High-magnitude innovators as keystone individuals in the evolution of culture.

Borrowing from the concept of keystone species in ecological food webs, a recent focus in the field of animal behaviour has been keystone individuals: individuals whose impact on population dynamics is disproportionally larger than their frequency in the population. In populations evolving culture, such may be the role of high-magnitude innovators: individuals whose innovations are a major departure from the population's existing behavioural repertoire. Their effect on cultural evolution is twofold: they produce innovations that constitute a 'cultural leap' and, once copied, their innovations may induce further innovations by conspecifics (socially induced innovations) as they explore the new behaviour themselves. I use computer simulations to study the coevolution of independent innovations, socially induced innovations and innovation magnitude, and show that while socially induced innovation is assumed here to be less costly than independent innovation, it does not readily evolve. When it evolves, it may in some conditions select against independent innovation and lower its frequency, despite it requiring independent innovation in order to operate; at the same time, however, it leads to much faster cultural evolution. These results confirm the role of high-magnitude innovators as keystones, and suggest a novel explanation for the low frequency of independent innovation.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'.

Constructive anthropomorphism: a functional evolutionary approach to the study of human-like cognitive mechanisms in animals.

Anthropomorphism, the attribution of human cognitive processes and emotional states to animals, is commonly viewed as non-scientific and potentially misleading. This is mainly because apparent similarity to humans can usually be explained by alternative, simpler mechanisms in animals, and because there is no explanatory power in analogies to human phenomena when these phenomena are not well understood. Yet, because it is also difficult to preclude real similarity and continuity in the evolution of humans' and animals' cognitive abilities, it may not be productive to completely ignore our understanding of human behaviour when thinking about animals. Here we propose that in applying a functional approach to the evolution of cognitive mechanisms, human cognition may be used to broaden our theoretical thinking and to generate testable hypotheses. Our goal is not to 'elevate' animals, but rather to find the minimal set of mechanistic principles that may explain 'advanced' cognitive abilities in humans, and consider under what conditions these mechanisms were likely to enhance fitness and to evolve in animals. We illustrate this approach, from relatively simple emotional states, to more advanced mechanisms, involved in planning and decision-making, episodic memory, metacognition, theory of mind, and consciousness.

The magnitude of innovation and its evolution in social animals.

Innovative behaviour in animals, ranging from invertebrates to humans, is increasingly recognized as an important topic for investigation by behavioural researchers. However, what constitutes an innovation remains controversial, and difficult to quantify. Drawing on a broad definition whereby any behaviour with a new component to it is an innovation, we propose a quantitative measure, which we call the magnitude of innovation, to describe the extent to which an innovative behaviour is novel. This allows us to distinguish between innovations that are a slight change to existing behaviours (low magnitude), and innovations that are substantially different (high magnitude). Using mathematical modelling and evolutionary computer simulations, we explored how aspects of social interaction, cognition and natural selection affect the frequency and magnitude of innovation. We show that high-magnitude innovations are likely to arise regularly even if the frequency of innovation is low, as long as this frequency is relatively constant, and that the selectivity of social learning and the existence of social rewards, such as prestige and royalties, are crucial for innovative behaviour to evolve. We suggest that consideration of the magnitude of innovation may prove a useful tool in the study of the evolution of cognition and of culture.

An arms race between producers and scroungers can drive the evolution of social cognition.

The "social intelligence hypothesis" states that the need to cope with complexities of social life has driven the evolution of advanced cognitive abilities. It is usually invoked in the context of challenges arising from complex intragroup structures, hierarchies, and alliances. However, a fundamental aspect of group living remains largely unexplored as a driving force in cognitive evolution: the competition between individuals searching for resources (producers) and conspecifics that parasitize their findings (scroungers). In populations of social foragers, abilities that enable scroungers to steal by outsmarting producers, and those allowing producers to prevent theft by outsmarting scroungers, are likely to be beneficial and may fuel a cognitive arms race. Using analytical theory and agent-based simulations, we present a general model for such a race that is driven by the producer-scrounger game and show that the race's plausibility is dramatically affected by the nature of the evolving abilities. If scrounging and scrounging avoidance rely on separate, strategy-specific cognitive abilities, arms races are short-lived and have a limited effect on cognition. However, general cognitive abilities that facilitate both scrounging and scrounging avoidance undergo stable, long-lasting arms races. Thus, ubiquitous foraging interactions may lead to the evolution of general cognitive abilities in social animals, without the requirement of complex intragroup structures.

The local enhancement conundrum: in search of the adaptive value of a social learning mechanism.

Social learning mechanisms are widely thought to vary in their degree of complexity as well as in their prevalence in the natural world. While learning the properties of a stimulus that generalize to similar stimuli at other locations (stimulus enhancement) prima facie appears more useful to an animal than learning about a specific stimulus at a specific location (local enhancement), empirical evidence suggests that the latter is much more widespread in nature. Simulating populations engaged in a producer-scrounger game, we sought to deploy mathematical models to identify the adaptive benefits of reliance on local enhancement and/or stimulus enhancement, and the alternative conditions favoring their evolution. Surprisingly, we found that while stimulus enhancement readily evolves, local enhancement is advantageous only under highly restricted conditions: when generalization of information was made unreliable or when error in social learning was high. Our results generate a conundrum over how seemingly conflicting empirical and theoretical findings can be reconciled. Perhaps the prevalence of local enhancement in nature is due to stimulus enhancement costs independent of the learning task itself (e.g. predation risk), perhaps natural habitats are often characterized by unreliable yet highly rewarding payoffs, or perhaps local enhancement occurs less frequently, and stimulus enhancement more frequently, than widely believed.

