# Linking Neural Population Activity and Visual Perception

> **NIH NIH R01** · UNIVERSITY OF TEXAS AT AUSTIN · 2024 · $388,760

## Abstract

Project Summary
The overarching goal of the current proposal is to uncover the neural mechanisms that underlie figure-ground
segregation, an important component of natural scene interpretation, focusing on the role of the primary visual
cortex (V1) and its dynamic interactions with higher visual cortical areas. Specifically, we will measure how V1
responds to a wide range of backgrounds, including artificial and naturalistic textures, with and without
occluding targets, and develop computational encoding models that would allow one to predict V1 population
responses at multiple biologically-relevant spatial scales to arbitrary figures and backgrounds (Aim 1). In Aim 2
we will study the role of V1 in figure-ground discrimination by measuring and perturbing V1 population
responses while animals detect a camouflaged target that occludes a background of the same texture family.
These experiments will be used to distinguish between different candidate decoding models that describe how
single-trial V1 population responses lead to behavior in the task. An important goal would be to test whether V1
plays an active role in the segmentation computation. The alternative is that V1 provides the feedforward input
to a segmentation computation that occurs downstream, and receives top-down figure-ground signals only
after the segmentation had been completed. Overall, the proposed experiments will lead to a deeper
understanding of the role of V1 in fundamental mid-level visual computations and will serve as an important
step toward a quantitative understanding of the representation of complex natural scenes by populations of
neurons in V1.

## Key facts

- **NIH application ID:** 10771982
- **Project number:** 5R01EY016454-18
- **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN
- **Principal Investigator:** EYAL J SEIDEMANN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $388,760
- **Award type:** 5
- **Project period:** 2005-05-01 → 2026-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10771982

## Citation

> US National Institutes of Health, RePORTER application 10771982, Linking Neural Population Activity and Visual Perception (5R01EY016454-18). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10771982. Licensed CC0.

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