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.
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.
Similar papers in this journal
- High frequency post-pause word choices and task-dependent speech behavior characterize connected speech in individuals with mild cognitive impairment 95%
- Sex Differences in Cognitive Performance in Alzheimer's Disease: Insights from the ADAS-Cog-13 92%
- Towards the development of a management protocol for Subjective Cognitive Decline: insights from a cross-sectional and longitudinal analyses of multimodal clinical data 92%
Similar papers in this journal
- Evaluation of a speech-based AI system for early detection of Alzheimer’s disease remotely via smartphones 95%
- Self-reported word-finding complaints are associated with cerebrospinal fluid beta-amyloid and atrophy in cognitively normal older adults 94%
- Clinical Validation and Machine Learning Optimization of MyCog: A Self-Administered Cognitive Screener for Primary Care Settings 93%
Similar papers in this journal
- Detection of dementia on raw voice recordings using deep learning: A Framingham Heart Study 94%
- Disentangling phonology from phonological short-term memory in Alzheimer’s disease phenotypes 93%
- Development and validation of a harmonized memory score for multicenter Alzheimer's disease and related dementia research 93%
Similar papers in this journal
- Impaired semantic control in the logopenic variant of primary progressive aphasia 95%
- Verbal fluency tests assess global cognitive status but have limited diagnostic differentiation: Evidence from a large-scale examination of six neurodegenerative diseases 95%
- Lexical Markers of Disordered Speech in Primary Progressive Aphasia and ‘Parkinson-plus’ Disorders 95%
"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.