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Authors: Liu, Mochi
Advisors: Leifer, Andrew M
Shaevitz, Joshua W
Contributors: Quantitative Computational Biology Department
Keywords: behavior
C. elegans
reverse correlation
Subjects: Neurosciences
Issue Date: 2020
Publisher: Princeton, NJ : Princeton University
Abstract: One of the fundamental problems in neuroscience is how behavior is generated from sensory input and internal neural states, such as the animal’s behavioral context. We present new methods and findings to address this by studying the model organism Caenorhabditis elegans. With a fully mapped connectome of 302 neurons, this nematode is a particularly good candidate to investigate the neural basis of behavior due to its rich history of scientific research and its optical transparency. First, we showcase an instrument that can record panneuronal calcium activity in the head of a freely moving worm at single neuron resolution. We find multiple neurons have correlated activity with behaviors such as forward, backward, and turning locomotion. We also developed a high-throughput method to measure sensorimotor transformations from soft touch stimulation to locomotory behavior. We use automated behavior segmentation and reverse correlation to reveal how mechanosensory stimuli influences behavioral transitions. Our results show that C. elegans make locomotory decisions based on both the temporal history of the stimulus and its own behavioral context in a predictable manner. Continuing our investigation of the soft touch circuit, we developed a more advanced apparatus that can probe worm behavioral response to excitatory and inhibitory optogenetic stimuli with sub-animal level spatial resolution. This instrument has the ability to target the heads and tails of many animals in parallel, and can tailor the stimuli based on real-time behavior information. Preliminary experiments demonstrate that it can evoke the same optogenetically driven touch response akin to mechanical activation of the touch neurons.
Alternate format: The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog:
Type of Material: Academic dissertations (Ph.D.)
Language: en
Appears in Collections:Quantitative Computational Biology

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