We are interested in understanding how behavior is connected to neural dynamics, internal biological factors, such as age, or hunger, and external environmental conditions. Because behavior is a complex, high-dimensional phenomenon, we engineer novel high-throughput imaging systems to acquire large volumes of postural data under well-controlled conditions [1,2,3], and develop complementary computational techniques for processing and understanding the dynamics [4,5].
Highlighted Lab Publications
- Bates K., Le K.N., Lu H., Deep learning for robust and flexible tracking in behavioral studies for C. elegans. PLOS Computational Biology. 2022, 18. https://doi.org/10.1371/journal.pcbi.1009942
- Sun, G., Manning, C.-A., Lee, G. H., Majeed, M., Lu, H., Microswimmer Combing: Controlling Interfacial Dynamics for Open-Surface Multifunctional Screening of Small Animals. Adv. Healthcare Mater. 2021, 10, 2001887. https://doi.org/10.1002/adhm.202001887
- Thomas, A., Bates, K., Elchesen, A., et al. Topological Data Analysis of C. elegans Locomotion and Behavior. Frontiers in Artificial Intelligence. 2021, 4. https://doi.org/10.3389/frai.2021.668395
- Le, K.N., Zhan, M., Cho, Y., et al. An automated platform to monitor long-term behavior and healthspan in Caenorhabditis elegans under precise environmental control. Commun Biol. 2020, 3. https://doi.org/10.1038/s42003-020-1013-2
- Aubry, G., Lu, H., Droplet array for screening acute behaviour response to chemicals in Caenorhabditis elegans. Lab on a Chip. 2017, 24. https://doi.org/10.1039/C7LC00945C
