We present a model of cultural evolution in which an individual's propensity to engage in social learning is affected by social learning itself. We assume that individuals observe cultural traits displayed by others and decide whether to copy them based on their overall preference for the displayed traits. Preferences, too, can be transmitted between individuals. Our results show that such cultural dynamics tends to produce conservative individuals, i.e., individuals who are reluctant to copy new traits. Openness to new information, however, can be maintained when individuals need significant time to acquire the cultural traits that make them effective cultural models. We show that a gradual enculturation of young individuals by many models and a larger cultural repertoire to be acquired are favorable circumstances for the long-term maintenance of openness in individuals and groups. Our results agree with data about lifetime personality change, showing that openness to new information decreases with age. Our results show that cultural remodeling of cultural transmission is a powerful force in cultural evolution, i.e., that cultural evolution can change its own dynamics

We use the term regulatory traits to indicate traits that both regulate cultural transmission (e.g., from whom to learn) and are themselves culturally transmitted. In the first part of this contribution we study the dynamics of some of these traits through simple mathematical models. In particular, we consider the cultural evolution of traits that determine the propensity to copy others, the ability to influence others, the number of individuals from whom one may copy, and the number of individuals one tries to influence. We then show how to extend these simple models to address more complex human cultural phenomena, such as ingroup biases, the emergence of open or conservative societies, and of cyclical, fashion-like, increases and decreases of popularity of cultural traits. We finally discuss how the ubiquity of regulatory traits in cultural evolution impacts on the analogy between genetic and cultural evolution and therefore on the possibility of using models inspired by evolutionary biology to study human cultural dynamics.

We call "regulatory traits" those cultural traits that are transmitted through cultural interactions and, at the same time, change individual behaviors directly influencing the outcome of future cultural interactions. The cultural dynamics of some of those traits are studied through simple simulations. In particular, we consider the cultural evolution of traits determining the propensity to copy, the number of potential demonstrators from whom one individual may copy, and conformist versus anti conformist attitudes. Our results show that regulatory traits generate peculiar dynamics that may explain complex human cultural phenomena. We discuss how the existence and importance of regulatory traits in cultural evolution impact on the analogy between genetic and cultural evolution and therefore on the possibility of using evolutionary biology inspired models to study human cultural dynamics.

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.

The mathematical study of genealogies has yielded important insights in population biology, such as the ability to estimate the time to the most recent common ancestor (MRCA) of a sample of genetic sequences or of a group of individuals. Here we introduce a model of cultural genealogies that is a step toward answering similar questions for cultural traits. In our model individuals can inherit from a variable, potentially large number of ancestors, rather than from a fixed, small number of ancestors (one or two) as is typical of genetic evolution. We first show that, given a sample of individuals, a cultural common ancestor does not necessarily exist. We then introduce a related concept: the most recent unique ancestor (MRUA), i.e., the most recent single individual who is the earliest cultural ancestor of the sample. We show that, under neutral evolution, the time to the MRUA can be staggeringly larger than the time to MRCA in a single ancestor model, except when the average number of learning opportunities per individuals is small. Our results point out that the properties of cultural genealogies may be very different from those of genetic genealogies, with potential implications for reconstructing the histories of cultural traits.

We investigated whether a sexual preference for smoking can be related to past experiences of parental smoking during childhood, as predicted by the theory of sexual imprinting, but also by sexual conditioning theory. In a sample of over 4000 respondents to five Internet surveys on sexual preferences, we found that parental smoking correlates with increased attraction to smoking in self-reported hetero- and homosexual males. Maternal smoking was associated with an increase in attraction to smoking both in hetero- and homosexual males, while paternal smoking was associated with an increase in attraction to smoking only in males who prefer male partners. We could not explain these findings by considering other factors than parental smoking habits, such as possibly biased reporting, indicators of a sexually liberal lifestyle or phenotype matching. Our data are consistent with the hypothesis that sexual preferences are acquired early in life by exposure to stimuli provided by individuals in the child’s environment, such as caregivers. The sex specificity of the parental effect is consistent with sexual imprinting theory but not with conditioning theory.

