# Neural coding of natural stimuli in freely moving macaque

> **NIH NIH R34** · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · 2022 · $229,442

## Abstract

Despite the fact that visual perception represents such a fundamental aspect of our everyday life, our knowledge
of the underlying neural coding of natural stimuli is woefully lacking. One major limitation preventing our
understanding of the neural underpinnings of natural vision is the lack of viable methodologies for recording and
synchronizing eye movements and incoming visual stimuli from freely-moving monkeys during unrestrained
exploratory behavior. Indeed, examining the neural bases of visual perception has been traditionally performed
by studying the brain of nonhuman primates in a laboratory environment in which the head and body are
restrained while synthetic stimuli are presented on a computer monitor. However, it has become increasingly
clear that studying the brain in spatially confined, artificial laboratory rigs poses severe limits on our capacity to
understand the function of brain circuits. To overcome these limitations, we propose a novel approach by
designing an integrated wireless eye tracking system to precisely record naturally-occurring eye movements and
retinotopic visual inputs throughout unstructured, freely-moving behavior in conjunction with massive, wireless
electrical recordings of population activity across four cortical areas. Our novel system will be used to study the
visual coding and brain state-dependence of cortical dynamics during natural visual exploration by recording
population activity in multiple visual, temporal, and frontal cortical areas while nonhuman primates are interacting
with their environment. We will focus on the sparseness of the population response, the real-time encoding of
natural scenes, and spatial position dependency of stimulus coding. We hypothesize that the sparse coding of
natural stimuli during free viewing improves the accuracy with which neural populations encode stimuli across
the visual cortical hierarchy. Our proposed research will constitute a paradigm shift by moving visual
neuroscience - from simply observing animal behavior and recording the responses of single cells - to a
quantitative understanding of the distributed neuronal network encoding during task-free behavior in freely
moving nonhuman primates interacting with their physical environment. We anticipate that the large quantity of
neural data recorded using our approach will be of great interest to clinicians and computational neuroscientists
studying general properties of normal and dysfunctional neural networks, possibly leading to medical insights
into cortical visual impairments and innovations in cortical prosthetics for restoring natural visual functions.

## Key facts

- **NIH application ID:** 10524592
- **Project number:** 1R34NS128894-01
- **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
- **Principal Investigator:** VALENTIN DRAGOI
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $229,442
- **Award type:** 1
- **Project period:** 2022-07-15 → 2023-09-15

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10524592

## Citation

> US National Institutes of Health, RePORTER application 10524592, Neural coding of natural stimuli in freely moving macaque (1R34NS128894-01). Retrieved via AI Analytics 2026-06-23 from https://api.ai-analytics.org/grant/nih/10524592. Licensed CC0.

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