Dating human cultural capacity using phylogenetic principles

Humans have genetically based unique abilities making complex culture possible; an assemblage of traits which we term “cultural capacity”. The age of this capacity has for long been subject to controversy. We apply phylogenetic principles to date this capacity, integrating evidence from archaeology, genetics, paleoanthropology, and linguistics. We show that cultural capacity is older than the first split in the modern human lineage, and at least 170,000 years old, based on data on hyoid bone morphology, FOXP2 alleles, agreement between genetic and language trees, fire use, burials, and the early appearance of tools comparable to those of modern hunter-gatherers. We cannot exclude that Neanderthals had cultural capacity some 500,000 years ago. A capacity for complex culture, therefore, must have existed before complex culture itself. It may even originated long before. This seeming paradox is resolved by theoretical models suggesting that cultural evolution is exceedingly slow in its initial stages

The Logic of Fashion Cycles

Many cultural traits exhibit volatile dynamics, commonly dubbed fashions or fads. Here we show that realistic fashion-like dynamics emerge spontaneously if individuals can copy others' preferences for cultural traits as well as traits themselves. We demonstrate this dynamics in simple mathematical models of the diffusion, and subsequent abandonment, of a single cultural trait which individuals may or may not prefer. We then simulate the coevolution between many cultural traits and the associated preferences, reproducing power-law frequency distributions of cultural traits (most traits are adopted by few individuals for a short time, and very few by many for a long time), as well as correlations between the rate of increase and the rate of decrease of traits (traits that increase rapidly in popularity are also abandoned quickly and vice versa). We also establish that alternative theories, that fashions result from individuals signaling their social status, or from individuals randomly copying each other, do not satisfactorily reproduce these empirical observations

Neural networks and animal behavior

DAL SITO DELL'EDITORE: How can we make better sense of animal behavior by using what we know about the brain? This is the first book that attempts to answer this important question by applying neural network theory. Scientists create Artificial Neural Networks (ANNs) to make models of the brain. These networks mimic the architecture of a nervous system by connecting elementary neuron-like units into networks in which they stimulate or inhibit each other's activity in much the same way neurons do. This book shows how scientists can employ ANNs to analyze animal behavior, explore the general principles of the nervous systems, and test potential generalizations among species. The authors focus on simple neural networks to show how ANNs can be investigated by math and by computers. They demonstrate intuitive concepts that make the operation of neural networks more accessible to nonspecialists. The first chapter introduces various approaches to animal behavior and provides an informal introduction to neural networks, their history, and their potential advantages. The second chapter reviews artificial neural networks, including biological foundations, techniques, and applications. The following three chapters apply neural networks to such topics as learning and development, classical instrumental condition, and the role of genes in building brain networks. The book concludes by comparing neural networks to other approaches. It will appeal to students of animal behavior in many disciplines. It will also interest neurobiologists, cognitive scientists, and those from other fields who wish to learn more about animal behavior

Cumulative culture and explosive demographic transitions

A demographic transition is a change in the pattern of growth of a population. Human history records several kinds of such transitions, e.g., from stability to growth or between different kinds of growth. Culture is often implied as the main fuel of demographic transitions, but theorizing is so far limited to verbal arguments. Here we study two simple formal models in which population size and the amount of culture in a population influence each other's dynamics. The first model has two regimes: an equilibrium regime in which both population size and amount of culture reach stable values, and an explosive regime in which both variables increase exponentially without bound. A transition between these regimes is caused by changes in parameters that describe the accuracy of cultural transmission and the interaction between demography and culture. The second model suggests that a transition from extensive to intensive accumulation of culture may derive from a qualitative change in how individuals cooperate to create culture

Culture creates its own rules: the rise of conservatism and persuasion

Many aspects of human behaviour are attributed to culture, but the extent to which culture is influenced by our genes remains strongly debated. Cultural evolution has been viewed as controlled by a genetically determined human nature, as a distinct process in interaction with genetic evolution, and as an autonomous process wholly free from genetic influences. Proponents of the latter view often imply that cultural evolution may take any direction, but this is not necessarily true. Here we show how forces that operate within culture itself can systematically shape behaviour and personality traits that have a significant impact on cultural change. Specifically, we show that both unwillingness to change (``conservatism'') and influencing others to become like yourself (``persuasion'') are traits favoured by cultural evolution, even when individuals have no genetic predisposition towards these traits

Sustainability of culture-driven population dynamics

We consider models of the interactions between human population dynamics and cul- tural evolution, asking whether they predict sustainable or unsustainable patterns of growth. Phenomenological models predict either unsustainable population growth or stabilization in the near future. The latter prediction, however, is based on extrapolation of current demographic trends and does not take into account causal processes of demographic and cultural dynamics. Most existing causal models assume (or derive from simplified models of the economy) a positive feedback between cultural evolution and demographic growth, and predict unlimited growth in both culture and population. We augment these models taking into account that: 1) cultural transmission is not perfect, i.e., culture can be lost; 2) culture does not always promote population growth. We show that taking these factors into account can cause radically different model behavior, such as population extinction rather than stability, and extinction rather than growth. We conclude that all models agree that a population capable of maintaining a large amount of culture, including a powerful tech- nology, runs a high risk of being unsustainable. We suggest that future work must address more explicitly both the dynamics of resource consumption and the cultural evolution of beliefs implicated in reproductive behavior (e.g., ideas about the preferred family size) and in resource use (e.g., environmentalist stances)

Old and young individuals' role in cultural change

We explore the impact of age on cultural change through simulations of cultural evolution. Our simulations show that common observations about the relationship between old and young naturally emerge from repeated cultural learning. In particular, young individuals are more open to learn than older individuals, they are less effective as cultural models, and they possess less cultural traits. We also show that, being more open to learning, young individuals are an important source of cultural change. Cultural change, however, is faster in populations with both young and old. A relatively large share of older individuals, in fact, allows a population to retain more culture, and a large culture can change in more directions than a small culture. For the same reason, considering age-biased cultural transmission in an overlapping generations model, cultural evolution is slower when individuals interact preferentially with models of similar age than when they mainly interact with older models.Swedish Research Counci

CRITICAL POINTS IN CURRENT THEORY OF CONFORMIST SOCIAL LEARNING

Existing mathematical models suggest that gene-culture co- evolution favours a conformist bias in social learning, that is a psycho- logical mechanism to preferentially acquire the most common cultural variants. Here we show that this conclusion relies on specific assump- tions that seem unrealistic, such as that all cultural variants are known to every individual. We present two models that remove these assumptions, showing that: 1) the rate of cultural evolution and the adaptive value of culture are higher in a population in which individuals picks cultural variants at random (Random strategy) rather than picking the most com- mon one (Conform strategy); 2) in genetic evolution the Random strategy outcompetes the Conform strategy, unless cultural evolution is very slow, in which case Conform and Random usually coexist; 3) the individuals’ ability to evaluate cultural variants is a more important determinant of the adaptive value of culture than frequency-based choice strategies. We also review existing empirical literature and game-theoretic arguments for conformity, finding neither strong empirical evidence nor a strong theoretical expectation for a general conformist bias. Our own vignette study of social learning shows that people may indeed use different so- cial learning strategies depending on context

Regulatory traits: Cultural influences on cultural evolution

Swedish Research Counci