Conférenciers invités

Nous aurons 3 conférences plénières

Dr. Christine ROLLARD, MNHN Paris

LES ARAIGNEES: MOEURS "REMARQUABLES"

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Pr. Manfred GAHR, Max Planck Institute of Ornithology, Seewiesen, Allemagne              

HORMONE-DEPENDENT VOCAL COMMUNICATION OF SONGBIRDS

Vocal communication including singing of songbirds is controlled by a multi-area circuit that is composed of steroid hormone-sensitive neuron populations. Most of these areas express androgen receptors, the target of testosterone; the song area HVC expresses in addition receptors for estrogens. Testosterone and its estrogenic derivatives affect vocal communication dynamics as well as song pattern. Testosterone and estrogen act locally in HVC to change gene expression in a species-specific manner since genomic hormone-sensitivity differs between songbird species. These hormone-driven changes of gene expression are area-specific, fast and concern many genes. In the canary, among these genes, one hub-gene is BDNF that induces singing with high repetition rates (a sexy song features) if locally overexpressed in HVC. In concert with other testosterone-dependent gene networks, elevated levels of BDNF facilitate differentiation of large song syllable repertoires. I further discuss how the hormones affect the anatomy and physiology of the syllable producing neural circuits.

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Dr. Roger MUNDRY, Max Planck Institute for Evolutionary Anthropology, Leipzig, Allemagne

DO WE REALLY NEED ALL THESE RANDOM SLOPES? ISSUES IN THE APPLICATION OF MIXED MODELS IN ANIMAL BEHAVIOUR RESEARCH

Linear Mixed Models (LMM) are increasingly used in animal behaviour research. However, other than more traditional methods LMMs represent a relatively novel statistical tool. As such they are still a matter of development and debate. For researchers in our field this means that there is uncertainty and disagreement about how to apply them appropriately. In my talk I focus on random slopes, currently a matter of quite some debate and uncertainty in our field. I shall explain what random slopes are and what they mean biologically and discuss their potential biological relevance. Furthermore, I shall present what we currently know and do not know about the behaviour of LMMs including or neglecting random slopes. Finally, I shall present results of simulation based investigations, conducted in order to close some of the gaps in our knowledge. In particular, I shall focus on the relevance of random slopes in non-Gaussian models (e.g., logistic and Poisson models) and issues potentially arising when trying to consider random slopes with data sets fairly typical in animal behaviour research, namely data characterized by a smaller sample size and imbalanced contributions of individuals. I conclude with some recommendations and pointing out open questions which warrant future research.