(4hz) Microfluidic and Computational Tools for Behavior-coupled Functional Analysis of Neural Networks in C. elegans

I am interested in a postdoctoral opportunity where I can leverage my interdisciplinary expertise in microfluidics, biomarker detection, neuroscience, and machine-learning-based image processing to develop new technologies in healthcare, including diagnostics, therapy, and preventive care. My interests include, but are not limited to, wearable biosensors and brain-machine interfaces.

Abstract:

Understanding the connection between brain activity and behavior is one of central pursuits in neuroscience. Studying the roundworm C. elegans enables the investigation of this connection for all neurons in the nervous system at the level of individual cells. However, there are technical limitations that impede the acquisition of neural activity of many neurons and the animal’s concurrent behavior. As a result, how a sensory input is processed by multiple neurons and their organizations to produce outcome behaviors in C. elegans remains elusive. In my research, I introduce technical innovations to gain clues for answering this question. First, I developed two different methods to selectively fix the head region of the worm to allow for recording of the animal’s behavior during calcium imaging and chemosensory stimulation. Second, I developed an automatic image processing tool to detect and identify many neurons in multi-cell images of C. elegans nervous system. Lastly, leveraging the first two innovations, I investigated how the C. elegans responds to chemosensory stimuli neuronally and behaviorally in the context of attractive/repulsive odor encounters and olfactory learning. The tools I developed open new avenues for C. elegans research, in which the neuronal and behavior information are easily accessible during chemical stimulation. Likewise for my future research, I would like to develop new diagnostic and therapeutic tools that address real-world challenges in healthcare.