# Circuit mechanisms for encoding naturalistic motion in the mammalian retina

> **NIH NIH R01** · UNIVERSITY OF CHICAGO · 2020 · $649,641

## Abstract

Abstract
Motion detection, a fundamental computation of the visual system, begins in the retina. In the
mammalian retina, the direction of moving objects is computed by the direction-selective circuit.
The retinal output of this circuit is provided by direction-selective ganglion cells (DSGCs). These
cells are strongly activated by motion in their preferred direction, but are suppressed by motion in
the opposite, or “null”, direction. They report the direction of motion to higher brain centers for
further visual processing, and they contribute to the control of eye movements and conscious
vision. Besides their direction selectivity, DSGC responses are prominently influenced by the
context of visual environments. These context-dependent properties are central to the motion
encoding by DSGCs in the natural environment. This proposal aims to address two important
context-dependent circuit functions pertinent to naturalistic stimuli. The first one is noise
resilience. Motion in natural scenes is often accompanied by the presence of other visual features
or “noise”. Aim 1 will determine circuit mechanisms that preserve direction selectivity in the
presence of background noise. The second function is the encoding of motion contrast. Due to
constant body and eye movements, visual inputs on the retina are composites of global image
shifts and relative motion between moving objects and their backgrounds. DSGC responses are
not only direction-selective, but also sensitive to relative motion compared to global motion. Aim
2 will determine the circuit motifs that confer DSGCs sensitivity to motion contrast. In Aim 3, we
will link the algorithmic functions of experimentally defined circuit motifs to the encoding
performance of DSGCs to naturalistic motion stimuli. Our proposed work combining functional,
connectomic, computational and theoretical approaches is expected to produce a multi-layered
circuit model that dynamically engages distinct circuit components for context-dependent
processing of naturalistic motion, a dramatic departure from the current static circuit model of
retinal feature selectivity. Since the connectivity patterns in the retina consist of canonical circuit
motifs that recur across brain regions and animal species, our study will provide insights into the
general principles of neural computation by the algorithmic functions of elementary circuit motifs.

## Key facts

- **NIH application ID:** 9983841
- **Project number:** 5R01NS109990-03
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Wei Wei
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $649,641
- **Award type:** 5
- **Project period:** 2018-09-30 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9983841

## Citation

> US National Institutes of Health, RePORTER application 9983841, Circuit mechanisms for encoding naturalistic motion in the mammalian retina (5R01NS109990-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9983841. Licensed CC0.

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