# Neural mechanisms of optic flow processing for visually-guided control of steering

> **NIH NIH R01** · UNIVERSITY OF ROCHESTER · 2022 · $485,369

## Abstract

When an observer moves through the environment, self-motion creates large-field patterns of
visual motion known as optic flow. Cortical processing of optic flow is important for perception of
self-motion, as demonstrated in animal models. In most navigation behaviors, such as driving a
vehicle, optic-flow processing is part of an active sensing loop in which self-motion produces
optic flow which is, in turn, used to change direction at the next instant of time. While this is a
natural mode of optic flow processing, almost all previous studies of neural processing of optic
flow involve passive self-motion without an active control component. Indeed, the patterns of
optic flow that are experienced when steering a vehicle along a curved path are quite different
than those typically used to study cortical neurons. Thus, what we know about cortical
processing of optic flow is generally not applicable to control of steering. Furthermore, to
effectively steer, control theory indicates that optic flow signals should be combined with
efference copy of motor commands and working memory signals, but essentially nothing is
known about these critical interactions. We propose a tightly integrated program of research,
involving behavior, neurophysiology and theory, that will provide the first systematic study of the
neural mechanisms of visually guided steering control. In Aim #1, we train monkeys to steer
through a virtual environment to align their heading with the remembered direction of a briefly
flashed target. We develop optimal stochastic control theory for our task, and we fit the model to
behavioral data to extract estimates of key latent variables that govern steering control. In Aim
#2, we record from populations of neurons in areas MSTd and 7a during performance of the
steering task. Using both model-free and model-based analyses, we test specific hypotheses
about how and where the critical variables for steering control are represented in the brain. Our
strong preliminary data suggest that we will make important advances in understanding cortical
processing of optic flow in a more natural active-sensing context. The proposed research is
directly relevant to the research priorities of the Strabismus, Amblyopia, and Visual Processing
program at the National Eye Institute.

## Key facts

- **NIH application ID:** 10527799
- **Project number:** 2R01EY016178-16
- **Recipient organization:** UNIVERSITY OF ROCHESTER
- **Principal Investigator:** GREGORY C DEANGELIS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $485,369
- **Award type:** 2
- **Project period:** 2005-08-01 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10527799

## Citation

> US National Institutes of Health, RePORTER application 10527799, Neural mechanisms of optic flow processing for visually-guided control of steering (2R01EY016178-16). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10527799. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*