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    About the TICE Lab

    The multidisciplinary Theory in Cultural Evolution Lab (TICE Lab) is based in the Department of Human Behavior, Ecology and Culture (HBEC) at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany. The lab brings together a unique group of mathematicians, physicists, theoretical biologists, and statisticians contributing to a general theory of cultural evolution.

     

    Cultural evolution aims in part to explain the dynamics of cultural change, defined as changes in the frequency and diversity of cultural traits over time. We work on the premise that a mechanistic understanding of the processes underlying cultural change can help us to explain something about the human species beyond what can be gleaned from genetic or even cultural data alone. Thus, we aim to place the study of cultural evolution on a firm theoretical footing, and provide a bridge between that theory and the cultural data collected by anthropologists and archaeologists.

     

    To do this, we focus on developing analytical and simulation models of various cultural phenomena. The research themes section lists some current lab projects that illustrate the kind of research we do and outline the methods we use.

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    HBEC and the TICE lab

    At the Max Planck Institute for Evolutionary Anthropology

    The Department of Human Behavior, Ecology and Culture, headed by Director Richard McElreath, is a unique environment for theoreticians where there is daily interaction with field anthropologists and empirical researchers. The exchange of ideas, knowledge and data in the department is invaluable, it drives our theory towards useful and grounded questions and allows that theory, in turn, to shape the development of effective data collection and quantitative analysis in anthropology.

     

    The department is highly interdisciplinary with researchers from diverse backgrounds including comparative behavioral ecology, psychology, economics, archaeology, anthropology, evolutionary biology, statistics, and mathematics - all now focused on the study of human ecology and culture.

     

    Because of the diversity of our department and the value we place on interdisciplinary research, the TICE lab explicitly seeks students and post doctoral researchers from diverse backgrounds. We especially encourage applications from students with quantitative backgrounds. However, prospective students and post docs are not expected to have prior experience modelling cultural evolution. We offer a training program designed to enable students with more technical backgrounds to get to grips with evolutionary biology and cultural evolution, and to help students with less technical backgrounds improve their modelling skills.

     

  • Lab Members, Visitors, and Collaborators

    Senior Scientist

    Senior Scientist

    Senior Scientist

    PhD. Student

    PhD. Student

    Alfredo Cortell-Nicolau

    Humboldt Fellow

  • Research Themes

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    Cultural Adaptation and Gene-Culture co-Evolution

     

    Literature in cultural evolution often suggests that humans occupy much of the planet in part because of our ability to amass complex culture and to adapt culturally to new environments. However, we understand little about what this process of cultural adaptation and gene culture co-evolution might look like. We work on mathematical models that investigate the roles of cultural variation, cultural transmission, innovation, and gene-culture interactions in human adaptation. We also investigate ways in which we can use such models to identify cultural selective sweeps in cultural data, exploring the kind of data and analysis needed to infer selection and cultural adaptation.

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    Individual-Level Processes and Population-Level Patterns

    Understanding how group-level patterns of culture emerge from individual-level behaviour is a long-standing question in the biological and social sciences. We study whether, and under what conditions, different processes of cultural transmission can be distinguished based on their group-level signature, in an effort to establish theoretical limits to inference. We develop statistical inference frameworks to analyse real-world datasets. Borrowing from population genetics, we use generative inference approaches which evaluate the consistency between individual-level transmission processes and observed population-level patterns.

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    Demography and Cultural Evolution

     

     

    This research examines the interaction between subsistence strategy, demographic structure, and the spread of demographically important cultural traits affecting survival, fertility, or both. The work investigates how the cultural transmission of such traits can influence the birth rate, age structure, and asymptotic growth rate of a population. In particular, the ages at which different types of learning (for example, vertical or oblique learning) may be important can vary among populations, particularly those with different subsistence strategies, and this may have important effects on cultural evolutionary processes and, in turn, demographic structure itself.

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    Innovation and Creativity

    Creativity represents the starting point of the cultural evolutionary process but has typically received less attention in models of cultural evolution than, for example, modes of cultural transmission. Studies of the neuroscience and psychology of creativity have shown that it is a nuanced, idiosyncratic, and complex process that is rarely adequately captured by the single ‘cultural mutation rate’ that is often used in models. Our work aims to improve the representation of creativity in models of cultural evolution and to develop new theoretical frameworks to untangle the effects of cultural transmission and innovation on patterns of cultural accumulation.
     

