Abstract: Complex networks are studied across many fields of science. To uncover their structural design principles, we defined “network motifs,” patterns of interconnections occurring in complex networks at numbers that are significantly higher than those in randomized networks. We found such motifs in networks from biochemistry, neurobiology, ecology, and engineering. The motifs shared by ecological food webs were distinct from the motifs shared by the genetic networks of Escherichia coli and Saccharomyces cerevisiae or from those found in the World Wide Web. Similar motifs were found in networks that perform information processing, even though they describe elements as different as biomolecules within a cell and synaptic connections between neurons in Caenorhabditis elegans. Motifs may thus define universal classes of networks. This approach may uncover the basic building blocks of most networks.

Abstract: The acquisition and use of socially acquired information is commonly assumed to be profitable. We challenge this assumption by exploring hypothetical scenarios where the use of such information either provides no benefit or can actually be costly. First, we show that the level of incompatibility between the acquisition of personal and socially acquired information will directly affect the extent to which the use of socially acquired information can be profitable. When these two sources of information cannot be acquired simultaneously, there may be no benefit to socially acquired information. Second, we assume that a solitary individual's behavioural decisions will be based on cues revealed by its own interactions with the environment. However, in many cases, for social animals the only socially acquired information available to individuals is the behavioural actions of others that expose their decisions, rather than the cues on which these decisions were based. We argue that in such a situation the use of socially acquired information can lead to informational cascades that sometimes result in sub-optimal behaviour. From this theory of informational cascades, we predict that when erroneous cascades are costly, individuals should pay attention only to socially generated cues and not behavioural decisions. We suggest three scenarios that might be examples of informational cascades in nature.

Abstract: Human cooperation is an evolutionary puzzle. Unlike other creatures, people frequently cooperate with genetically unrelated strangers, often in large groups, with people they will never meet again, and when reputation gains are small or absent. These patterns of cooperation cannot be explained by the nepotistic motives associated with the evolutionary theory of kin selection and the selfish motives associated with signalling theory or the theory of reciprocal altruism. Here we show experimentally that the altruistic punishment of defectors is a key motive for the explanation of cooperation. Altruistic punishment means that individuals punish, although the punishment is costly for them and yields no material gain. We show that cooperation flourishes if altruistic punishment is possible, and breaks down if it is ruled out. The evidence indicates that negative emotions towards defectors are the proximate mechanism behind altruistic punishment. These results suggest that future study of the evolution of human cooperation should include a strong focus on explaining altruistic punishment.