# Computational, anatomical, and molecular principles of system-wide visual encoding

> **NIH NIH F32** · STANFORD UNIVERSITY · 2024 · $76,756

## Abstract

Abstract
The computations performed by circuits in the visual system are numerous and varied, emerging from many
cell types with unique combinations of synaptic inputs, molecular composition, and physiological properties.
How are distinct computations distributed across neurons and circuits in the visual system, and how are
anatomical and molecular features differentially engaged to support them? Addressing these fundamental
questions requires a model with deep, cell-by-cell descriptions of gene expression and morphology. This
project will examine computation by assessing the varied representation of visual features across cell types in
the Drosophila medulla, the first site of major synaptic divergence and signal expansion in the fly visual
pathway. By extending established genetic tools, this study will record visual selectivity in most of the ~70
medulla cell types in a fraction of the time required for traditional approaches. This broad physiological
assessment will then be leveraged to explore how differences in wiring and gene expression relate to different
visual computations. First, a linear/non-linear sum-of-inputs model, weighted according to data from the fly
connectome, will describe the extent to which a neuron’s activity can be explained by its feedforward input.
Second, a large-scale regression of response features with cell type-specific transcriptome data will reveal how
genetic suites and individual molecules contribute to visual feature selectivity. And finally, manipulations of
modulatory circuit elements will uncover how feedback and laterally connected cell types contribute to visual
computation. Collectively, these experiments will describe how different forms of synaptic input and distinct
genetic programs are differentially recruited to build the computations necessary for proper visual processing.
The results of this study have the potential to qualitatively improve critical technologies related to the quality of
human life, including retinal prosthetics and machine vision.

## Key facts

- **NIH application ID:** 10845369
- **Project number:** 5F32EY035135-02
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Timothy A Currier
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $76,756
- **Award type:** 5
- **Project period:** 2023-05-03 → 2025-05-02

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10845369

## Citation

> US National Institutes of Health, RePORTER application 10845369, Computational, anatomical, and molecular principles of system-wide visual encoding (5F32EY035135-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10845369. Licensed CC0.

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