Developing code to image neuronal activity in a simple nervous system.
We examine how the brain generates persistent behavioral states like sleep/wake and emotional states. In mammals, the circuits controlling these states include millions of neurons, making them challenging to study. Using the nematode C. elegans, which has only 302 neurons, we have identified neural circuits that generate long-lasting locomotor states that animals display as they forage for food. We are developing tools for monitoring the activity of all of the neurons in these circuits simultaneously in moving animals, with the goal of understanding how activity within these circuits drives long-lasting behavioral states. We also hope that these studies will provide a platform for a mechanistic analysis of how persistent neural activity arises in circuits.
Current projects are centered around the imaging technologies and data analysis pipelines that will enable this project. Current challenges that need to be addressed include: (1) Developing a closed feedback loop where a microscope stage is controlled by animal movement to keep the animal in field of view, (2) Developing image analysis tools to identify and track each neuron throughout long multi-neuron recordings in moving animals, (3) Applying analysis tools from dynamical systems theory and machine learning to relate neural activity to behavior.
Students should have a fairly strong background in computer programming. Experience in C and/or Matlab is preferable. Familiarity with data analysis tools (PCA, etc) would also be helpful. Students should also be detail-oriented and have an interest in learning about cellular and systems neuroscience. Preference will be given to students who are able to commit ~10 hours per week. For sophomores and juniors, this position could be open to a longer-term commitment.
Please contact Steve Flavell with your resume/CV, and highlight programming and research experiences that may be relevant.