# A Toolkit for Analysis and Visualization of Preclinical Rodent Neuroimaging Experiments

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2023 · $612,523

## Abstract

Project Summary
Rodent models remain an important in preclinical studies of brain disease and disorders, as well as basic
neuroscience investigations. Rodent imaging data, acquired through techniques including MRI and microscopy,
play a critical role in many of these studies. While a great deal of effort has gone into the development of software
tools for analyzing MRI of the brain, much of this work has been focused largely on human data, and investigators
studying animal models of disease must often resort to adapting these tools for their research. In this project, we
will address this need by developing a dedicated suite of open source software tools for processing, analyzing,
and visualizing neuroimaging data acquired from rodent brains. These tools will operate on structural diffusion,
and functional MRI, as well as optical microscopy of optically cleared serially sectioned tissue samples. These
tools will build upon our decades of experience developing software for analyzing human and mouse imaging
data, our experience in developing multimodal atlases of the mouse brain, and our active efforts in community
engagement and dissemination while applying these resources in neuroscientific studies. Where suitable, we
will make use of deep learning methods to produce powerful segmentation and registration networks trained on
manually annotated and delineated data. We will also develop easy-to-use interfaces that will facilitate data
processing and provide advanced visualization capabilities of datasets with sizes on the order of one terapixel.
The project has five specific aims. Aim 1 will develop MRI processing tools, which will include intrasubject co-
registration of MRI modalities, extraction of brain tissue from whole head scans, tissue classification, and
processing of diffusion and functional MRI data. Aim 2 will develop tools for processing microscopy of cleared
and sectioned tissue, with the major goal of aligning these data to a reference atlas generated from either optical
microscopy or MRI. These tools will perform cell counting in automatically segmented regions; axon following;
dendritic arborization; and dendritic spine counting. In Aim 3, we will develop a statistical analysis toolbox, which
will perform statistical inference for neuroimaging measures from microscopy and MRI data analyzed using
methods from Aims 1 and 2. In Aim 4, we will integrate the components from Aims 1-3 into an informatics platform
that will provide command line tools for easy scripting, interoperability with related imaging tools, and a graphical
interface for visualizing data across different scales. In Aim 5, we will perform evaluation of our software tools
using two studies: imaging an experimental autoimmune encephalomyelitis (EAE) mouse model of multiple
sclerosis; and imaging a mouse model of normative aging. We will also work with a network of small animal
imaging experts external to the project, who will use and evaluate the software. These driving...

## Key facts

- **NIH application ID:** 10584587
- **Project number:** 5R01NS121761-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Allan James MacKenzie-Graham
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $612,523
- **Award type:** 5
- **Project period:** 2022-04-01 → 2027-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10584587

## Citation

> US National Institutes of Health, RePORTER application 10584587, A Toolkit for Analysis and Visualization of Preclinical Rodent Neuroimaging Experiments (5R01NS121761-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10584587. Licensed CC0.

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