Sensory Integration for Heading Perception

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The proposed research seeks to understand the neural circuits by which we perceive our self-motion through space and by which we judge the motion of objects relative to ourselves. The visual system processes large- scale patterns of retinal image motion (optic flow) to estimate the direction of self-motion (or heading). However, optic flow is contaminated by our own eye and head movements, as well as motion of objects in the world. As a result, the visual system likely cannot solve these problems on its own. We seek to understand how neural circuits in extrastriate cortex of macaques combine visual motion with vestibular signals and other sources of non-visual input (e.g., efference copy of eye movements) to solve the complex intertwined problems of estimating self-motion and object motion. We approach this through a combination of electrophysiological and computational studies in trained animals. In Aim 1, we propose a general computational framework (multisensory normalization) that accounts for diverse observations regarding integration of multiple sensory inputs by single neurons. We devise and test a critical prediction of the model to establish whether multisensory normalization takes place in area MSTd, which is involved in visual-vestibular integration for self- motion perception. In Aim 2, we examine how eye and head rotations alter the tuning of MSTd neurons for heading as defined by optic flow and vestibular inputs. We use a population decoding approach to quantify the relative contributions of extra-retinal signals and visual depth information to stabilizing the heading tuning of neurons during eye/head rotation. In Aim 3, we examine the interactions between object motion and self- motion and explore the contributions of vestibular inputs to dissociating self-motion and object motion in two subdivisions of area MST. In broad terms, this research addresses the general problem of how critical variables of interest (e.g., heading) are extracted from neural activity that is influenced by confounding internal and external variables, and thus has broad application to many problems in systems neuroscience. The proposed research is directly relevant to the research priorities of the Strabismus, Amplyopia, and Visual Processing program at the National Eye Institute