Quantifying Multi-neuronal Olfactory Responses in <i>C. elegans</i>
ORAL
Abstract
Complex animal behaviors arise in response to an organism’s environment, as perceived through its senses. Unlike other stimuli animals experience, such as light or sound, chemosensory stimuli form a high dimensional space, making the computational problem faced by organisms interpreting olfactory cues especially complex. The processes by which olfactory information is encoded are poorly understood.
To better understand ensemble-level olfactory representation, we record from all sensory neurons in the nematode C. elegans simultaneously, while presenting stimuli in a highly controlled manner in a microfluidics environment. Observing the dynamics of these neurons in response to odors and odor mixtures of varying identity and strength has allowed us to build a quantitative and comprehensive picture of the way the olfactory system in C. elegans consolidates and represents high-dimensional sensory information. Our results suggest that olfactory stimuli are represented by distinct constellations of multiple chemosensory neurons, and that response characteristics of individual neurons is odor-dependent.
To better understand ensemble-level olfactory representation, we record from all sensory neurons in the nematode C. elegans simultaneously, while presenting stimuli in a highly controlled manner in a microfluidics environment. Observing the dynamics of these neurons in response to odors and odor mixtures of varying identity and strength has allowed us to build a quantitative and comprehensive picture of the way the olfactory system in C. elegans consolidates and represents high-dimensional sensory information. Our results suggest that olfactory stimuli are represented by distinct constellations of multiple chemosensory neurons, and that response characteristics of individual neurons is odor-dependent.
*This work was supported by an NSF BRAIN EAGER grant, the NSF Ideas Lab: Cracking the Olfactory Code, and an NIH PO1 grant.
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Presenters
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Albert Lin
- Department of Physics, Harvard University