Sensing in a dynamic world: what the antennae of the fruit fly can teach us about sensation and the perception of movement

Presented at: Neuroscience 2020
C.E. Credits: P.A.C.E. CE Florida CE
  • Postdoctoral Fellow, NYU Neuroscience Institute, NYU Langone Medical Center
      Marie Suver is a postdoctoral fellow at the NYU Neuroscience Institute, working with Katherine Nagel. She received her PhD from the California Institute of Technology in Computation and Neural Systems, and her undergraduate degrees from the University of Washington in Biology and Computer Science. Marie's research combines electrophysiological, genetic, quantitative behavior and machine learning approaches to understand mechanisms of sensory-motor circuit function. Her research was previously supported by the Leon Levy Foundation and is currently funded by a BRAIN Initiative K99/R00 award from the NINDS.


    Normal behavior in any moving animal, including humans, relies on communication between motor systems that control movements, and the sensory systems we use to guide these actions. A critical task for the brain is distinguishing between sensations created by our own actions from those caused by external sources; disruptions in this process cause significant impairments in normal behavior. Yet the neural circuits that aid in this task are generally not well understood. To understand these processes at the cellular, circuit and behavioral level, I study the small, tractable brain of the fruit fly Drosophila melanogaster. In this presentation, I will describe current research focusing on the neural circuits that control movements and mechanosensation in the antennae of the fruit fly. Through this work, I aim to discover fundamental principles underlying the brain’s ability to make sense of its own movements through the world.

    Learning Objectives:

    1. Define active sensing

    2. Introduce the audience to tools and advantages of studying neural circuit function in the fruit fly (Drosophila melanogaster)

    3. Explain current strategies to develop the fruit fly as a model for active sensing

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