The refinement paradox and cumulative cultural evolution: Complex products of collective improvement favor conformist outcomes, blind copying, and hyper-credulity.

Social learning is common in nature, yet cumulative culture (where knowledge and technology increase in complexity and diversity over time) appears restricted to humans. To understand why, we organized a computer tournament in which programmed entries specified when to learn new knowledge and when to refine (i.e.

Differential impact of self and environmental antigens on the ontogeny and maintenance of CD4 T cell memory.

Laboratory mice develop populations of circulating memory CD4 T cells in the absence of overt infection. We have previously shown that these populations are replenished from naive precursors at high levels throughout life (Gossel et al., 2017).

Aversive medical treatments signal a need for support: a mathematical model.

Ineffective, aversive and harmful medical treatments are common cross-culturally, historically and today. Using evolutionary game theory, we develop the following model to explain their persistence. Humans are often incapacitated by illness and injury, and are unusually dependent on care from others during convalescence.

Social learning may lead to population level conformity without individual level frequency bias.

A requirement of culture, whether animal or human, is some degree of conformity of behavior within populations. Researchers of gene-culture coevolution have suggested that population level conformity may result from frequency-biased social learning: individuals sampling multiple role models and preferentially adopting the majority behavior in the sample. When learning from a single role model, frequency-bias is not possible.

Memory CD4 T cell subsets are kinetically heterogeneous and replenished from naive T cells at high levels.

Characterising the longevity of immunological memory requires establishing the rules underlying the renewal and death of peripheral T cells. However, we lack knowledge of the population structure and how self-renewal and de novo influx contribute to the maintenance of memory compartments. Here, we characterise the kinetics and structure of murine CD4 T cell memory subsets by measuring the rates of influx of new cells and using detailed timecourses of DNA labelling that also distinguish the behaviour of recently divided and quiescent cells.

Random synaptic feedback weights support error backpropagation for deep learning.

The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learning, the backpropagation algorithm assigns blame by multiplying error signals with all the synaptic weights on each neuron's axon and further downstream.

The learning of action sequences through social transmission.

Previous empirical work on animal social learning has found that many species lack the ability to learn entire action sequences solely through reliance on social information. Conversely, acquiring action sequences through asocial learning can be difficult due to the large number of potential sequences arising from even a small number of base actions. In spite of this, several studies report that some primates use action sequences in the wild.

Correlations in fertility across generations: can low fertility persist?

Correlations in family size across generations could have a major influence on human population size in the future. Empirical studies have shown that the associations between the fertility of parents and the fertility of children are substantial and growing over time. Despite their potential long-term consequences, intergenerational fertility correlations have largely been ignored by researchers.

Inclusive fitness analysis on mathematical groups.

Recent work on the evolution of behaviour is set in a structured population, providing a systematic way to describe gene flow and behavioural interactions. To obtain analytical results one needs a structure with considerable regularity. Our results apply to such "homogeneous" structures (e.

Why copy others? Insights from the social learning strategies tournament.

Social learning (learning through observation or interaction with other individuals) is widespread in nature and is central to the remarkable success of humanity, yet it remains unclear why copying is profitable and how to copy most effectively. To address these questions, we organized a computer tournament in which entrants submitted strategies specifying how to use social learning and its asocial alternative (for example, trial-and-error learning) to acquire adaptive behavior in a complex environment. Most current theory predicts the emergence of mixed strategies that rely on some combination of the two types of learning.

Next-generation tools for evolutionary invasion analyses.

Evolutionary invasion analysis is a powerful technique for modelling in evolutionary biology. The general approach is to derive an expression for the growth rate of a mutant allele encoding some novel phenotype, and then to use this expression to predict long-term evolutionary outcomes. Mathematically, such 'invasion fitness' expressions are most often derived using standard linear stability analyses from dynamical systems theory.