On July 11, Joseph Shomar successfully defended the thesis “Visual Circuits for Distance Estimation in Walking Drosophila” (advisor: Damon Clark).
Shomar explained, “Though depth perception is a common task for many sighted organisms and is algorithmically well theorized, there have been no neurons to date shown to be causally linked to this task in the brain of any animal. I developed a new high throughout experiment that allowed us to very efficiently measure depth perception in flies and used it to discover two feature detecting neurons that causally control depth perception for the first time.
Using mathematical models and simulations, I then explain the response properties of these neurons in the context of motion parallax detection algorithms.”
He hopes to begin a career sports analytics for an MLB team where he will use player tracking data to identify advantageous features in batting stance and swing kinematics to help optimize player performance and provide a competitive advantage to the team.
 |
 |
Thesis abstract
Animals are often tasked with determining how far away salient objects are in order to successfully navigate and survive in their environment. Here, we design a novel high-throughput assay in which several individually compartmentalized Drosophila encounter various differently sized gaps during free locomotion. Using this assay, we conduct a targeted screen to identify neurons that contribute to the fly’s ability to visually determine the size of the gaps they encounter. We find that silencing T4 and T5 neurons, the primary motion detectors in the fly visual system, eliminates flies’ ability to estimate distances in this paradigm. Additionally, we identify a visual projection neuron in the lobula, LC15, as a key contributor to the fly’s ability to estimate distances. Using two-photon microscopy and in vivo calcium indicators, we characterize the response properties of LC15 neurons to various distance-like visual stimuli. The response properties suggest that the neuron encodes signals relevant for the implementation of a motion parallax algorithm. Simulations of object motion in the visual field of a moving observer provide further interpretation of LC15’s response properties in the broader context of motion parallax.