Sensory-guided navigation is crucial for survival and generic across species of all scales.
Animals can dynamically adjust their behavioral response depending on the environment, their internal states, and learned experiences. To understand these behavioral dynamics, we study olfactory learning and navigation strategies in the nematode C. elegans. We used a novel apparatus and optogenetics to measure and then model learned odor-navigation strategies in worms. Specifically, we constructed an experimental apparatus that enables precise control and monitor of odor concentration along the animal’s navigation path. This odor flow system enables quantitative study of behavioral strategies in small animals. On the order of hours, worms can associate butanone odor with food (appetitive training) or starvation (aversive training). After training, we recorded navigation in the controlled sensory environment. We developed a statistical model that incorporates behavioral strategies in worm navigation. By fitting the model to navigation trajectories after training, we find that the worms can differentially alter strategies depending on the appetitive or aversive training. Given finite data, the model successfully decodes the learned experience with >90% accuracy and outperforms classical chemotaxis metric. Furthermore, the model predicts impulse responses under optogenetic perturbation in an olfactory neuron and characterizes behavioral variability. Lastly, we extended to a dynamical model that incorporates strategies depending on internal states and discovered a better fit to data. State-dependent strategies achieve a normatively better solution to the olfactory navigation problem. We discuss progress towards identifying neural circuits underlying learning and state-dependency through neural ablation and optogenetic perturbation. By combining modeling approaches with measurements of odor-guided behavior, our study provides a new paradigm for understanding state-dependent navigation and olfactory learning in C. elegans.
Host: Thierry Emonet
Physics & QBio Special Seminar: Kevin S Chen, Princeton University, “Behavioral dynamics and Neural Computation for Olfactory Navigation in C. elegans”
Event time:
Wednesday, November 29, 2023 - 10:00am to 11:00am
Location:
Bass Center for Molecular and Structural Biology
266 Whitney Avenue
New Haven, CT
06511
Speaker/Performer:
Kevin S Chen, Princeton University
Event description:
Admission:
Free
Contact: