# Precision Mapping of Functional Networks in Healthy and Pathological Aging

> **NIH NIH F99** · NORTHWESTERN UNIVERSITY · 2024 · $44,439

## Abstract

Project Summary
Functional Magnetic Resonance Imaging (fMRI) has become a powerful tool for studying the underlying
functional architecture of brain networks by tracking temporal correlations in the activity of different brain regions;
a technique called resting-state functional connectivity (rs-FC). Recently, individualized methods of rs-FC have
revealed reliable differences in functional organization between individuals and group averages that have been
implicated with differences in behavior. These precision fMRI methods involve collecting extended amounts of
rs-FC data across multiple sessions for each subject and the use of advanced denoising techniques to improve
the quality of the data. Individual-specific networks have not been examined in older adults yet, even though
group-average studies suggest that brain networks change systematically over the course of the lifespan and as
a function of disease, both in cortical and cerebellar regions. I propose the use of a dataset of highly sampled
older adults, ages 60-75 (N = 38), and younger adults, ages 18-30 (N = 38), to create individual-specific
parcellations and network representations using high-quality anatomical and rs-FC data. In Aim 1, I will examine
whether the properties of individualized networks in older adults differ compared to young adults. In Aim 2, I will
examine whether the networks affected in Alzheimer’s Disease (AD) differ from those affected in healthy aging,
particularly in the cerebellum. Preliminary data suggests that, with sufficient high-quality data, cortical networks
in young adults are stable across days (r > 0.85), supporting their endophenotypic nature and potential for use
as biomarkers. This study will be the first to use individualized measures in older adults to provide a better
understanding of neurodevelopmental changes to rs-FC that may be relevant to behavior. Individualized network
topology has previously been found to be predictive of behavioral and cognitive measurements, suggesting that
it may be a promising avenue to search for biomarkers of cognitive decline. My pre-doctoral work (Aim 1) will set
the benchmark for using precision fMRI with an older population to study the relationship between brain network
variability and cognitive decline. My post-doctoral goal (Aim 2) is to apply these methodologies to the study of
AD-related changes to the functional architecture of the brain and how these changes drive hallmark cognitive
symptoms. This project will also provide ample opportunities for additional scientific and professional training.
My training goals will focus on gaining theoretical and practical knowledge of defining individualized functional
networks and brain parcellations, ensuring the quality of anatomical images using FreeSurfer, and applying
special considerations to obtain reliable signal from cerebellar data. Professional development goals will center
on mentoring practices and science communication. These skills will be key to my fut...

## Key facts

- **NIH application ID:** 10973479
- **Project number:** 1F99AG088569-01
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** Diana Carolina Perez Rivera
- **Activity code:** F99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $44,439
- **Award type:** 1
- **Project period:** 2024-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10973479

## Citation

> US National Institutes of Health, RePORTER application 10973479, Precision Mapping of Functional Networks in Healthy and Pathological Aging (1F99AG088569-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10973479. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*