# Functional networks underlying cognitive decline in aging and Alzheimer's disease

> **NIH NIH F31** · UNIVERSITY OF CALIFORNIA BERKELEY · 2022 · $42,901

## Abstract

Project Summary
Aging and Alzheimer’s disease (AD) are characterized by progressive cognitive decline, ranging from mild to
severe deficits in episodic memory and executive function. In addition, recent work has begun to identify
networks of functional connections across the brain whose activity subserve specific cognitive functions.
Network dysfunction is a feature of AD, but alterations in cognition-related networks may also be detectable in
normal aging. Positron emission tomography (PET) imaging of pathological amyloid-β (Aβ) and tau proteins
has revealed that their accumulation is related to cognitive decline in older adults. The mechanisms by which
these protein aggregates lead to impaired cognitive function are still not well understood, but recent work
suggests that Aβ and tau accumulation may alter the integrity of functional brain networks. This project will
investigate the impact of AD pathology on these networks and their role in age-related cognitive decline. Using
a novel network definition approach, behaviorally-specific functional networks will be defined in older adults
using both resting state and task fMRI data. Neuropsychological episodic memory and executive function
measures as well as memory performance in an fMRI task will be used as behavioral outcomes to define these
networks. In addition, AD pathology will be measured using the 11C-PiB (Aβ) and 18F-Flortaucipir (tau) PET
tracers. In Aim 1, whole-brain resting state functional connectivity will be used to define networks based on
episodic memory and executive function performance, and the overall strength of these networks will be
related to pathology and cognitive performance. In Aim 2, functional connectivity and behavioral data from a
memory encoding fMRI experiment will be used to define a task-based network, which will again be related to
pathology and cognition. Finally, in Aim 3, we will compare these networks in terms of their topography,
relationship with AD pathology, and ability to predict longitudinal cognitive decline. Overall, this study will
investigate changes in functional brain networks as a mechanism by which cognition declines, offering a
compelling new tool for researchers to predict cognitive change in aging and disease. Completion of this
project will provide training in (1) multimodal neuroimaging and processing, (2) novel biostatistical techniques
for neuroimaging data analysis, (3) the cognitive neuroscience of aging and AD, (4) scientific communication,
and (5) teaching and mentorship. The Helen Wills Neuroscience Institute at UC Berkeley provides an ideal
environment for this research, bringing together world-class experts in neuroimaging, biostatistics, and
cognitive neuroscience who will aid in the completion of this project. The sponsor Dr. William Jagust is uniquely
suited for overseeing this work, having built a career on applying multimodal neuroimaging techniques to better
understand the underlying mechanisms of aging and AD. The propos...

## Key facts

- **NIH application ID:** 10537411
- **Project number:** 1F31AG079595-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** Jacob Ziontz
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $42,901
- **Award type:** 1
- **Project period:** 2022-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10537411

## Citation

> US National Institutes of Health, RePORTER application 10537411, Functional networks underlying cognitive decline in aging and Alzheimer's disease (1F31AG079595-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10537411. Licensed CC0.

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