# Development and characterization of EEG signature of cognitive fluctuations in Lewy body dementia

> **NIH NIH R21** · VIRGINIA COMMONWEALTH UNIVERSITY · 2022 · $426,938

## Abstract

PROJECT SUMMARY / ABSTRACT
Lewy body dementia (LBD) is the second most common cause of dementia and is associated with unrelenting
cognitive decline, profound caregiver burden, and higher healthcare costs compared to Alzheimer disease
(AD). Despite its prevalence and worse prognosis, patients with LBD suffer from misdiagnosis and delayed
diagnosis, which may result in use of medications with increased morbidity and delays in appropriate clinical
care. Thus, accurate and early diagnosis of LBD is a serious unmet need. To support earlier and accurate
diagnosis, we seek to develop a physiological biomarker of cognitive fluctuations, a characteristic feature of
LBD that differentiates it from other dementias. This goal addresses the NIH Alzheimer’s Disease-Related
Dementias (ADRD) Summit recommendation to develop biomarkers in LBD. Cognitive fluctuations (CF) are
defined as spontaneous periods of impaired attention and reduced arousal that correspond to variability in
measures of sustained attention. CF are a core clinical feature of cognitive impairment in LBD and are
associated with greater impairment in activities of daily living and worse quality of life. Despite their prevalence,
CF are challenging to diagnose clinically, because commonly used formal assessments require administration
by an experienced clinician and the presence of a reliable informant. An accurate and widely available
biomarker of CF would greatly advance the ability to diagnose CF and thus LBD. EEG differences in LBD are
well-documented, but there is currently insufficient evidence to consider specific EEG findings as an indicative
biomarker of LBD. A few studies found that both lower dominant frequency and higher dominant frequency
variability on EEG correlated with CF. These EEG correlates of CF are thought to reflect dysregulation of
cortical synchronization, but perturbations in dominant frequency have not been temporally linked to short-term
clinical fluctuations in sustained attention. Demonstrating that EEG correlates of CF in LBD correspond to
differences in sustained attention over short timescales will provide evidence of the clinical relevance of EEG
as a biomarker. We hypothesize that reduced dominant frequency and higher dominant frequency variability on
EEG can accurately identify CF in LBD patients and that dominant frequency on EEG is temporally associated
with performance on a test of sustained attention. In Aim 1 we will elucidate the EEG signature underlying CF
in LBD by comparing the EEG features of LBD with CF to LBD, AD, Parkinson disease and healthy controls
without CF. In Aim 2 we will correlate EEG features of CF in LBD with impairment in sustained attention. We
anticipate that this proposal will result in a clinically relevant physiological biomarker of CF in LBD that can then
be validated in a large-scale multi-center study. The fact that EEG is non-invasive, relatively inexpensive, and
widely available will support its adoption as a biomarker for CF...

## Key facts

- **NIH application ID:** 10447380
- **Project number:** 1R21AG077469-01
- **Recipient organization:** VIRGINIA COMMONWEALTH UNIVERSITY
- **Principal Investigator:** Matthew James Barrett
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $426,938
- **Award type:** 1
- **Project period:** 2022-06-15 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10447380

## Citation

> US National Institutes of Health, RePORTER application 10447380, Development and characterization of EEG signature of cognitive fluctuations in Lewy body dementia (1R21AG077469-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10447380. Licensed CC0.

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