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    Niche Construction and Cultural Niche Construction

    Niche construction is a process through which organisms modify their environment and, as a result, alter the selection pressures on themselves and other species. In cultural niche construction, one or more cultural traits can influence the evolution of other cultural or biological traits by affecting the social environment in which the latter traits may evolve. Cultural niche construction may include either gene-culture or culture-culture interactions. We develop models of this process and examine the interactions between cultural transmission, population structure, selection, and niche construction, in particular focusing on new models of niche construction and cultural niche construction with a view to resolving controversies surrounding the evolutionary importance of niche construction and driving forward our theoretical understanding of non-genetic inheritance.

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    Non-Equilibrium Models

    There is often a disconnect between mathematical models describing cultural systems and cultural data. Where the models focus on equilibrium states. Further, it is often unclear whether data is collected from a system in equilibrium. Reconciling the theory and the data requires models that can replicate the temporal dynamic that can be compared to the observed data.

  • Selected Publications

    Demography, Structure and Culture

    Kandler, A., Fogarty, L., & Karsdorp, F. (2023). The interplay between age structure and cultural transmission. PLoS Computational Biology, 19(7), 1–21. https://doi.org/10.1371/journal.pcbi.1011297

     

    Deffner, D., Kandler, A., & Fogarty, L. (2022). Effective population size for culturally evolving traits. PLoS Computational Biology, 18(4), 1–22. https://doi.org/10.1371/journal.pcbi.1009430

     

    Fogarty, L., Creanza, N., & Feldman, M. W. (2019). The life history of learning: Demographic structure changes cultural outcomes. PLOS Computational Biology, 15(4), e1006821. https://doi.org/10.1371/journal.pcbi.1006821

     

    Fogarty, L., Creanza, N., & Feldman, M. W. (2013). The role of cultural transmission in human demographic change: An age-structured model. Theoretical Population Biology, 88, 68-77.

     

    Kandler, A., Perreault, C., & Steele, J. (2012). Cultural evolution in spatially structured populations: A review of alternative modeling frameworks. Advances in Complex Systems,15(1-2): 1203001.

     

    Fogarty, L. and Feldman, M.W. (2011) The cultural and demographic evolution of son preference and marriage type in contemporary China. Biological Theory, vol. 3 no. 6, pp. 272-282.

     

    Rendell, L.E., Fogarty, L. & Laland, K.N. (2010) Rogers' paradox recast and resolved: population structure and the evolution of social learning strategies, Evolution, vol. 64, no. 2, pp. 534-548.

     

    Kandler, A. (2009). Demography and language competition. Human Biology,81(2-3), 181-210.

    Innovation, creativity, and cognition

    Ammar, M., Fogarty, L., & Kandler, A. (2023). Social learning and memory. Proceedings of the National Academy of Sciences of the United States of America, 120(33), 1–10. https://doi.org/10.1073/pnas.2310033120

     

    Fogarty, L. & Creanza, N. (2017) The niche construction of cultural complexity: interactions between innovations, population size, and the environment, Phil. Trans. R. Soc. B 372: 20160428

     

    Fogarty, L., Creanza, N. & Feldman, M.W. (2015) Cultural evolutionary perspectives on early human innovation. Trends in Ecology and Evolution, vol. 30, no. 12, pp. 736-754.

     

    Kandler, A., & Laland, K. N. (2009). An investigation of the relationship between innovation and cultural diversity. Theoretical Population Biology,76(1), 59-67.

     

    Kandler, A., & Steele, J. (2009). Innovation diffusion in time and space: Effects of social information and of income inequality. In Diffusion Fundamentals III: Athens 2009 (pp. 82-98). Leipzig: Leipziger Universitätsverlag.

     

    Kandler, A., & Steele, J. (2009). Social learning, economic inequality, and innovation diffusion. In M. O'Brien, & S. J. Shennan ( Eds. ), Innovation in cultural systems: Contributions from evolutionary anthropology (pp. 193-216). Cambridge, MA: MIT Press.

    Process to Patterns

    Yeh, D. J., Fogarty, L., & Kandler, A. (2019). Cultural linkage: The influence of package transmission on cultural dynamics. Proceedings of the Royal Society B: Biological Sciences, 286(1916). https://doi.org/10.1098/rspb.2019.1951

     

    Kandler, A., & Powell, A. (2018). Generative inference for cultural evolution. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences,373(1743).

