# Development of an Integrated System for Monitoring Home-Cage Behavior in Non-Human Primates

> **NIH NIH R01** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2020 · $521,954

## Abstract

7: Project Summary/Abstract
Marmosets are emerging as an important model species for neuroscience research, driven by the
development of new technologies such as CRISPR that allow targeted genetic modifications in
this species. These developments will allow primate research to take advantage of powerful
genetic tools that were previously restricted largely to rodents, including optogenetics, genetic
activity reporters, and targeted mutation of endogenous genes implicated in brain function and
human disease. Marmosets are well suited to this approach, being small and fast-breeding
compared to most primates. They are typically housed in family groups, and exhibit a variety of
social behaviors in captivity including complex vocal repertoires. Marmosets thus represent a
promising system for studying social behavior and other cognitive functions in a primate model,
and they also hold great promise for modeling brain disorders that affect cognitive functions that
are difficult to study in other species such as rodents. To take full advantage of these emerging
animal models, it is necessary to develop new methods for analyzing their behavior, including
naturalistic social interactions that are imperfectly captured by standardized behavioral tasks. We
therefore plan to develop a system for automated analysis of marmoset behaviors in the home
cage. The system will consist of an integrated array of sensors including video cameras, depth
sensors, and collar-mounted wearable microphones. The resulting multimodal data will be
synchronized and analyzed using methods from computer vision, speech processing, machine
learning, and multimodal data analysis. Specifically we will formulate the tracking analysis as a
probabilistic graphical model, which will allow video data to be integrated with audio
recordings, and with other modalities that could be explored in future, including inertial motion
sensors, physiological recordings and other contextual data. Based on this approach we will
develop methods to classify calls, identify individual callers, track the locations and identities of
each animal in three dimensions, and classify different actions, including interactions between
individuals. We envisage that our system will be useful for a wide range of studies in basic and
translational neuroscience, and in particular it will be useful for studying behavioral phenotypes
in genetic models of human psychiatric disorders, and for relating behavioral abnormalities to
their underlying genetic and neural causes.

## Key facts

- **NIH application ID:** 9901577
- **Project number:** 5R01MH111916-03
- **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Robert Desimone
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $521,954
- **Award type:** 5
- **Project period:** 2018-05-08 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9901577

## Citation

> US National Institutes of Health, RePORTER application 9901577, Development of an Integrated System for Monitoring Home-Cage Behavior in Non-Human Primates (5R01MH111916-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9901577. Licensed CC0.

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