Back

Language Abnormalities in Alzheimer's Disease Arise from Reduced Informativeness: A Cross-Linguistic Study in English and Persian

Bayat, S.; Sanati, M.; Mohammad Panahi, M.; Khodadadi, A.; Ghassimi, M.; Rezaee, S.; Besharat, S.; Mahboubi, Z.; Almasi-Dooghaee, M.; Sanei Taheri, M.; Dickerson, B. C.; Rezaii, N.

2024-03-22 neurology
10.1101/2024.03.19.24304407 medRxiv
Show abstract

INTRODUCTIONThis research investigates the psycholinguistic origins of language impairments in Alzheimers Disease (AD), questioning if these impairments result from language-specific structural disruptions or from a universal deficit in generating meaningful content. METHODSCross-linguistic analysis was conducted on language samples from 184 English and 52 Persian speakers, comprising both AD patients and healthy controls, to extract various language features. Furthermore, we introduced a machine learning-based metric, Language Informativeness Index (LII), to quantify informativeness. RESULTSIndicators of AD in English were found to be highly predictive of AD in Persian, with a 92.3% classification accuracy. Additionally, we found robust correlations between the typical linguistic abnormalities of AD and language emptiness (low LII) across both languages. DISCUSSIONFindings suggest AD linguistics impairments are attributed to a core universal difficulty in generating informative messages. Our approach underscores the importance of incorporating biocultural diversity into research, fostering the development of inclusive diagnostic tools.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.