Quantitatively modelling the phenomenology of Alzheimer's-type dementia using frame-theoretic semantics and psycholinguistic norms
James CarneyBackground
The phenomenology of Alzheimer's disease—the “what is it like?” of the condition—has previously been approached via either quantitative analyses of granular linguistic features or qualitative analyses of lived experience.
Objective
What is lacking is an empirically credible framework that captures high-level qualitative insight by way of cognitive models rather than surface linguistic features.
Methods
Frame semantics and a 1.19 million-token psycholinguistic word norm lookup were applied to two topic-matched corpora: the DementiaBank Pitt Cookie Theft recordings and a COVID-era diary corpus combining CoSoWELL controls with
Results
A combined classifier contributed information statistically independent of the Fraser set on both corpora. On Pitt, four variance-based features defined a variance-collapse signature, with imageability being most significant; the within-document standard deviation of imageability replicated on COVID. Twelve semantic-frame comparisons survived Holm correction; Kinship was under-used on both corpora, giving a second cross-corpus anchor alongside imageability. A four-feature minimal classifier drawing equally from both feature families achieved AUC 0.748 on Pitt and 0.781 on COVID.
Conclusions
Alzheimer's-type dementia is characterized not by a shift in the mean of any linguistic dimension but by a flattening of the phenomenological range across which a speaker moves when describing and experiencing the world. Because the diagnostic labels available in both corpora are coarse, the extent to which this flattening reflects a unitary phenomenology of Alzheimer's disease rather than heterogeneity within the diagnostic category remains to be established.