The Language of Dementia: How Connectedness in Speech Reveals the Severity

Published on September 19, 2023

Imagine a group of friends sitting around a campfire, sharing stories, and passing a sentence from one person to another. They laugh, they interrupt each other, and their stories flow seamlessly. Now imagine another group where each person speaks in short, disconnected bursts. Their words hang in the air, unanchored, leaving sentences unfinished and thoughts disjointed. It turns out that this second group may hold a marker of dementia due to Alzheimer’s disease. A recent study explored the connectedness of spontaneous speech production as an indicator of dementia severity. The results revealed that individuals with higher educational attainment and better verbal fluency tended to have more cohesively connected speech, indicating better cognitive function. Using a computational tool called SpeechGraphs, researchers calculated the connectedness of speech during picture description tasks. The findings suggest that automated language processing approaches like graph structure analysis could offer a faster and more valid way to detect dementia symptoms in the future. Explore the research for yourself to learn more about this exciting potential breakthrough!

The study evaluated the connectedness of spontaneous speech production in individuals with dementia as a potential predictor of dementia severity. Data were derived from the baseline sample of 143 individuals with dementia in the English Pitt corpus. Dementia severity was assessed via the Mini Mental Status Exam, the Mattis Dementia Rating Scale, and the Blessed Dementia Scale. Language abilities were evaluated using verbal fluency and picture description tasks. Graph analysis was carried out for the picture description task using the computational tool SpeechGraphs to calculate connectedness. Results demonstrated that higher educational attainment, higher verbal fluency and strongly-connected spontaneous speech were associated with better cognitive function. Results suggest that automated language processing approaches, such as graph structure analysis, may provide a faster and ecologically valid method of detecting dementia symptoms.

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