# Characterizing vigilance in fMRI data and its relation to age-related cognitive impairment.

> **NIH NIH F99** · VANDERBILT UNIVERSITY · 2022 · $48,252

## Abstract

PROJECT SUMMARY/ABSTRACT
Magnetic resonance imaging (MRI) is a powerful non-invasive tool for imaging brain activity that allows for
investigating the dynamically changing activity patterns and structure that give rise to human brain function and
dysfunction. Functional MRI (fMRI) signal variations linked with vigilance states, and the subcortical-cortical
networks that underlie these fluctuations in vigilance, are being increasingly recognized as fMRI signals of
interest both for neuroscience and in studying disease. However, vigilance has been largely ignored in routine
fMRI studies, despite the fact that subjects tend to fall asleep in the scanner and certain patient populations may
be susceptible to fatigue or daytime sleepiness. More precisely characterizing the role of vigilance in disease,
and its effects in fMRI data, could be key for developing imaging biomarkers as well as improving treatment. My
doctoral work thus far, (Aim 1.1) developed a method for extracting a vigilance metric, based on fMRI data alone,
using a vigilance-related activity pattern built from correlations between simultaneous fMRI-EEG in healthy young
adults. For my F99 phase, I will (Aim 1.2) investigate whether a state-of-the-art image acquisition/processing
method, multi-echo independent component analysis (ME-ICA), improves the correspondence between fMRI
signal and EEG signal, and whether using the ME-ICA approach improves sensitivity in detecting subcortical
arousal networks. Finally, I will (in Aim 1.3) attempt to distinguish between mild cognitive impaired (MCI) patients
and healthy aging controls by leveraging fMRI-based vigilance as a biomarker. By comparing vigilance
fluctuations and functional connectivity differences in vigilance network regions of interest, we seek to
understand the role of vigilance in early-stage Alzheimer’s disease.
 The proposed project will help the candidate, Sarah Goodale; achieve her career goal of becoming an
independent investigator at the forefront of aging neuroimaging at a research-focused institution. This project
provides cutting-edge research training in EEG and fMRI analysis and advanced statistical methods. Further,
the proposed studies will provide professional and technical training to prepare the candidate to successfully
transition the postdoctoral (K00) phase. The postdoctoral laboratory will extend Sarah’s training to incorporate
structural imaging to characterize the impact of structural degeneration on functional networks with respect to
age-related cognitive decline. Vanderbilt University is an ideal environment to achieve these goals as it (1)
encourages collaboration, (2) has state-of-the-art technical resources to perform cutting-edge research, and (3)
contains renowned faculty that encourage training, mentorship, and the development of aspiring researchers.
The complete plan proposed for both the F99 and K00 phases is designed to develop an independent
neuroimaging scientist prepared for a successful postdo...

## Key facts

- **NIH application ID:** 10562847
- **Project number:** 1F99AG079810-01
- **Recipient organization:** VANDERBILT UNIVERSITY
- **Principal Investigator:** Sarah E Goodale
- **Activity code:** F99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $48,252
- **Award type:** 1
- **Project period:** 2022-12-01 → 2024-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10562847

## Citation

> US National Institutes of Health, RePORTER application 10562847, Characterizing vigilance in fMRI data and its relation to age-related cognitive impairment. (1F99AG079810-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10562847. Licensed CC0.

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