adolescent increases in circulating testosterone, impact social behavior during adolescences in primates.     

A community model of ciliateTetrahymena and bacteriaE. coli: Part II. Interactions in a batch system

Premised on relatively simple assumptions, mathematical models like those of Monod, Pirt or Droop inadequately explain the complex transient behavior of microbial populations. In particular, these models fail to explain many aspects of the dynamics of aTetrahymena pyriformis-Escherichia coli community. In this study an alternative approach, an individual-based model, is employed to investigate the growth and interactions ofTetrahymena pyriformis andE. coli in a batch culture. Due to improved representation of physiological processes, the model provides a better agreement with experimental data of bacterial density and ciliate biomass than previous modeling studies. It predicts a much larger coexistence domain than rudimentary models, dependence of biomass dynamics on initial conditions (bacteria to ciliate biomasses ratio) and appropriate timing of minimal bacteria density. Moreover, it is found that accumulation ofE. coli sized particles andE. coli toxic metabolites has a stabilizing effect on the system.     

Towards Predictive Computational Models of Oncolytic Virus Therapy: Basis for Experimental Validation and Model Selection

Oncolytic viruses are viruses that specifically infect cancer cells and kill them, while leaving healthy cells largely intact. Their ability to spread through the tumor makes them an attractive therapy approach. While promising results have been observed in clinical trials, solid success remains elusive since we lack understanding of the basic principles that govern the dynamical interactions between the virus and the cancer. In this respect, computational models can help experimental research at optimizing treatment regimes. Although preliminary mathematical work has been performed, this suffers from the fact that individual models are largely arbitrary and based on biologically uncertain assumptions. Here, we present a general framework to study the dynamics of oncolytic viruses that is independent of uncertain and arbitrary mathematical formulations. We find two categories of dynamics, depending on the assumptions about spatial constraints that govern that spread of the virus from cell to cell. If infected cells are mixed among uninfected cells, there exists a viral replication rate threshold beyond which tumor control is the only outcome. On the other hand, if infected cells are clustered together (e.g. in a solid tumor), then we observe more complicated dynamics in which the outcome of therapy might go either way, depending on the initial number of cells and viruses. We fit our models to previously published experimental data and discuss aspects of model validation, selection, and experimental design. This framework can be used as a basis for model selection and validation in the context of future, more detailed experimental studies. It can further serve as the basis for future, more complex models that take into account other clinically relevant factors such as immune responses.     

From single cells to tissue architecture—a bottom-up approach to modelling the spatio-temporal organisation of complex multi-cellular systems

Collective phenomena in multi-cellular assemblies can be approached on different levels of complexity. Here, we discuss a number of mathematical models which consider the dynamics of each individual cell, so-called agent-based or individual-based models (IBMs). As a special feature, these models allow to account for intracellular decision processes which are triggered by biomechanical cell-cell or cell-matrix interactions. We discuss their impact on the growth and homeostasis of multi-cellular systems as simulated by lattice-free models. Our results demonstrate that cell polarisation subsequent to cell-cell contact formation can be a source of stability in epithelial monolayers. Stroma contact-dependent regulation of tumour cell proliferation and migration is shown to result in invasion dynamics in accordance with the migrating cancer stem cell hypothesis. However, we demonstrate that different regulation mechanisms can equally well comply with present experimental results. Thus, we suggest a panel of experimental studies for the in-depth validation of the model assumptions.     

Saving species in a snap: On the feasibility and efficacy of augmented reality-based wildlife interactions for conservation

Interactions with wildlife can contribute to biodiversity conservation outcomes, though safety and accessibility considerations limit animal encounters from being a viable strategy. This investigation explores the feasibility of mobile augmented reality to facilitate interactions with wildlife and encourage biodversity conservation. A mobile augmented reality experience (Snapchat lens), titled “Penguin Rescue!”, was created to allow users to rehabilitate an oil-slicked virtual penguin. Study 1 distributed the lens globally to Snapchat users (N = 63,605) who spent an average of 47 s rehabilitating the penguin; psychographic data showed pro-environmental interests were not associated with the lens’ use. Study 2 employed a within-subjects experimental design (N = 80) to examine the effects of Penguin Rescue! on conservation outcomes. Results showed that the interaction increased connectedness with the species. Moreover, social presence and plausibility served as key mechanisms contributing to environmental concern and behavioral intentions. Overall, results clarify how biophilic interactions via augmented reality can benefit biodiversity conservation.     

