We live in a three-dimensional (3D) environment, and accurate perception of the 3D structure of the visual scene is crucial for many daily activities. Although much is known about human perception of depth from multiple cues (such as binocular disparity, motion parallax, and texture), our understanding of the neural mechanisms of depth perception remains very incomplete. This proposal addresses three fundamental issues regarding the neural basis of depth perception.
Aim #1 examines the neural representation of 3D surface structure based on smooth spatial variations in binocular disparity. We will characterize how neurons in extrastriate visual cortex code the orientation and spatial frequency of depth corrugations defined by disparity gradients, and we will explore whether linear or nonlinear receptive field mechanisms are involved in such selectivity. In addition, we will reversibly inactivate these brain regions to probe for causal links between neural activity and perception of disparity-defined surface structure.
Aim #2 provides the first direct tests of a potential neural substrate for depth perception from motion parallax. We will train monkeys to discriminate depth from motion parallax, and will use single-unit recordings and electrical microstimulation to test the hypothesis that area MT plays an important functional role in this form of depth perception.
Aim #3 tackles a major unexplored question: how do we detect objects moving in 3D space during self-motion? We have devised a novel behavioral task to demonstrate that detecting inconsistencies between two depth cues--disparity and motion parallax--provides a robust mechanism for detecting object motion, and we test the hypothesis that neurons in area MT with incongruent depth tuning for disparity and motion parallax play an important role in this process. This research addresses the general problem of how neural circuits extract specialized information from the visual scene that is computationally important for solving specific behavioral tasks, 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

The health-related value of this work will follow from a deeper understanding of how cognitive functions can be explained in terms of neural activity, as this will ultimately elucidate causes of various mental disorders. This work will also likely have practical applications to the development and assessment of 3D virtual environments which have growing importance in both commercial and entertainment applications. Basic science will aid development of virtual environments that are compelling, safe, and ergonomic.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY013644-14
Application #
8710222
Study Section
Central Visual Processing Study Section (CVP)
Program Officer
Araj, Houmam H
Project Start
2001-07-05
Project End
2016-07-31
Budget Start
2014-08-01
Budget End
2015-07-31
Support Year
14
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Rochester
Department
Miscellaneous
Type
Schools of Arts and Sciences
DUNS #
City
Rochester
State
NY
Country
United States
Zip Code
14627
Zaidel, Adam; DeAngelis, Gregory C; Angelaki, Dora E (2017) Decoupled choice-driven and stimulus-related activity in parietal neurons may be misrepresented by choice probabilities. Nat Commun 8:715
Kim, HyungGoo R; Angelaki, Dora E; DeAngelis, Gregory C (2017) Gain Modulation as a Mechanism for Coding Depth from Motion Parallax in Macaque Area MT. J Neurosci 37:8180-8197
Kim, HyungGoo R; Angelaki, Dora E; DeAngelis, Gregory C (2015) A novel role for visual perspective cues in the neural computation of depth. Nat Neurosci 18:129-37
Kim, HyungGoo R; Angelaki, Dora E; DeAngelis, Gregory C (2015) A functional link between MT neurons and depth perception based on motion parallax. J Neurosci 35:2766-77
Sanada, Takahisa M; DeAngelis, Gregory C (2014) Neural representation of motion-in-depth in area MT. J Neurosci 34:15508-21
Nadler, Jacob W; Barbash, Daniel; Kim, HyungGoo R et al. (2013) Joint representation of depth from motion parallax and binocular disparity cues in macaque area MT. J Neurosci 33:14061-74, 14074a
Sanada, Takahisa M; Nguyenkim, Jerry D; Deangelis, Gregory C (2012) Representation of 3-D surface orientation by velocity and disparity gradient cues in area MT. J Neurophysiol 107:2109-22
Rao, Vinod; DeAngelis, Gregory C; Snyder, Lawrence H (2012) Neural correlates of prior expectations of motion in the lateral intraparietal and middle temporal areas. J Neurosci 32:10063-74
Anzai, Akiyuki; Chowdhury, Syed A; DeAngelis, Gregory C (2011) Coding of stereoscopic depth information in visual areas V3 and V3A. J Neurosci 31:10270-82
Anzai, Akiyuki; DeAngelis, Gregory C (2010) Neural computations underlying depth perception. Curr Opin Neurobiol 20:367-75

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