STAR 2021 Scholar
Title: Uncovering motor circuits involved in sensorimotor transformations using novel electron microscopy analysis tools
Sensorimotor transformation is the process by which sensory stimulus is converted to motor response. This is essential for survival as they lead to behaviors. We know less about how motor codes are relayed to motor circuits that drive a behavior because we do not know the connectivity of circuits within the spinal cord. We overcome this limitation by investigating sensorimotor connections within the fruit fly D. melanogaster, using a complete electron microscopy (EM) dataset of the ventral nerve cord (VNC, fly "spinal cord"). The VNC is accessible in insects because there is no vertebra, and their small size allows them to be a great model for human behavior. We first examine and compare new toolkits including Fly Wire, NeuPrint, and CATMAID that can be used to analyze EM data. We apply these tools to map out key neural connections within sensorimotor circuits that drive well-defined behaviors. We identify interneurons and motorneurons postsynaptic to descending neurons that are hypothesized to drive escape behaviors, like the Giant Fiber. Tracing the connectivity of these descending neurons gives insight into the specifics of fly behaviors and provides a better understanding of how sensorimotor circuits control motor output.
Title: Uncovering motor circuits involved in sensorimotor transformations using novel electron microscopy analysis tools
Sensorimotor transformation is the process by which sensory stimulus is converted to motor response. This is essential for survival as they lead to behaviors. We know less about how motor codes are relayed to motor circuits that drive a behavior because we do not know the connectivity of circuits within the spinal cord. We overcome this limitation by investigating sensorimotor connections within the fruit fly D. melanogaster, using a complete electron microscopy (EM) dataset of the ventral nerve cord (VNC, fly "spinal cord"). The VNC is accessible in insects because there is no vertebra, and their small size allows them to be a great model for human behavior. We first examine and compare new toolkits including Fly Wire, NeuPrint, and CATMAID that can be used to analyze EM data. We apply these tools to map out key neural connections within sensorimotor circuits that drive well-defined behaviors. We identify interneurons and motorneurons postsynaptic to descending neurons that are hypothesized to drive escape behaviors, like the Giant Fiber. Tracing the connectivity of these descending neurons gives insight into the specifics of fly behaviors and provides a better understanding of how sensorimotor circuits control motor output.