不同社群序位布氏田鼠的繁殖行为

在实验室条件下观察了捕自内蒙古草原的不同序位布氏田鼠的繁殖行为特征。结果表明, 雌鼠对雄性配偶存在着激烈的竞争, 高序位雌鼠获得被选择、交尾及产仔的机会最多, 较低序位雌鼠若被选择并且产仔, 则其序位将随之上升; 高序位雄鼠对各个序位雌鼠均可选择, 且在繁殖期间对同性个体表现很强的攻击性, 以获得更多的交配机会。在社群繁殖中高序位雌、雄个体的作用明显高于低序位个体, 这是布氏田鼠种群长期选择进化的生存策略。实验支持了布氏田鼠为混交制、一雄多雌的婚配制度推论。     

A critical review of the influence of oxytocin nasal spray on social cognition in humans: evidence and future directions

The past eight years of research has demonstrated that oxytocin nasal spray has a significant impact on human social cognition. The aim of this review is to provide critical comment on the literature using an information-processing framework. We provide a summary of fundamental assumptions of information-processing models and highlight an impressive range of consistent findings that demonstrate the impact of oxytocin nasal spray on social information processing. These findings include that oxytocin nasal spray improves the early conceptual detection of affect from social cues and improves the accurate appraisal of affect from social cues at elaborate and strategic levels of processing. There is some evidence that these effects may be particularly powerful for positive social cues. This review comments on inconsistent results that have been reported. We argue that such inconsistencies can, in part, be explained by variability across experiments in the degree to which potential extraneous confounds have been controlled, the different methods upon which studies assessed cognition, and the extent to which the focus of investigation has been on group-based outcomes. Finally, we argue that sound cognitive experimental methods can provide powerful tools to identify markers of response to oxytocin nasal spray that can be integrated into more complex circuitry models. The identification of robust markers has particular value in predicting behavioral and therapeutic response to intervention. This should now be a major focus for future research. This article is part of a Special Issue entitled Oxytocin, Vasopressin, and Social Behavior.     

Population Dynamics of a Salmonella Lytic Phage and Its Host: Implications of the Host Bacterial Growth Rate in Modelling

The prevalence and impact of bacteriophages in the ecology of bacterial communities coupled with their ability to control pathogens turn essential to understand and predict the dynamics between phage and bacteria populations. To achieve this knowledge it is essential to develop mathematical models able to explain and simulate the population dynamics of phage and bacteria. We have developed an unstructured mathematical model using delay-differential equations to predict the interactions between a broad-host-range Salmonella phage and its pathogenic host. The model takes into consideration the main biological parameters that rule phage-bacteria interactions likewise the adsorption rate, latent period, burst size, bacterial growth rate, and substrate uptake rate, among others. The experimental validation of the model was performed with data from phage-interaction studies in a 5 L bioreactor. The key and innovative aspect of the model was the introduction of variations in the latent period and adsorption rate values that are considered as constants in previous developed models. By modelling the latent period as a normal distribution of values and the adsorption rate as a function of the bacterial growth rate it was possible to accurately predict the behaviour of the phage-bacteria population. The model was shown to predict simulated data with a good agreement with the experimental observations and explains how a lytic phage and its host bacteria are able to coexist.     

Melanoblast proliferation dynamics during mouse embryonic development. Modeling and validation

In this paper, we are looking for mathematical modeling of mouse embryonic melanoblast proliferation dynamics, taking into account, the expression level of β‐catenin. This protein plays an important role into the whole signal pathway process. Different assumptions on some unobservable features lead to different candidate models. From real data measured, from biological experiments and from a priori biological knowledge, it was able to validate or invalidate some of the candidate models. Data assimilation and parameter identification allowed us to derive a mathematical model that is in very good agreement with biological data. As a result, the produced model can give tracks for biologists into their biological investigations and experimental evidence. Another interest is the use of this model for robust hidden parameter identification like double times or number of founder melanoblasts.     

