Studies of animal behavior consistently demonstrate that the social environment impacts cooperation, yet the effect of social dynamics has been largely excluded from studies of human cooperation. Here, we introduce a novel approach inspired by nonhuman primate research to address how social hierarchies impact human cooperation. Participants competed to earn hierarchy positions and then could cooperate with another individual in the hierarchy by investing in a common effort. Cooperation was achieved if the combined investments exceeded a threshold, and the higher ranked individual distributed the spoils unless control was contested by the partner. Compared to a condition lacking hierarchy, cooperation declined in the presence of a hierarchy due to a decrease in investment by lower ranked individuals. Furthermore, hierarchy was detrimental to cooperation regardless of whether it was earned or arbitrary. These findings mirror results from nonhuman primates and demonstrate that hierarchies are detrimental to cooperation. However, these results deviate from nonhuman primate findings by demonstrating that human behavior is responsive to changing hierarchical structures and suggests partnership dynamics that may improve cooperation. This work introduces a controlled way to investigate the social influences on human behavior, and demonstrates the evolutionary continuity of human behavior with other primate species.
Movement interactions and the underlying social structure in groups have relevance across many social-living species. Collective motion of groups could be based on an “egalitarian” decision system, but in practice it is often influenced by underlying social network structures and by individual characteristics. We investigated whether dominance rank and personality traits are linked to leader and follower roles during joint motion of family dogs. We obtained high-resolution spatio-temporal GPS trajectory data (823,148 data points) from six dogs belonging to the same household and their owner during 14 30-40 min unleashed walks. We identified several features of the dogs' paths (e.g., running speed or distance from the owner) which are characteristic of a given dog. A directional correlation analysis quantifies interactions between pairs of dogs that run loops jointly. We found that dogs play the role of the leader about 50-85% of the time, i.e. the leader and follower roles in a given pair are dynamically interchangable. However, on a longer timescale tendencies to lead differ consistently. The network constructed from these loose leader-follower relations is hierarchical, and the dogs' positions in the network correlates with the age, dominance rank, trainability, controllability, and aggression measures derived from personality questionnaires. We demonstrated the possibility of determining dominance rank and personality traits of an individual based only on its logged movement data. The collective motion of dogs is influenced by underlying social network structures and by characteristics such as personality differences. Our findings could pave the way for automated animal personality and human social interaction measurements.
As vertebrate embryos develop to adulthood, their organs undergo marked changes in size and tissue architecture. The heart acquires muscle mass and matures structurally to fulfil increasing circulatory needs, a process that is incompletely understood. Here we used multicolour clonal analysis to define the contributions of individual cardiomyocytes as the zebrafish heart undergoes morphogenesis from a primitive embryonic structure into its complex adult form. We find that the single-cardiomyocyte-thick wall of the juvenile ventricle forms by lateral expansion of several dozen cardiomyocytes into muscle patches of variable sizes and shapes. As juvenile zebrafish mature into adults, this structure becomes fully enveloped by a new lineage of cortical muscle. Adult cortical muscle originates from a small number of cardiomyocytes–an average of approximately eight per animal–that display clonal dominance reminiscent of stem cell populations. Cortical cardiomyocytes initially emerge from internal myofibres that in rare events breach the juvenile ventricular wall, and then expand over the surface. Our results illuminate the dynamic proliferative behaviours that generate adult cardiac structure, revealing clonal dominance as a key mechanism that shapes a vertebrate organ.
Herman Melville’s novel Moby Dick was inspired by historical instances in which large sperm whales (Physeter macrocephalus L.) sank 19th century whaling ships by ramming them with their foreheads. The immense forehead of sperm whales is possibly the largest, and one of the strangest, anatomical structures in the animal kingdom. It contains two large oil-filled compartments, known as the “spermaceti organ” and “junk,” that constitute up to one-quarter of body mass and extend one-third of the total length of the whale. Recognized as playing an important role in echolocation, previous studies have also attributed the complex structural configuration of the spermaceti organ and junk to acoustic sexual selection, acoustic prey debilitation, buoyancy control, and aggressive ramming. Of these additional suggested functions, ramming remains the most controversial, and the potential mechanical roles of the structural components of the spermaceti organ and junk in ramming remain untested. Here we explore the aggressive ramming hypothesis using a novel combination of structural engineering principles and probabilistic simulation to determine if the unique structure of the junk significantly reduces stress in the skull during quasi-static impact. Our analyses indicate that the connective tissue partitions in the junk reduce von Mises stresses across the skull and that the load-redistribution functionality of the former is insensitive to moderate variation in tissue material parameters, the thickness of the partitions, and variations in the location and angle of the applied load. Absence of the connective tissue partitions increases skull stresses, particularly in the rostral aspect of the upper jaw, further hinting of the important role the architecture of the junk may play in ramming events. Our study also found that impact loads on the spermaceti organ generate lower skull stresses than an impact on the junk. Nevertheless, whilst an impact on the spermaceti organ would reduce skull stresses, it would also cause high compressive stresses on the anterior aspect of the organ and the connective tissue case, possibly making these structures more prone to failure. This outcome, coupled with the facts that the spermaceti organ houses sensitive and essential sonar producing structures and the rostral portion of junk, rather than the spermaceti organ, is frequently a site of significant scarring in mature males suggest that whales avoid impact with the spermaceti organ. Although the unique structure of the junk certainly serves multiple functions, our results are consistent with the hypothesis that the structure also evolved to function as a massive battering ram during male-male competition.
