Download or read book Neural Basis of Object Motion Perception During Self-motion written by Nicole E. Peltier and published by . This book was released on 2020 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The ability to perceive independently moving objects during self-motion is vital for reaching goals and avoiding obstacles. Self-motion generates a structured pattern of retinal motion called optic flow. An independently moving object produces retinal motion that is the vector sum of its world-relative motion and the optic flow created by the observer's self-motion. To interpret the object's world-relative motion, an observer must compensate for their self-motion. The flow-parsing hypothesis posits that the visual system may accomplish this compensation by globally subtracting out the optic flow due to self-motion (Rushton & Warren, 2005; P.A. Warren & Rushton, 2007, 2009a). This subtraction induces a perceptual bias (in retinal coordinates) away from the optic flow vector at the object's location. Despite psychophysical evidence for flow parsing in humans, the neural mechanisms underlying flow parsing remained unknown. This thesis presents the first evidence for a neural correlate to flow parsing in the middle temporal area (MT). First, we tested the flow-parsing hypothesis in an animal model using macaque monkeys. Two monkeys discriminated the direction of a moving object in the presence of optic flow simulating self-motion. Perception of object motion was biased in a manner consistent with flow parsing. Biases generally depended on the direction and magnitude of the optic flow vectors to subtract at the object's location. The addition of vestibular self-motion cues increased flow-parsing biases in a multiplicative manner. This perceptual evidence of flow parsing in monkeys positioned us to investigate its neural mechanisms. Next, we recorded neural activity in area MT while monkeys performed the same flow-parsing discrimination task. The responses of individual MT units to object motion were modulated by optic flow, and this modulation depended on a unit's direction tuning. We used population decoding to demonstrate that MT populations convey information about choice, retinal object motion, and world-relative object motion. Finally, we characterized the effect of optic flow on MT direction tuning curves by modeling each unit's reference frame as a weighted average of retinal and world-centered. The average MT unit modestly shifted its reference frame from retinal toward world-centered. These small shifts suggest that MT plays a role in a more extensive flow-parsing network"--Pages x-xi