     

    O'Dwyer, J. P., & Kandler, A. (2017). Inferring processes of cultural transmission: The critical role of rare variants in distinguishing neutrality from novelty biases. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences,372(1735): 20160426.

     

    Kandler, A., Wilder, B., & Fortunato, L. (2017). Inferring individual-level processes from population-level patterns in cultural evolution. Royal Society Open Science,4: 170949

     

    Kandler, A., & Powell, A. (2015). Inferring learning strategies from cultural frequency data. In A. Mesoudi, & K. Aoki ( Eds. ), Learning strategies and cultural evolution during the Palaeolithic (pp. 85-101). Tokyo: Springer Japan.

     

    Kandler, A., & Shennan, S. (2015). A generative inference framework for analysing patterns of cultural change in sparse population data with evidence for fashion trends in LBK culture. Journal of the Royal Society, Interface,12(113): 20150905.

     

    Wilder, B., & Kandler, A. (2015). Inference of cultural transmission modes based on incomplete information. Human Biology,87(3), 193-204.

    Culture and Adaptation

    Fogarty, L., & Kandler, A. (2020). The fundamentals of cultural adaptation: implications for human adaptation. Scientific reports, 10(1), 1-11.

     

    Fogarty, L., Wakano, J.Y., Feldman, M.W. & Aoki, K. (2016) The driving forces of cultural complexity: Neanderthals, modern humans, and the question of population size. Human Nature, doi:10.1007/s12110-016-9275-6

    Niche Construction and Cultural Niche Construction

    Fogarty, L., & Wade, M. J. (2022). Niche construction in quantitative traits: Heritability and response to selection. Proceedings of the Royal Society B: Biological Sciences, 289(1976). https://doi.org/10.1098/rspb.2022.0401

     

    Creanza, N., Fogarty, L. & Feldman, M.W. (2016) Cultural niche construction of repertoire size and learning strategies in songbirds. Evolutionary Ecology, vol. 30, pp. 285–305.

     

    Creanza N, Fogarty L., Feldman MW. (2014) Cultural niche construction from the Paleolithic to modern hunter-gatherers. Dynamics of Learning in Neanderthals and Modern Humans, Vol. 1: Cultural Perspectives.

     

    Creanza, N., Fogarty, L. & Feldman, M.W. (2012) Models of Cultural Niche Construction with Selection and Assortative Mating. PLoS ONE, vol. 7, no. 8, e42744

     

    Fogarty, L., Rendell, L.E. & Laland, K.N. (2012) The importance of space in models of social learning, cultural evolution and niche construction, Advances in Complex Systems vol. 15, no. 1&2.

     

    Rendell, L.E., Fogarty, L. & Laland, KN (2011) Runaway cultural niche construction, Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 366, no. 1566, pp. 823-835.

    Non-Equilibrium Models of Cultural Evolution

    Crema, E. R., Kandler, A., & Shennan, S. (2016). Revealing patterns of cultural transmission from frequency data: Equilibrium and non-equilibrium assumptions. Scientific Reports,6: 39122.

     

    Kandler, A., & Shennan, S. (2013). A non-equilibrium neutral model for analysing cultural change. Journal of Theoretical Biology,330, 18-25.

    Language Evolution

    Kandler, A., & Steele, J. (2017). Modeling language shift. Proceedings of the National Academy of Sciences,114(19), 4851-4853.

     

    Kandler, A., Unger, R., & Steele, J. (2010). Language shift, bilingualism and the future of Britain's Celtic languages. Philosophical Transactions of the Royal Society B: Biological Sciences,365(1559), 3855-3864.

     

    Steele, J., & Kandler, A. (2010). Language trees ≠ gene trees. Theory in Biosciences,129(2-3), 223-233.

     

    Kandler, A., & Steele, J. (2008). Ecological models of language competition. Biological Theory,3(2), 164-173.

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    Join The TICE Lab

    Please contact us if you are interested in post doctoral or PhD positions with the lab

    We are always keen to hear from potential PhD students or post-doctoral researchers with interest or experience in theoretical cultural evolution, especially from mathematical or quantitative backgrounds. We are open to individuals interested in specific projects above or with an interest in the general topics and themes of the lab.

     

    Potential PhD students who have a Masters Degree can apply through the International Max Planck Research School (IMPRS): the Leipzig School of Human Origins or contact us directly.

     

    Potential postdocs should contact the lab initially and can also apply for external funding - here is a useful list of funding opportunities.

     

    Please contact Laurel Fogarty or Anne Kandler with any questions.