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Updated: Sep 13, 2025

Examining the Characteristics of Episodic Memory using Event-related Potentials in Patients with Alzheimer's Disease
Published on: August 30, 2011
A prospective observational study of lucid episodes in advanced dementia
Andrea Gilmore-Bykovskyi1, Haley Kottler1,2, Amy Cochran2,3
1BerbeeWalsh Department of Emergency Medicine, University of Wisconsin-Madison School of Medicine & Public Health, Madison, Wisconsin, United States.
Background And Objectives:
Recent studies have provided new insights into lucid episodes (LEs) in people living with advanced dementia, but direct observational data documenting LEs are lacking. This prospective observational aimed to detect, characterize, and validate potential LEs.
Research Design And Methods:
Data from longitudinal audiovisual observations of participants living with advanced dementia (N = 20) were coded to generate measures of verbal output/expressions and nonverbal communicative actions (e.g., coherence, eye gaze). Potential LEs underwent a structured multi-informant review for validation. We applied generalized estimating equations to compare features of validated LEs to a random 20% sample of participant data used to estimate baseline functioning. Data were fit to a homogeneous Poisson point process to estimate the number of observations needed to accurately estimate the prevalence of LEs.
Results:
Across 539 observations, nine validated LEs were evidenced by three participants (range 2-4). Shared significant differences across LEs included an increased rate of meaningful vocalizations, although heterogeneity in features of LE was observed.
Discussion And Implications:
These findings represent the first prospectively documented and directly observed cases of LEs in advanced dementia. Features of LEs vary across individuals, but marked recovery of verbal communication abilities was a defining feature across all events. Lucid episodes occur infrequently, but these findings suggest that they may not be as rare as initially hypothesized. Larger samples and more diverse cohorts are needed to inform robust estimates of incidence and prevalence. Measurement advances to detect and characterize these events are critical to elucidating the underlying mechanisms driving these events and advancing supportive interventions.
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