# Elucidating novel features of visual processing and physiological connectivity from retina to primary visual cortex

> **NIH NIH R01** · DUKE UNIVERSITY · 2021 · $487,568

## Abstract

Project Summary
The use of stimuli with increasingly naturalistic properties has become critical to advance our understanding of
vision. Many studies demonstrate that simple artificial stimuli (e.g. sinusoidal gratings and white noise) fail to
engage nonlinearities that profoundly alter responses in the retina, lateral geniculate nucleus (LGN), and primary
visual cortex (V1). A recent and striking example comes from the use of naturalistic ‘flow’ stimuli, which engage
robust responses in V1 that are not predicted from responses to gratings. This gap in understanding motivates
the development of a stimulus ensemble and analysis framework that produces a quantitative understanding of
visual processing to increasingly naturalistic stimuli and the nonlinearities that they engage. Our objective is to
understand how flow stimuli are processed from retina through visual cortex. To meet this goal, we will make
neural population recordings in retina (Aims 1 & 3), LGN (Aims 1 & 3) and V1 (Aim 3) using matched experimental
conditions and a unified theoretical/modeling framework to map the transformations that occur across these
stages of visual processing. Our central hypothesis is that V1 transforms a discrete and heavily light-level-de-
pendent retinal representation of natural stimuli into a continuous (uniform) representation that is relatively in-
variant to changes in the mean luminance. This invariance places a strong constraint on the class of nonlineari-
ties that transform retinal responses to those observed in LGN and V1. We test this hypothesis in three aims: (1)
determine early visual processing (retina & LGN) of naturalistic flow stimuli; (2) develop an encoding manifold to
capture the population activity at each processing stage and transforms from one stage to the next; (3) test the
ability of the manifold description to predict the impact of light adaptation on processing flow stimuli from retina
to V1. Aim 1 will yield a matched experimental dataset to an interesting and novel class of ecologically-relevant
stimuli. Aim 2 will yield a quantitative framework by which to understand the transformations that occur between
retina, LGN, and V1. Aim 3 will provide a platform for globally perturbing the output of the retina by switching
from photopic to mesopic and scotopic conditions, and thereby compare predictions of our model to measured
changes in LGN and V1 activity. The primary significance of this research is that it will provide a computationally
and experimentally unified framework for understanding the transformations that occur in the processing of stim-
uli across multiple stages of visual processing. The major innovations are (1) presenting visual stimuli for retinal
recordings that are matched to eye movements and pupil dynamics in alert animals; (2) creating a novel analysis
framework that captures the responses of neurons at all three levels and the inter-level transformations to in-
creasingly complex stimuli; (3) utilizing light...

## Key facts

- **NIH application ID:** 10229447
- **Project number:** 5R01EY031059-02
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Gregory Darin Field
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $487,568
- **Award type:** 5
- **Project period:** 2020-09-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10229447

## Citation

> US National Institutes of Health, RePORTER application 10229447, Elucidating novel features of visual processing and physiological connectivity from retina to primary visual cortex (5R01EY031059-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10229447. Licensed CC0.

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