Master in Physics of Complex Systems at Université de Paris
Structural Basis of Neural Computation and Behavior.
Behavior and decision-making are determined by physical processes taking place in the complex environment of the nervous system. During the last 3-5 years, breakthroughs in experimental techniques have made it possible to map the wiring diagram (the physical connectome) of the full central nervous systems of simple model organisms at the level of single synapses and portions of the brain for higher animals. Moreover, we can now control the activity of individual neurons in live animals through optogenetic stimulation and record the resulting behavior. Together this offers the occasion to reverse engineer the physical basis of behavior. The current project aims to leverage simultaneous access to the wiring of the central nervous system of Drosophila melanogaster larva and to existing data from large-scale behavior screens, which record the effect of individual activation or silencing of the majority of the larva’s neurons, in order to address the following question: What constraints do the structure of the connectome impose on an organism’s capability to process information and encode behavior? Specifically, it will combine modern methods from machine learning and network science to investigate how the circuitry of the Drosophila larva’s nervous system influences the way it encodes behavior.