Introduction.  Several theories, including psychodynamic theories, sexual imprinting and early conditioning have been formulated to explain sexual development. Empirical data, however, remain insufficient for a thorough evaluation of these theories.

Aim.  In this study, we test the hypothesis that a critical period exists for the acquisition of sexual preferences, as suggested by empirical findings in birds and mammals (sexual imprinting).

Methods.  An Internet questionnaire was used.

Main Outcome Measures.  We gather data from individuals with a sexual preference for pregnant and/or lactating women, under the hypothesis that pregnancy or lactation may become sexually attractive in adulthood following an exposure to pregnant or lactating women in infancy.

Results.  We find that these preferences are more common in older siblings, i.e., in individuals who have been exposed to more maternal pregnancy and lactation. This result is independent of respondent and sibling sex. In addition, only maternal pregnancies and lactations experienced between 1.5 and 5 years of age are associated with the preferences.

Conclusions.  We discuss our findings in relation to theories of sexual development and to earlier reports of birth order effects on sexual behavior. We suggest that this age range may constitute a sensitive period for the acquisition of sexual preferences.

Previous work on mathematical models of cultural evolution has mainly focused on the diffusion of simple cultural elements. However, a characteristic feature of human cultural evolution is the seemingly limitless appearance of new and increasingly complex cultural elements. Here, we develop a general modelling framework to study such cumulative processes, in which we assume that the appearance and disappearance of cultural elements are stochastic events that depend on the current state of culture. Five scenarios are explored: evolution of independent cultural elements, stepwise modification of elements, differentiation or combination of elements and systems of cultural elements. As one application of our framework, we study the evolution of cultural diversity (in time as well as between groups).

Developmental psychology and cultural evolution are concerned with the same research questions but rarely interact. Collaboration between these fields could lead to substantial progress. Developmental psychology and related fields such as educational science and linguistics explore how behavior and cognition develop through combinations of social and individual experiences and efforts. Human developmental processes display remarkable plasticity, allowing children to master complex tasks, many which are of recent origin and not part of our biological history, such as mental arithmetic or pottery. It is this potency of human developmental mechanisms that allow humans to have culture on a grand scale. Biological evolution would only establish such plasticity if the combinatorial problems associated with flexibility could be solved, biological goals be reasonably safeguarded, and cultural transmission faithful. We suggest that cultural information can guide development in similar way as genes, provided that cultural evolution can establish productive transmission/teaching trajectories that allow for incremental acquisition of complex tasks. We construct a principle model of development that fulfills the needs of both subjects that we refer to as Incremental Functional Development. This process is driven by an error-correcting mechanism that attempts to fulfill combinations of cultural and inborn goals, using cultural information about structure. It supports the acquisition of complex skills. Over generations, it maintains function rather than structure, and this may solve outstanding issues about cultural transmission. The presence of cultural goals gives the mechanisms an open architecture that become an engine for cultural evolution.

Historical records show that culture can increase exponentially in time, e.g., in number of poems, musical works, scientific discoveries. We model how human capacities for creativity and cultural transmission may make such an increase possible, suggesting that: (1) creativity played a major role at the origin of human culture and for its accumulation throughout history, because cultural transmission cannot, on its own, generate exponentially increasing amounts of culture; (2) exponential increase in amount of culture can only occur if creativity is positively influenced by culture. The evolution of cultural transmission is often considered the main genetic bottleneck for the origin of culture, because natural selection cannot favor cultural transmission without any culture to transmit. Our models suggest that an increase in individual creativity may have been the first step toward human culture, because in a population of creative individuals there may be enough non-genetic information to favor the evolution of cultural transmission.

We introduce a mathematical model of cultural evolution to study cultural traits that shape how individuals exchange information. Current theory focuses on traits that influence the reception of information (receiver traits), such as evaluating whether information represents the majority or stems from a trusted source. Our model shifts the focus from the receiver to the sender of cultural information and emphasizes the role of sender traits, such as communicability or persuasiveness. Here, we show that sender traits are probably a stronger driving force in cultural evolution than receiver traits. While receiver traits evolve to curb cultural transmission, sender traits can amplify it and fuel the self-organization of systems of mutually supporting cultural traits, including traits that cannot be maintained on their own. Such systems can reach arbitrary complexity, potentially explaining uniquely human practical and mental skills, goals, knowledge and creativity, independent of innate factors. Our model incorporates social and individual learning throughout the lifespan, thus connecting cultural evolutionary theory with developmental psychology. This approach provides fresh insights into the trait-individual duality, that is, how cultural transmission of single traits is influenced by individuals, who are each represented as an acquired system of cultural traits.

