Sociogenomics of Cooperation and Conflict during Colony Founding in the Fire Ant Solenopsis invicta.

One of the fundamental questions in biology is how cooperative and altruistic behaviors evolved. The majority of studies seeking to identify the genes regulating these behaviors have been performed in systems where behavioral and physiological differences are relatively fixed, such as in the honey bee. During colony founding in the monogyne (one queen per colony) social form of the fire ant Solenopsis invicta, newly-mated queens may start new colonies either individually (haplometrosis) or in groups (pleometrosis). However, only one queen (the "winner") in pleometrotic associations survives and takes the lead of the young colony while the others (the "losers") are executed. Thus, colony founding in fire ants provides an excellent system in which to examine the genes underpinning cooperative behavior and how the social environment shapes the expression of these genes. We developed a new whole genome microarray platform for S. invicta to characterize the gene expression patterns associated with colony founding behavior. First, we compared haplometrotic queens, pleometrotic winners and pleometrotic losers. Second, we manipulated pleometrotic couples in order to switch or maintain the social ranks of the two cofoundresses. Haplometrotic and pleometrotic queens differed in the expression of genes involved in stress response, aging, immunity, reproduction and lipid biosynthesis. Smaller sets of genes were differentially expressed between winners and losers. In the second experiment, switching social rank had a much greater impact on gene expression patterns than the initial/final rank. Expression differences for several candidate genes involved in key biological processes were confirmed using qRT-PCR. Our findings indicate that, in S. invicta, social environment plays a major role in the determination of the patterns of gene expression, while the queen's physiological state is secondary. These results highlight the powerful influence of social environment on regulation of the genomic state, physiology and ultimately, social behavior of animals.

Looming signals reveal synergistic principles of multisensory integration.

Multisensory interactions are a fundamental feature of brain organization. Principles governing multisensory processing have been established by varying stimulus location, timing and efficacy independently. Determining whether and how such principles operate when stimuli vary dynamically in their perceived distance (as when looming/receding) provides an assay for synergy among the above principles and also means for linking multisensory interactions between rudimentary stimuli with higher-order signals used for communication and motor planning. Human participants indicated movement of looming or receding versus static stimuli that were visual, auditory, or multisensory combinations while 160-channel EEG was recorded. Multivariate EEG analyses and distributed source estimations were performed. Nonlinear interactions between looming signals were observed at early poststimulus latencies (∼75 ms) in analyses of voltage waveforms, global field power, and source estimations. These looming-specific interactions positively correlated with reaction time facilitation, providing direct links between neural and performance metrics of multisensory integration. Statistical analyses of source estimations identified looming-specific interactions within the right claustrum/insula extending inferiorly into the amygdala and also within the bilateral cuneus extending into the inferior and lateral occipital cortices. Multisensory effects common to all conditions, regardless of perceived distance and congruity, followed (∼115 ms) and manifested as faster transition between temporally stable brain networks (vs summed responses to unisensory conditions). We demonstrate the early-latency, synergistic interplay between existing principles of multisensory interactions. Such findings change the manner in which to model multisensory interactions at neural and behavioral/perceptual levels. We also provide neurophysiologic backing for the notion that looming signals receive preferential treatment during perception.

Double gene deletion reveals the lack of cooperation between PPARalpha and PPARbeta in skeletal muscle.

The peroxisome proliferator-activated receptors (PPARs) are involved in the regulation of most of the pathways linked to lipid metabolism. PPARalpha and PPARbeta isotypes are known to regulate muscle fatty acid oxidation and a reciprocal compensation of their function has been proposed. Herein, we investigated muscle contractile and metabolic phenotypes in PPARalpha-/-, PPARbeta-/-, and double PPARalpha-/- beta-/- mice. Heart and soleus muscle analyses show that the deletion of PPARalpha induces a decrease of the HAD activity (beta-oxidation) while soleus contractile phenotype remains unchanged. A PPARbeta deletion alone has no effect. However, these mild phenotypes are not due to a reciprocal compensation of PPARbeta and PPARalpha functions since double gene deletion PPARalpha-PPARbeta mostly reproduces the null PPARalpha-mediated reduced beta-oxidation, in addition to a shift from fast to slow fibers. In conclusion, PPARbeta is not required for maintaining skeletal muscle metabolic activity and does not compensate the lack of PPARalpha in PPARalpha null mice.