Recombination and the evolution of coordinated phenotypic expression in a frequency-dependent game.

A long standing question in evolutionary biology concerns the maintenance of adaptive combinations of traits in the presence of recombination. This problem may be solved if positive epistasis selects for reducing the rate of recombination between such traits, but this requires sufficiently strong epistasis. Here we use a model that we developed previously to analyze a frequency-dependent strategy game in asexual populations, to study how adaptive combinations of traits may be maintained in the presence of recombination when epistasis is too weak to select for genetic linkage. Previously, in the asexual case, our model demonstrated the evolution of adaptive associations between social foraging strategies and learning rules. We verify that these adaptive associations, which are represented by different two-locus haplotypes, can easily be broken by genetic recombination. We also confirm that a modifier allele that reduces the rate of recombination fails to evolve (due to weak epistasis). However, we find that under the same conditions of weak epistasis, there is an alternative mechanism that allows an association between traits to evolve. This is based on a genetic switch that responds to the presence of one social foraging allele by activating one of the two alternative learning alleles that are carried by all individuals. We suggest that such coordinated phenotypic expression by genetic switches offers a general and robust mechanism for the evolution of adaptive combinations of traits in the presence of recombination.

Evolution of social learning when high expected payoffs are associated with high risk of failure.

In an environment where the availability of resources sought by a forager varies greatly, individual foraging is likely to be associated with a high risk of failure. Foragers that learn where the best sources of food are located are likely to develop risk aversion, causing them to avoid the patches that are in fact the best; the result is sub-optimal behaviour. Yet, foragers living in a group may not only learn by themselves, but also by observing others. Using evolutionary agent-based computer simulations of a social foraging game, we show that in an environment where the most productive resources occur with the lowest probability, socially acquired information is strongly favoured over individual experience. While social learning is usually regarded as beneficial because it filters out maladaptive behaviours, the advantage of social learning in a risky environment stems from the fact that it allows risk aversion to be circumvented and the best food source to be revisited despite repeated failures. Our results demonstrate that the consequences of individual risk aversion may be better understood within a social context and suggest one possible explanation for the strong preference for social information over individual experience often observed in both humans and animals.

Co-evolution of learning complexity and social foraging strategies.

Variation in learning abilities within populations suggests that complex learning may not necessarily be more adaptive than simple learning. Yet, the high cost of complex learning cannot fully explain this variation without some understanding of why complex learning is too costly for some individuals but not for others. Here we propose that different social foraging strategies can favor different learning strategies (that learn the environment with high or low resolution), thereby maintaining variable learning abilities within populations. Using a genetic algorithm in an agent-based evolutionary simulation of a social foraging game (the producer-scrounger game) we demonstrate how an association evolves between a strategy based on independent search for food (playing a producer) and a complex (high resolution) learning rule, while a strategy that combines independent search and following others (playing a scrounger) evolves an association with a simple (low resolution) learning rule. The reason for these associations is that for complex learning to have an advantage, a large number of learning steps, normally not achieved by scroungers, are necessary. These results offer a general explanation for persistent variation in cognitive abilities that is based on co-evolution of learning rules and social foraging strategies.

Sex-specific variability and a 'cage effect' independently mask a neuropathic pain quantitative trait locus detected in a whole genome scan.

Sex and environment may dramatically affect genetic studies, and thus should be carefully considered. Beginning with two inbred mouse strains with contrasting phenotype in the neuroma model of neuropathic pain (autotomy), we established a backcross population on which we conducted a genome-wide scan. The backcross population was partially maintained in small social groups and partially in isolation. The genome scan detected one previously reported quantitative trait locus (QTL) on chromosome 15 (pain1), but no additional QTLs were found. Interestingly, group caging introduced phenotypic noise large enough to completely mask the genetic effect of the chromosome 15 QTL. The reason appears to be that group-caging animals from the low-autotomy strain together with animals from the high-autotomy strain dramatically increases autotomy in the otherwise low-autotomy mice (males or females). The converse, suppression of pain behaviour in the high-autotomy strain when caged with the low-autotomy strain was also observed, but only in females. Even in isolated mice, the genetic effect of the chromosome 15 QTL was significant only in females. To determine why, we evaluated autotomy levels of females in 12 different inbred stains of mice and compared them to previously reported levels for males. Strikingly larger environmental variation was observed in males than in females for this pain phenotype. The high baseline variance in males can explain the difficulty in detecting the genetic effect, which was readily seen in females. Our study emphasizes the importance of sex and environment in the genetic analysis of pain.

pain1: a neuropathic pain QTL on mouse chromosome 15 in a C3HxC58 backcross.

We have produced a backcross (BC) population of 267 mice from the parental strains C3H/HeN and C58/J. The mice were phenotyped for neuropathic pain using the neuroma model. Subsequently all BC mice were genotyped in a region of chromosome 15 that has been previously suggested to contain a quantitative trait locus (QTL) for this trait. We have confirmed the linkage of the QTL, named pain1, to the central region of chromosome 15. Our finding provides the necessary robustness to justify efforts towards identification of the underlying gene.