Behaving efficiently (optimally or near-optimally) is central to animals' adaptation to their environment. Much evolutionary biology assumes, implicitly or explicitly, that optimal behavioural strategies are genetically inherited, yet the behaviour of many animals depends crucially on learning. The question of how learning contributes to optimal behaviour is largely open. Here we propose an associative learning model that can learn optimal behaviour in a wide variety of ecologically relevant circumstances. The model learns through chaining, a term introduced by Skinner to indicate learning of behaviour sequences by linking together shorter sequences or single behaviours. Our model formalizes the concept of conditioned reinforcement (the learning process that underlies chaining) and is closely related to optimization algorithms from machine learning. Our analysis dispels the common belief that associative learning is too limited to produce ‘intelligent’ behaviour such as tool use, social learning, self-control or expectations of the future. Furthermore, the model readily accounts for both instinctual and learned aspects of behaviour, clarifying how genetic evolution and individual learning complement each other, and bridging a long-standing divide between ethology and psychology. We conclude that associative learning, supported by genetic predispositions and including the oft-neglected phenomenon of conditioned reinforcement, may suffice to explain the ontogeny of optimal behaviour in most, if not all, non-human animals. Our results establish associative learning as a more powerful optimizing mechanism than acknowledged by current opinion.

Bridging associative and normative theories of animal learning, I show that an associative system can behave as if performing probabilistic inference by using the function f(V) = 1 − e^−cV to transform associative strengths (V) into response probabilities. For example, using this function, an associative system can respond normatively to a compound stimulus AB, given previous separate experiences with the components A and B. The CR probability formulae that result from the proposed function have a normative interpretation in terms of statistical decision theory. The formulae also suggest a normative interpretation of stimulus generalization as a heuristic to infer whether different stimuli are likely to convey redundant or independent information about reinforcement. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Ravignani et al (2013) abituated squirrel monkeys to sound sequences conforming to an ABnA grammar (n = 1, 2, 3), then tested them for their reactions to novel grammatical and non -grammatical sequences. Although they conclude that the monkeys consistently recognized and generalized the sequence AB(n)A, I remark that this conclusion is not robust. The statistical significance of results depends on specific choices of data analysis, namely dichotomization of the response variable and omission of specific data points. Additionally, there is little evidence of generalization to novel patterns (n = 4, 5), which is important to conclude that the monkeys recognized the AB(n)A grammar beyond the habituation patterns. Lastly, many test sequences were perceptually similar to habituation sequences, raising the possibility that the monkeys may have generalized based on perceptual similarity rather than based on grammaticality.

In summation experiments, responding to a compound stimulus is assessed after conditioning a response to each of its components. This simple experiment poses significant challenges to models of associative learning because of substantial variability in results. Here, I introduce a new method to quantify generalization from components to compound in summation experiments, which I apply to over 250 measurements of summation in rabbits, pigeons, rats, and humans. The analysis confirms that more summation occurs with stimuli from different rather than from the same sensory modality, although this is not the sole determinant of summation. A theoretical analysis shows that this finding is best accounted for by a model that includes both element sharing (Rescorla & Wagner, 1972) and element replacement (Brandon et al., 2000) in stimulus representations. I point out remaining gaps in our empirical and theoretical understanding of summation. 

I introduce a simple mathematical method to calculate the associative strengths of stimuli in many models of associative learning, without solving the models' learning equations and without simulating the learning process. The method applies to many models, including the Rescorla and Wagner (1972) model, the replaced elements model of Brandon et al. (2000), and Pearce's (1987) configural model. I illustrate the method by calculating the predictions of these three models in summation and blocking experiments, allowing for a degree of similarity between the training stimuli as well as for the effects of contextual stimuli. The method clarifies the models' predictions and suggests new empirical tests.