Overview
Our laboratory gathers theoretical physicists, software engineers, applied mathematicians, and biologists to address decision-making in various biological systems. Our overarching research interests are the organizing principles of biological information processing. More precisely, we seek these organizing
principles in the physics underlying the computations in an animal’s nervous system and the physics of its sensory environments. To approach these principles, we previously developed models and statistical analysis frameworks that allowed us to describe bacterial chemotaxis, olfactory search strategies without spatial perception in insects, and synaptic variability in the random walk dynamics of neurotransmitter receptors.
We now seek to understand how evolution shapes efficient, small biological neural networks in
insects, allowing them to process complex sensory signals in their environments and generate complex
behaviours. We address these questions by combining physical modelling, Bayesian inference, numerical simulations, information theory, and biological experiments.
