# Mechanism, connectivity, and outcome prediction of anxiety intervention from MRI-derived models in tDCS augmented cognitive training

> **NIH NIH F31** · UNIVERSITY OF FLORIDA · 2024 · $43,902

## Abstract

Project Summary / Abstract
Alzheimer’s disease (AD) is the most common form of dementia. The rate of dementia increases almost
exponentially with age – thus, the prevalence of AD has rapidly grown with the global life expectancy. Dementia
is detrimental to an individual’s standard of life, economic status, and psychological condition. Studies have
shown that certain neuropsychiatric disorders can promote the progression of mild cognitive impairment (MCI)
to AD. These disorders include anxiety, depression, and apathy. Depression and apathy have been studied in
this population; however, anxiety has largely been neglected. Understanding the mechanism, brain connectivity,
and response heterogeneity involved in anxiety interventions is pivotal in developing individualized interventions
for anxiety-paired MCI or AD.
This proposal broadly aims to understand the mechanism of anxiety interventions in an older adult population.
The objective of this work is to compare the neural changes that occur in individuals who respond and do not
respond to the non-invasive intervention. This work focuses on transcranial direct current stimulation (tDCS) for
anxiety intervention. Prior works have shown that tDCS shows promise to treat anxiety when paired with cognitive
training. However, a greater understanding of its mechanisms is required to develop a consistent pipeline for this
intervention. Functional magnetic resonance imaging (fMRI) will be used to identify the regions of interest (ROIs)
that are responsible for neurophysiological changes in tDCS-paired cognitive training for anxiety intervention
(Aim 1). We focus on specific brain regions (DLPFC, DMPFC, VLPFC) that have been shown to lead to response
in previous anxiety and dementia studies. Our hypothesis is that these activity in these regions will be positively
correlated to changes in neural function compared to sham. The neuroimaging results will highlight the specific
functional connectivity networks (left or right DLPFC, ACC) in fMRI that are associated with response to cognitive
training and tDCS intervention (Aim 2). Our analysis target specific functional connectivity networks that are
backed by anxiety research. These results will provide insight into the best intervention strategies to yield positive
results to anxiety interventions. All together, these aims will provide crucial insight into anxiety pathways and the
ideal steps for targeted anxiety interventions to prevent AD and related dementia.
This training proposal will provide the applicant with comprehensive training in effective teaching and mentoring
techniques. She will foster her ability to collaborate seamlessly within interdisciplinary teams and hone the skills
necessary for disseminating research findings to both scientific and clinical audiences. The applicant will gain
experience in designing and performing experiments that combine neural and cognitive outcome measures.
These experiences will further exposure her to advanced machine...

## Key facts

- **NIH application ID:** 10997645
- **Project number:** 1F31AG087647-01A1
- **Recipient organization:** UNIVERSITY OF FLORIDA
- **Principal Investigator:** Skylar E Stolte
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $43,902
- **Award type:** 1
- **Project period:** 2024-08-16 → 2025-08-15

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10997645

## Citation

> US National Institutes of Health, RePORTER application 10997645, Mechanism, connectivity, and outcome prediction of anxiety intervention from MRI-derived models in tDCS augmented cognitive training (1F31AG087647-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10997645. Licensed CC0.

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