# High-resolution 3D tracking of social behaviors for deep phenotypic analysis

> **NIH NIH R34** · DUKE UNIVERSITY · 2024 · $378,727

## Abstract

Project Summary
The aim of this proposal is to plan for and deliver a proof-of-concept solution for an innovative
and easy-to-use experimental platform for measuring and quantifying social behaviors in animal
models. Efforts during this initial grant period will be restricted to rats and mice, experimental
animals with rich social behaviors, but we hope in future iterations of this program to expand also
to other model organisms, including birds and monkeys. To capture kinematic details of whole-
body movement during social behaviors requires novel solutions for dealing with the inevitable
occlusions that results from social interactions. To overcome the limitations of current approaches
we will build and validate a novel deep neural network that learns to combine images across
multiple synchronized cameras and infer the 3D physical coordinates of multiple animals.
Preliminary studies have been very positive and suggest large improvements over current
methods both when it comes to the range of social behaviors that can be tracked and the precision
with which they can be measured. Importantly, all new technology will be readily shared with the
scientific community, thereby leveraging from this single grant the potential for numerous
investigators to dramatically improve the efficiency of their research programs requiring rigorous
quantitative descriptions of animal behavior.

## Key facts

- **NIH application ID:** 10786685
- **Project number:** 1R34DA059506-01
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Timothy William Dunn
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $378,727
- **Award type:** 1
- **Project period:** 2024-09-15 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10786685

## Citation

> US National Institutes of Health, RePORTER application 10786685, High-resolution 3D tracking of social behaviors for deep phenotypic analysis (1R34DA059506-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10786685. Licensed CC0.

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