Decoding Olfaction in C. Elegans with Integrated Cellular and Circuit Modeling

Animals interact with a constantly changing environment and must adapt their behavior accordingly to survive. How does a nervous system make sense of the outside world to generate appropriate behavioral output? In particular, how are external and internal stimuli encoded into patterns of neuronal activity and computed at the neuronal, circuit, and system levels? We will address these fundamental questions using the nematode worm Caenorhabditis elegans as a model organism. C. elegans is a powerful genetic model with an anatomically small and well-defined nervous system that enables the unraveling of the entire circuitry with single-cell resolution. Through a combination of electrophysiology, in vivo calcium imaging, and behavioral analysis, we aim to match single-neuron biophysics to their intrinsic computational functions and emergent circuit properties. Guided by this empirical data and the available connectome information, we propose to construct a circuit-level model that can simulate information flow, network dynamics, and motor output in the olfactory circuit in C. elegans. By computational ablation validated through experimental observation, such a model would allow us to eventually understand how a simple circuit generates a well-defined chemotaxis behavior. Since biophysical and molecular mechanisms underlying neuronal function and mathematical algorithms used by neural computation are often conserved between species through evolution, we expect that the knowledge gained from the worm will help us understand more complex nervous systems like the human brain.