When Cooperation Stumbles: the effects of grades on indicators of cooperation

(English Abstract) In western societies, grades are to date the most widespread means by which achievement and performance are assessed in educational contexts. Grades are used for their capacity to provide individuals with a clear indicator of success or failure, in particular in comparison to others; in this respect, we study their impact on particular work contexts requiring cooperation. Indeed, students are often exhorted to cooperate and work in groups, while at the same time assessed with grades and focused on inter-individual comparison. However, to the best of our knowledge, no work has investigated the effects of grades on cooperation and on indicators of cooperation, a central question to be addressed given its significance for educational trends encouraging cooperative practices, and which we propose to explore in the experimental parts of this thesis. The first experimental chapter, Chapter 4, investigates the effect of grades with regards to their capacity to highlight individual visibility and at the same time social comparison. It tries to disentangle which of these facets could affect a motivated bias likely to reduce cooperation, namely individuals' preference for information confirming their own choice. In two experiments, results showed that a graded-cooperative situation increased this preference effect in comparison to other conditions where only individual visibility was manipulated, and furthermore increased individuals' perception of a competitive atmosphere. Chapter 5 investigates the effect of grades on direct cooperative inter- individual interactions, namely on group information sharing. Two experiments showed that grades hindered informational communication between individuals, leading them to withhold crucial task-information. Finally, Chapter 6 investigates the effects of grades on another indicator of group cooperation, namely inter-individual coordination. Results indicated that showcasing grades at the onset of a cooperative task necessitating inter-individual coordination decreased group performance and elicited more negative dominant behaviours amongst participants. Together these results provide evidence that grades hamper group cooperation. We conclude by discussing implications for the practice of grading in Education. ------------------------------------------------------- (Résumé en langue française) Dans la plupart des pays occidentaux, les notes sont majoritairement utilisées pour évaluer la performance et rendre compte de la réussite scolaire des individus. Dans cette perspective, elles sont non seulement un indicateur de succès ou d'échec, mais aussi de la valeur comparative des individus. Dans cette thèse nous proposons de tester l'effet des notes lorsque celles-ci sont utilisées dans des contextes bien spécifiques de coopération. En effet, si les notes et la comparaison sociale sont pratique courante, les étudiants sont souvent encouragés et amenés à coopérer en groupe. Cependant, à notre connaissance, point d'études ont testé l'effet des notes sur la coopération; études qui seraient pourtant légitimes étant donné la tendance existante en milieu éducatif à encourager les pratiques coopératives. C'est précisément ce que proposent de faire les chapitres expérimentaux de cette thèse. Le premier (Chapitre 4) teste l'effet des notes au regard de leur capacité à accentuer à la fois la visibilité et la comparaison sociale. Deux expériences investiguent l'effet des notes et tentent de démêler ce qui, de la visibilité individuelle, de la comparaison sociale ou des deux, pourrait affecter un biais motivationnel qui réduit la propension à coopérer: la propension à préférer les informations qui confirment les choix de l'individu. Les résultats montrent qu'en situation coopérative, les notes accroissent ce biais comparativement à des situations où seule la visibilité individuelle est soulignée, suggérant de plus que les notes produisent une focalisation des individus sur une comparaison sociale compétitive. Le second (Chapitre 5) teste l'effet des notes sur les interactions coopératives des individus, précisément sur le partage d'information. Deux expériences montrent que dans un contexte de travail en groupe coopératif, les notes entravent le bon partage des informations entre individus, les amenant à faire de la rétention d'information. Enfin, le troisième (Chapitre 6) investigue l'effet des notes sur un autre indicateur de coopération en groupe: la coordination interindividuelle. Les résultats montrent que les notes réduisent la coordination des individus et les mènent à avoir des comportements de dominance négative entre eux. En somme, les notes entravent la coopération et réduisent les comportements coopératifs entre individus. Enfin, nous discutons des implications pour le milieu éducatif.

Suivi thérapeutique des médicaments (I). Les principes [Principles of therapeutic drug monitoring]

Requesting a blood level measurement of a drug is part of the global approach known as "Therapeutic Drug Monitoring". Diverse situations require this monitoring approach, such as inadequate response to treatment or organ failure. Every drug however does not possess all the characteristics for a TDM program. The therapeutic range of a TDM drug has indeed to be narrow and its interindividual pharmacokinetic variability to be wide. As the development of new drugs is currently slowing down, the precise management of existing treatments certainly deserves progress, but needs however to be applied rationally, starting from a valid indication to blood sampling, and ending with a sound dosage adaptation decision.

