Postdoctoral Fellowship: SPRF: Idiomatic Language as a Diagnostic Marker in Alzheimer’s Dementia

Conger, Kathryn Summerville, Gainesville FL

Investigators

Abstract

Under the sponsorship of Dr. Stefanie Wulff at the University of Florida, this postdoctoral fellowship award supports an early career scientist establishing biomarker-based diagnostic tools that can detect early signs of Alzheimer's Disease (AD)-related cognitive impairment and progression. This project addresses an urgent need for more sensitive, accurate, and less costly ways to detect AD. One potential marker is the degree to which the comprehension of idioms, common formulaic phrases with a meaning that is not the sum of the parts (e.g. have in mind, fresh eyes, big picture), can be used to detect and monitor AD. Current physiological methods, such as imaging and cerebrospinal fluid testing, are costly, invasive, and may detect disease only after significant progression. Linguistic biomarkers offer an increasingly popular alternative as nearly all patients experience early semantic deficits. However, current linguistic applications are limited in their scope. Idiomatic language offers a deeper, more nuanced window into cognitive functioning as they place unique demands on executive functions. This research investigates changes in idiom understanding using a series of behavioral studies. This project establishes a theoretical and empirical foundation for future development of linguistically informed diagnostics, helping to translate behavioral science to clinical applications. To better understand how idiom comprehension reflects underlying cognitive changes in Alzheimer's Disease (AD), this project focuses on certain properties of idioms that influence how these phrases are processed. Idioms exist on a continuum, with certain phrases placing more demands on executive functions such as working memory, attention, and inhibition, while other subclasses require far fewer cognitive resources. These cognitive demands suggest that idioms can serve as varied and nuanced indicators of cognitive changes associated with AD. The proposed research seeks to establish relationships between idiom recognition and idiom biomarkers, determining the viability of idioms as more fine-grained detectors of AD. Grounded in theories from psycholinguistics and cognitive science, the research uses a series of experiments to measure judgments of idiomaticity and related properties across different stages of AD. Responses from individuals with early- and mid-stage Alzheimer's will be compared to a younger baseline population and a healthy older adult population using statistical modeling and predictive analysis to determine whether certain properties serve as early indicators of disease progression, laying the groundwork for future AI-based diagnostic tools based on everyday language. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.