The Walking Behaviour of Pedestrian Social Groups and Its Impact on Crowd Dynamics

Human crowd motion is mainly driven by self-organized processes based on local interactions among pedestrians. While most studies of crowd behaviour consider only interactions among isolated individuals, it turns out that up to 70% of people in a crowd are actually moving in groups, such as friends, couples, or families walking together. These groups constitute medium-scale aggregated structures and their impact on crowd dynamics is still largely unknown. In this work, we analyze the motion of approximately 1500 pedestrian groups under natural condition, and show that social interactions among group members generate typical group walking patterns that influence crowd dynamics. At low density, group members tend to walk side by side, forming a line perpendicular to the walking direction. As the density increases, however, the linear walking formation is bent forward, turning it into a V-like pattern. These spatial patterns can be well described by a model based on social communication between group members. We show that the V-like walking pattern facilitates social interactions within the group, but reduces the flow because of its “non-aerodynamic” shape. Therefore, when crowd density increases, the group organization results from a trade-off between walking faster and facilitating social exchange. These insights demonstrate that crowd dynamics is not only determined by physical constraints induced by other pedestrians and the environment, but also significantly by communicative, social interactions among individuals.     

Testing the Cognition of the Forgotten Colobines: A First Look at Golden Snub-Nosed Monkeys (Rhinopithecus roxellana)

Although our understanding of primate cognition is growing rapidly, little is known about the cognition of colobines. Here we report the results of a set of 5 experiments on colobine cognition using 17 golden snub-nosed monkeys (Rhinopithecus roxellana). These monkeys are folivores that form multilevel societies with groups of hundreds of individuals and relatively high fission–fusion dynamics. We investigated their sensitivity to human social cues and ability to inhibit impulsive behavioral responses. In three sociocognitive experiments we found that, like most other primates, they follow the gaze direction of a human demonstrator but there is no evidence that they use others’ social cues in a cooperative task to locate hidden food or in a competitive task to steal forbidden food. In two inhibitory control experiments, we found that the monkeys showed a low level of inhibitory control, comparable to that of other folivorous primates. These results suggest that phylogeny and folivory might have been important in shaping the cognition of golden snub-nosed monkeys. Moreover, this species’ large group size and relatively high fission–fusion dynamics may not have imposed a significant social challenge to their cognition, as social interactions occur mainly within basic social units.     

Evidence of Functional Protein Dynamics from X-Ray Crystallographic Ensembles

It is widely recognized that representing a protein as a single static conformation is inadequate to describe the dynamics essential to the performance of its biological function. We contrast the amino acid displacements below and above the protein dynamical transition temperature, T_D∼215K, of hen egg white lysozyme using X-ray crystallography ensembles that are analyzed by molecular dynamics simulations as a function of temperature. We show that measuring structural variations across an ensemble of X-ray derived models captures the activation of conformational states that are of functional importance just above T_D, and they remain virtually identical to structural motions measured at 300K. Our results highlight the ability to observe functional structural variations across an ensemble of X-ray crystallographic data, and that residue fluctuations measured in MD simulations at room temperature are in quantitative agreement with the experimental observable.     

Cell‐fate determination in Myxococcus xanthus development: Network dynamics and novel predictions

Myxococcus xanthus is a myxobacterium that exhibits aggregation and cellular differentiation during the formation of fruiting bodies. Therefore, it has become a valuable model system to study the transition to multicellularity via cell aggregation. Although there is a vast set of experimental information for the development on M. xanthus, the dynamics behind cell‐fate determination in this organism's development remain unclear. We integrate the currently available evidence in a mathematical network model that allows to test the set of molecular elements and regulatory interactions that are sufficient to account for the specification of the cell types that are observed in fruiting body formation. Besides providing a dynamic mechanism for cell‐fate determination in the transition to multicellular aggregates of M. xanthus, this model enables the postulation of specific mechanisms behind some experimental observations for which no explanations have been provided, as well as new regulatory interactions that can be experimentally tested. Finally, this model constitutes a formal basis on which the continuously emerging data for this system can be integrated and interpreted.     