Integration of local elements into a coherent global form is a fundamental aspect of visual object recognition. How the different hierarchically organized stages of visual analysis develop in order to support object representation in infants remains unknown. The aim of this study was to investigate structural encoding of natural images in 4- to 6-month-old infants and adults. We used the steady-state visual evoked potential (ssVEP) technique to measure cortical responses specific to the global structure present in object and face images, and assessed whether differential responses were present for these image categories. This study is the first to apply the ssVEP method to high-level vision in infants. Infants and adults responded to the structural relations present in both image categories, and topographies of the responses differed based on image category. However, while adult responses to face and object structure were localized over occipitotemporal scalp areas, only infant face responses were distributed over temporal regions. Therefore, both infants and adults show object category specificity in their neural responses. The topography of the infant response distributions indicates that between 4 and 6 months of age, structure encoding of faces occurs at a higher level of processing than that of objects.
Biology presents many examples of planar distribution and structural networks having dense sets of closed loops. An archetype of this form of network organization is the vasculature of dicotyledonous leaves, which showcases a hierarchically-nested architecture containing closed loops at many different levels. Although a number of approaches have been proposed to measure aspects of the structure of such networks, a robust metric to quantify their hierarchical organization is still lacking. We present an algorithmic framework, the hierarchical loop decomposition, that allows mapping loopy networks to binary trees, preserving in the connectivity of the trees the architecture of the original graph. We apply this framework to investigate computer generated graphs, such as artificial models and optimal distribution networks, as well as natural graphs extracted from digitized images of dicotyledonous leaves and vasculature of rat cerebral neocortex. We calculate various metrics based on the asymmetry, the cumulative size distribution and the Strahler bifurcation ratios of the corresponding trees and discuss the relationship of these quantities to the architectural organization of the original graphs. This algorithmic framework decouples the geometric information (exact location of edges and nodes) from the metric topology (connectivity and edge weight) and it ultimately allows us to perform a quantitative statistical comparison between predictions of theoretical models and naturally occurring loopy graphs.
The goal of the study was to demonstrate a hierarchical structure of resting state activity in the healthy brain using a data-driven clustering algorithm.
We study evolutionary game dynamics on structured populations in which individuals take part in several layers of networks of interactions simultaneously. This multiplex of interdependent networks accounts for the different kind of social ties each individual has. By coupling the evolutionary dynamics of a Prisoner’s Dilemma game in each of the networks, we show that the resilience of cooperative behaviors for extremely large values of the temptation to defect is enhanced by the multiplex structure. Furthermore, this resilience is intrinsically related to a non-trivial organization of cooperation across the network layers, thus providing a new way out for cooperation to survive in structured populations.
We introduce a new method for detecting communities of arbitrary size in an undirected weighted network. Our approach is based on tracing the path of closest-friendship between nodes in the network using the recently proposed Generalized Erds Numbers. This method does not require the choice of any arbitrary parameters or null models, and does not suffer from a system-size resolution limit. Our closest-friend community detection is able to accurately reconstruct the true network structure for a large number of real world and artificial benchmarks, and can be adapted to study the multi-level structure of hierarchical communities as well. We also use the closeness between nodes to develop a degree of robustness for each node, which can assess how robustly that node is assigned to its community. To test the efficacy of these methods, we deploy them on a variety of well known benchmarks, a hierarchal structured artificial benchmark with a known community and robustness structure, as well as real-world networks of coauthorships between the faculty at a major university and the network of citations of articles published in Physical Review. In all cases, microcommunities, hierarchy of the communities, and variable node robustness are all observed, providing insights into the structure of the network.
Understanding intra-molecular coevolution helps to elucidate various structural and functional constraints acting on molecules and might have practical applications in predicting molecular structure and interactions. In this study, we used 5S rRNA as a template to investigate how selective constraints have shaped the RNA evolution. We have observed the nonrandom occurrence of paired differences along the phylogenetic trees, the high rate of compensatory evolution, and the high TIR scores (the ratio of the numbers of terminal to intermediate states), all of which indicate that significant positive selection has driven the evolution of 5S rRNA. We found three mechanisms of compensatory evolution: Watson-Crick interaction (the primary one), complex interactions between multiple sites within a stem, and interplay of stems and loops. Coevolutionary interactions between sites were observed to be highly dependent on the structural and functional environment in which they occurred. Coevolution occurred mostly in those sites closest to loops or bulges within structurally or functionally important helices, which may be under weaker selective constraints than other stem positions. Breaking these pairs would directly increase the size of the adjoining loop or bulge, causing a partial or total structural rearrangement. In conclusion, our results indicate that sequence coevolution is a direct result of maintaining optimal structural and functional integrity.