Publié le 26 mars 2021–Mis à jour le 8 février 2022
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e-Guest Lecture : Fernando Peruani
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Towards a unified, quantitative understanding of self-organization in biology: From bacterial systems to decision-making and collective intelligence in animal groups
Fernando Peruani est Professeur au laboratoire LPTM à CY Cergy Paris Université
The underlying assumption is that many biological systems across scales, from ensembles of cells to animal groups, are likely to share similar statistical properties as occurs in equilibrium physical systems. Under this assumption, it is expected that the large-scale properties of biological self-organized processes can be described using a common mathematical framework. Here, we will illustrate this idea by applying the same theoretical framework to understand intermittent collective motion in bacterial systems and sheep herds. These two biological systems are, however, despite certain similarities in their mathematical description, fundamentally different. Sheep herds display highly synchronized intermittent collective motion. Furthermore, behavioral shifts propagate via imitation over the group and collective decision-making mechanisms are at work. Moreover, we will see that sheep self-organize their behavior via a democratic leadership scheme, which allows individuals to perform information pooling, and for the group to display collective intelligence.