# Behavior Automation

> **NIH NIH U19** · PRINCETON UNIVERSITY · 2020 · $140,392

## Abstract

Project Summary: Core 3, Behavior Automation 
 
Working memory, the ability to temporarily hold multiple pieces of information in mind for 
manipulation, is central to virtually all cognitive abilities. This multi-component research project 
aims to comprehensively dissect the neural circuit mechanisms of this ability across multiple 
brain areas. The individual parts of the project cohere conceptually, in part, because they all 
involve rodents trained to perform a type of decision-making task that is based on the gradual 
accumulation of sensory evidence and thus relies on working memory. To produce enough 
subjects for these experiments, this Core will scale up an existing high-throughput rat training 
facility run by technicians and adapt it for mice. This expansion will quintuple the project’s 
capacity for rodent training. To do so, we will take advantage of the expertise of the project 
leader in developing and managing such a training facility for sophisticated cognitive tasks in 
an existing virtual reality infrastructure, software, and hardware. Once this facility is operational, 
the Core will manage it and troubleshoot problems as needed. It will develop new hardware 
and software components for training rigs to make technician interventions as reproducible and 
error-free as possible. Because the most crucial and time-consuming aspect of mouse virtual 
training is ensuring that the head-fixed animal is properly aligned to the ball and the projection 
system, the Core will develop an automated alignment system based on image registration and 
actuators to replace the current manual alignment. It will develop software tools and 
standardized technician procedures to ensure consistency in rodent training, prevent training 
errors, detect hardware failures, and monitor the health of the animals. This centralized facility 
will promote rigor and reproducibility by reducing variability in animal training across labs, 
increase the rate of data acquisition, and free personnel to focus on designing and carrying out 
creative experiments. In the long run, the entire neuroscience community will benefit from this 
effort, as the software and hardware tools and management protocols produced will be made 
freely available, along with their documentation. These tools will enable other researchers to 
introduce automated training for well-controlled cognitive tasks in their own laboratories, 
leading to improved efficiency, rigor, and reproducibility in behavioral research across the field 
of neuroscience.

## Key facts

- **NIH application ID:** 9983196
- **Project number:** 5U19NS104648-04
- **Recipient organization:** PRINCETON UNIVERSITY
- **Principal Investigator:** Carlos D Brody
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $140,392
- **Award type:** 5
- **Project period:** 2017-09-28 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9983196

## Citation

> US National Institutes of Health, RePORTER application 9983196, Behavior Automation (5U19NS104648-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9983196. Licensed CC0.

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