Reputation based on punishment rather than generosity allows for evolution of cooperation in sizable groups

Cooperation among unrelated individuals can arise if decisions to help others can be based on reputation. While working for dyadic interactions, reputation-use in social dilemmas involving many individuals (e.g. public goods games) becomes increasingly difficult as groups become larger and errors more frequent. Reputation is therefore believed to have played a minor role for the evolution of cooperation in collective action dilemmas such as those faced by early humans. Here, we show in computer simulations that a reputation system based on punitive actions can overcome these problems and, compared to reputation system based on generous actions, (i) is more likely to lead to the evolution of cooperation in sizable groups, (ii) more effectively sustains cooperation within larger groups, and (iii) is more robust to errors in reputation assessment. Punishment and punishment reputation could therefore have played crucial roles in the evolution of cooperation within larger groups of humans.

Evolutionary games on complex networks : the emergence and maintenance of cooperation

Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.

Genetic team composition and level of selection in the evolution of cooperation

In cooperative multiagent systems, agents interac to solve tasks. Global dynamics of multiagent teams result from local agent interactions, and are complex and difficult to predict. Evolutionary computation has proven a promising approach to the design of such teams. The majority of current studies use teams composed of agents with identical control rules ("geneti- cally homogeneous teams") and select behavior at the team level ("team-level selection"). Here we extend current approaches to include four combinations of genetic team composition and level of selection. We compare the performance of genetically homo- geneous teams evolved with individual-level selection, genetically homogeneous teams evolved with team-level selection, genetically heterogeneous teams evolved with individual-level selection, and genetically heterogeneous teams evolved with team-level selection. We use a simulated foraging task to show that the optimal combination depends on the amount of cooperation required by the task. Accordingly, we distinguish between three types of cooperative tasks and suggest guidelines for the optimal choice of genetic team composition and level of selection

Emergence of Cooperation on Static and Dynamic Networks

Game theory is a branch of applied mathematics used to analyze situation where two or more agents are interacting. Originally it was developed as a model for conflicts and collaborations between rational and intelligent individuals. Now it finds applications in social sciences, eco- nomics, biology (particularly evolutionary biology and ecology), engineering, political science, international relations, computer science, and philosophy. Networks are an abstract representation of interactions, dependencies or relationships. Net- works are extensively used in all the fields mentioned above and in many more. Many useful informations about a system can be discovered by analyzing the current state of a network representation of such system. In this work we will apply some of the methods of game theory to populations of agents that are interconnected. A population is in fact represented by a network of players where one can only interact with another if there is a connection between them. In the first part of this work we will show that the structure of the underlying network has a strong influence on the strategies that the players will decide to adopt to maximize their utility. We will then introduce a supplementary degree of freedom by allowing the structure of the population to be modified along the simulations. This modification allows the players to modify the structure of their environment to optimize the utility that they can obtain.

How adult specialists deal with the principles of a successful transition.

OBJECTIVES: To evaluate whether adult specialists comply with the basic principles for a successful transition of adolescents with chronic disorders, and to determine whether the characteristics of the adult specialists have an influence on applying these principles. METHODS: Out of 299 adult specialists in four French-speaking Swiss cantons, 209 (70%) answered a paper-and-pencil mailed questionnaire between May and July 2007. Only those having received the transfer of at least one adolescent in the previous 2 years (N=102) were included in the analysis. We analyzed four dependent variables: discussing common concerns of adolescent patients, seeing the patient alone, having a transition protocol, and having a previous contact with the pediatric specialist. A logistic regression was performed for each dependent variable controlling for the physicians' characteristics (number of transfers, age, gender, workplace, and perceived experience). RESULTS: Fifty-four percent of the physicians did not spend time alone with their patients, and sensitive issues such as sexuality or substance use were not widely discussed with their young patients. Most respondents (59%) did not have an established protocol, and 54% did not have any contact with the pediatric specialist. In the multivariate analyses, the adult specialists' characteristics had little impact. CONCLUSIONS: For many adolescents with chronic disorders the transition from pediatric to adult healthcare seems to be limited to a simple transfer, often lacking adequate communication between physicians. Applying simple but basic principles such as a good coordination between providers would probably improve the quality of healthcare of adolescents with chronic illness.