# Representation and utilization of sensory uncertainty in the primate visual system

> **NIH NIH K99** · UNIVERSITY OF TEXAS AT AUSTIN · 2021 · $118,471

## Abstract

Project Summary
Representation and utilization of sensory uncertainty in the primate visual system
Accurate perception is vital for survival, but available sensory information can often be
impoverished. Observers act with seeming knowledge of their own uncertainty when making
perceptual decisions as well as reflecting on the accuracy of those decisions. This implies that
neural circuits which process sensory information also represent the uncertainty of this
information. How does this work? This proposal seeks to answer this question and investigate its
implications for perception and behavior. By combining theoretical neuroscience,
electrophysiological recordings, and perceptual experiments, this proposal will integrate results
from human and nonhuman primates to combine the characterization of sensory uncertainty and
its neuronal basis. This proposal comprises three specific research and training aims. First, we
will leverage theory and physiology to develop and test a novel computational theory of how
sensory neurons encode stimulus uncertainty (Aim 1). We propose a view that stimulus features
are encoded by the response mean of visual neurons, but stimulus uncertainty is encoded by
variance in the response gain. We will conduct electrophysiological recordings in the early visual
cortex while presenting stimuli with varying levels of uncertainty to further develop and test this
theory. This aim will provide strong training in computational neuroscience and the design of
experiments with a theory-driven approach. Second, we will identify how downstream circuits
decode stimulus uncertainty for perception (Aim 2), by recording neurons from animals trained to
judge the perceptual reliability of noisy sensory stimuli. Achieving this aim will require recording
from large neuronal populations across multiple areas simultaneously, so will provide training in
cutting-edge, large-scale electrophysiological techniques. Finally, we will connect the insights
gleaned from neurophysiological experiments in nonhuman primates to human behavior through
a novel approach to eliciting perceptual confidence (Aim 3). This approach will involve training in
and application of concepts from value-based decision-making to rigorously isolate confidence
behavior from the potential influence of reward preferences, such as risk attitude. These
experiments will be vital as a potential foundation for exploring the possible disruption of
uncertainty encoding in neuropsychiatric disorders. Overall, results from this proposal will help to
reveal the role of sensory circuits in representing and utilizing uncertainty to guide visual
perception.

## Key facts

- **NIH application ID:** 10099617
- **Project number:** 1K99EY032102-01
- **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN
- **Principal Investigator:** Corey M Ziemba
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $118,471
- **Award type:** 1
- **Project period:** 2021-03-01 → 2023-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10099617

## Citation

> US National Institutes of Health, RePORTER application 10099617, Representation and utilization of sensory uncertainty in the primate visual system (1K99EY032102-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10099617. Licensed CC0.

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