The human brain devotes enormous resources toward providing a cyclopean view of the world, by combining the separate inputs from the two eyes. The resulting binocular vision has substantial benefits in the form of stereopsis. In addition to the well-documented monocular deficits, humans with amblyopia (a developmental disorder affecting 2-3% of the general population) also suffer abnormal depth perception, and many more individuals are stereo-blind. However, the binocular deficits in amblyopia have seldom been assessed over the whole range of binocular disparity. In this project, we propose to use a novel rating-scale method to evaluate depth perception over the whole range of binocular disparities, and to use dynamic bandpass noise stereograms with depth corrugation to reveal spatial properties of depth profiles, and to develop and test a new model to predict depth perception pixel-by-pixel over a very broad range of stimulus conditions. The long-term objectives of this project are to understand how the brain combines the two eyes' inputs to form 3D images in humans with normal and abnormal binocular vision. We propose to develop a novel 3D model by combining a disparity sensitivity model with our previous 2D model.
Aim 1 : Mechanisms of depth perception. We propose to develop and test a new depth perception model with a filter/binocular-energy/filter (F-BE-F) structure, to predict depth perception pixel by pixel over a very broad range of conditions. The two eyes images pass through first-stage spatiotemporal filters to calculate the normalized binocular-energy (BE), which goes through a maximum (MAX) operator for solving the correspondence problem, then goes through a disparity window to compute local depth quantities, and finally through a second stage of spatiotemporal filtering to give the final perceived depth profile. Different mechanisms of depth perception in human vision can be isolated by different normalizations of the BE and different spatiotemporal properties of depth perception.
Aim 2 : Spatiotemporal properties of depth perception. Our preliminary experiments suggest that depth perception is dependent on stimulus size and duration, which can be explained by a second stage of spatiotemporal filtering. We will further study these spatiotemporal properties of depth perception (a) at different stimulus spatial frequencies; (b) at different stimulus orientations; (c) at different pedestal disparities in the reference background. (d) We will perform both experiments and model simulations to extract form information from stereograms with varying spatiotemporal depth profiles.
Aim 3 : Abnormal depth perception in amblyopia. We will measure and model depth perception in humans with abnormal binocular vision due to amblyopia. We will measure depth perception over a large range of conditions, simulating abnormalities both empirically (by stimulus manipulation), and theoretically, by making `lesions' in our model, in order to determine the nature and cause of reduced stereopsis in amblyopia.

Public Health Relevance

Amblyopia is a developmental disorder of spatial vision usually associated with the presence of strabismus and/or anisometropia early in life. People with amblyopia often suffer lower visual acuity, lower contrast sensitivity, binocular asymmetry, and abnormal stereovision. Our goal is to develop a novel method to access the binocular system in both normal and amblyopic vision, and to isolate different mechanisms of depth perception and specify deficits of depth perception in amblyopia.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
1R01EY030544-01A1
Application #
9912390
Study Section
Mechanisms of Sensory, Perceptual, and Cognitive Processes Study Section (SPC)
Program Officer
Araj, Houmam H
Project Start
2020-02-01
Project End
2023-12-31
Budget Start
2020-02-01
Budget End
2020-12-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of California Berkeley
Department
Type
Schools of Optometry/Opht Tech
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704