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

Public Health Relevance

Understanding the neural basis of self-motion perception may promote new strategies for treating spatial disorientation in patients with neurodegeneration such as Alzheimer's disease. Alzheimer's disease is widely known as a memory disorder, but is also accompanied by severe perceptual deficits including impaired ability to judge heading. A deeper understanding of these functions in a primate model will help in targeting new therapies to relevant brain areas and in developing training-based recovery programs.

National Institute of Health (NIH)
National Eye Institute (NEI)
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Special Emphasis Panel (ZRG1-IFCN-L (02))
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Steinmetz, Michael A
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University of Rochester
Schools of Arts and Sciences
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Gu, Yong; Angelaki, Dora E; DeAngelis, Gregory C (2014) Contribution of correlated noise and selective decoding to choice probability measurements in extrastriate visual cortex. Elife 3:
Chen, Xiaodong; DeAngelis, Gregory C; Angelaki, Dora E (2014) Eye-centered visual receptive fields in the ventral intraparietal area. J Neurophysiol 112:353-61
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Gu, Yong; Deangelis, Gregory C; Angelaki, Dora E (2012) Causal links between dorsal medial superior temporal area neurons and multisensory heading perception. J Neurosci 32:2299-313
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Gu, Yong; Liu, Sheng; Fetsch, Christopher R et al. (2011) Perceptual learning reduces interneuronal correlations in macaque visual cortex. Neuron 71:750-61
Ohshiro, Tomokazu; Angelaki, Dora E; DeAngelis, Gregory C (2011) A normalization model of multisensory integration. Nat Neurosci 14:775-82

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