Social cognition and psychopathology: a critical overview

The philosophical and interdisciplinary debate about the nature of social cognition, and the processes involved, has important implications for psychiatry. On one account, mindreading depends on making theoretical inferences about another person''s mental states based on knowledge of folk psychology, the so-called “theory theory” (TT). On a different account, “simulation theory” (ST), mindreading depends on simulating the other''s mental states within one''s own mental or motor system. A third approach, “interaction theory” (IT), looks to embodied processes (involving movement, gesture, facial expression, vocal intonation, etc.) and the dynamics of intersubjective interactions (joint attention, joint action, and processes not confined to an individual system) in highly contextualized situations to explain social cognition, and disruptions of these processes in some psychopathological conditions. In this paper, we present a brief summary of these three theoretical frameworks (TT, ST, IT). We then focus on impaired social abilities in autism and schizophrenia from the perspective of the three approaches. We discuss the limitations of such approaches in the scientific studies of these and other pathologies, and we close with a short reflection on the future of the field. In this regard we argue that, to the extent that TT, ST and IT offer explanations that capture different (limited) aspects of social cognition, a pluralist approach might be best.     

Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single‐species time series

Predicting population extinction risk is a fundamental application of ecological theory to the practice of conservation biology. Here, we compared the prediction performance of a wide array of stochastic, population dynamics models against direct observations of the extinction process from an extensive experimental data set. By varying a series of biological and statistical assumptions in the proposed models, we were able to identify the assumptions that affected predictions about population extinction. We also show how certain autocorrelation structures can emerge due to interspecific interactions, and that accounting for the stochastic effect of these interactions can improve predictions of the extinction process. We conclude that it is possible to account for the stochastic effects of community interactions on extinction when using single‐species time series.     

Assessing Mathematical Models of Influenza Infections Using Features of the Immune Response

The role of the host immune response in determining the severity and duration of an influenza infection is still unclear. In order to identify severity factors and more accurately predict the course of an influenza infection within a human host, an understanding of the impact of host factors on the infection process is required. Despite the lack of sufficiently diverse experimental data describing the time course of the various immune response components, published mathematical models were constructed from limited human or animal data using various strategies and simplifying assumptions. To assess the validity of these models, we assemble previously published experimental data of the dynamics and role of cytotoxic T lymphocytes, antibodies, and interferon and determined qualitative key features of their effect that should be captured by mathematical models. We test these existing models by confronting them with experimental data and find that no single model agrees completely with the variety of influenza viral kinetics responses observed experimentally when various immune response components are suppressed. Our analysis highlights the strong and weak points of each mathematical model and highlights areas where additional experimental data could elucidate specific mechanisms, constrain model design, and complete our understanding of the immune response to influenza.     

Female dominance over males in primates: self-organisation and sexual dimorphism

The processes that underlie the formation of the dominance hierarchy in a group are since long under debate. Models of self-organisation suggest that dominance hierarchies develop by the self-reinforcing effects of winning and losing fights (the so-called winner-loser effect), but according to 'the prior attribute hypothesis', dominance hierarchies develop from pre-existing individual differences, such as in body mass. In the present paper, we investigate the relevance of each of these two theories for the degree of female dominance over males. We investigate this in a correlative study in which we compare female dominance between groups of 22 species throughout the primate order. In our study female dominance may range from 0 (no female dominance) to 1 (complete female dominance). As regards 'the prior attribute hypothesis', we expected a negative correlation between female dominance over males and species-specific sexual dimorphism in body mass. However, to our surprise we found none (we use the method of independent contrasts). Instead, we confirm the self-organisation hypothesis: our model based on the winner-loser effect predicts that female dominance over males increases with the percentage of males in the group. We confirm this pattern at several levels in empirical data (among groups of a single species and between species of the same genus and of different ones). Since the winner-loser effect has been shown to work in many taxa including humans, these results may have broad implications.