Lecturer: Sagi Levy
Abstract:
A main goal in neuroscience is understanding how the brain translates environmental information into sensory activity and behavior. Here we combine quantitative experiments and mathematical modeling to identify computational mechanisms underlying chemosensory activity and navigational decisions in the nematodeC. elegans. We develop new microfluidic devices, imaging setups and software for quantification of neuronal activity and animal behavior, allowing systematically comparison of alternative sensation models. We derive a mathematical model in which sensory activity is regulated by a threshold that continuously adapts to odor history, allowing animals to compare present and past odor concentrations. The model predicts sensory activity and behavior during animal navigation in different odor gradients and across a broad stimulus regime, and unifies previous sensation models under one general mechanism. Our genetic studies demonstrate that the cGMP-dependent protein kinase EGL-4 determines the timescale of threshold adaptation, defining a molecular basis for a critical model feature. Our theoretical analysis shows that the adaptive-threshold model filters stimulus noise efficiently, allowing reliable sensation in fluctuating environments. The adaptive-threshold model represents a general feed-forward sensory mechanism with implications in other sensory systems, such as zebrafish vision.