# Neural basis of Depth Perception

> **NIH NIH R01** · UNIVERSITY OF ROCHESTER · 2020 · $385,000

## Abstract

Accurate perception of the three-dimensional (3D) structure of the environment is essential to
daily function. 3D vision requires the brain to reconstruct the depth structure of the environment
from the sequence of 2D retinal images arriving at the eyes. Most of our knowledge about the
neural mechanisms of 3D vision is limited to the case of stationary observers viewing static
surfaces; in contrast, objects typically move in depth and observers often need to judge 3D
scene structure while they are also moving. To arrive at a deeper understanding of how the
brain computes depth under dynamic viewing conditions, we need to elucidate the mechanisms
by which visual neurons compute the motion of objects in depth, as well as the neural
computations that underlie perception of depth from motion parallax cues that arise during self-
motion. We propose a series of experiments that take important steps toward this more general
understanding of the neural basis of depth perception. Aim #1 examines the mechanisms by
which neurons signal motion-in-depth via binocular cues. Recent work established that neurons
in area MT signal motion-in-depth based on both interocular velocity differences and changing
disparity cues, but the mechanisms of this selectivity remain unknown. Aim #2 examines how
global patterns of rotational optic flow resulting from observer movement are used by the brain
to interpret depth from motion parallax. We hypothesize that these “dynamic perspective” cues
are encoded by neurons in area MSTd with very large receptive fields, and that these neurons
also carry integrated efference copy signals regarding eye rotation. Aim #3 examines how extra-
retinal signals related to eye and body rotation are combined and used to compute depth from
motion parallax. At both neural and behavioral levels, we test a specific theoretically-motivated
hypothesis for how eye and body rotation signals should be integrated to compute depth. A
major strength of the proposed work is that it rigorously explores the interaction of multiple
visual and extra-retinal signals in tightly-controlled experiments with clear theoretical
predictions. The proposed research is directly relevant to the research priorities of the
Strabismus, Amplyopia, and Visual Processing program at the National Eye Institute.

## Key facts

- **NIH application ID:** 9897640
- **Project number:** 5R01EY013644-19
- **Recipient organization:** UNIVERSITY OF ROCHESTER
- **Principal Investigator:** GREGORY C DEANGELIS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $385,000
- **Award type:** 5
- **Project period:** 2001-07-05 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9897640

## Citation

> US National Institutes of Health, RePORTER application 9897640, Neural basis of Depth Perception (5R01EY013644-19). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9897640. Licensed CC0.

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