Investigating Acoustic and Psycholinguistic Predictors of Cognitive Impairment in Older Adults: Modeling Study

Overview

Journal JMIR Aging

Specialty Geriatrics

Date 2024 Sep 16

PMID 39283659

Authors

Varsha D Badal

Jenna M Reinen

Elizabeth W Twamley

Ellen E Lee

Robert P Fellows

Erhan Bilal

Colin A Depp

Affiliations

Soon will be listed here.

Abstract

Background: About one-third of older adults aged 65 years and older often have mild cognitive impairment or dementia. Acoustic and psycho-linguistic features derived from conversation may be of great diagnostic value because speech involves verbal memory and cognitive and neuromuscular processes. The relative decline in these processes, however, may not be linear and remains understudied.

Objective: This study aims to establish associations between cognitive abilities and various attributes of speech and natural language production. To date, the majority of research has been cross-sectional, relying mostly on data from structured interactions and restricted to textual versus acoustic analyses.

Methods: In a sample of 71 older (mean age 83.3, SD 7.0 years) community-dwelling adults who completed qualitative interviews and cognitive testing, we investigated the performance of both acoustic and psycholinguistic features associated with cognitive deficits contemporaneously and at a 1-2 years follow up (mean follow-up time 512.3, SD 84.5 days).

Results: Combined acoustic and psycholinguistic features achieved high performance (F-scores 0.73-0.86) and sensitivity (up to 0.90) in estimating cognitive deficits across multiple domains. Performance remained high when acoustic and psycholinguistic features were used to predict follow-up cognitive performance. The psycholinguistic features that were most successful at classifying high cognitive impairment reflected vocabulary richness, the quantity of speech produced, and the fragmentation of speech, whereas the analogous top-ranked acoustic features reflected breathing and nonverbal vocalizations such as giggles or laughter.

Conclusions: These results suggest that both acoustic and psycholinguistic features extracted from qualitative interviews may be reliable markers of cognitive deficits in late life.

References

Clarke N, Foltz P, Garrard P . How to do things with (thousands of) words: Computational approaches to discourse analysis in Alzheimer's disease. Cortex. 2020; 129:446-463. DOI: 10.1016/j.cortex.2020.05.001. View

Busse A, Hensel A, Guhne U, Angermeyer M, Riedel-Heller S . Mild cognitive impairment: long-term course of four clinical subtypes. Neurology. 2006; 67(12):2176-85. DOI: 10.1212/01.wnl.0000249117.23318.e1. View

Sundberg J, Nordenberg M . Effects of vocal loudness variation on spectrum balance as reflected by the alpha measure of long-term-average spectra of speech. J Acoust Soc Am. 2006; 120(1):453-7. DOI: 10.1121/1.2208451. View

Roshanzamir A, Aghajan H, Baghshah M . Transformer-based deep neural network language models for Alzheimer's disease risk assessment from targeted speech. BMC Med Inform Decis Mak. 2021; 21(1):92. PMC: 7971114. DOI: 10.1186/s12911-021-01456-3. View

Bird H, Ralph M, Patterson K, Hodges J . The rise and fall of frequency and imageability: noun and verb production in semantic dementia. Brain Lang. 2000; 73(1):17-49. DOI: 10.1006/brln.2000.2293. View

Boschi V, Catricala E, Consonni M, Chesi C, Moro A, Cappa S . Connected Speech in Neurodegenerative Language Disorders: A Review. Front Psychol. 2017; 8:269. PMC: 5337522. DOI: 10.3389/fpsyg.2017.00269. View

Asgari M, Kaye J, Dodge H . Predicting mild cognitive impairment from spontaneous spoken utterances. Alzheimers Dement (N Y). 2017; 3(2):219-228. PMC: 5651423. DOI: 10.1016/j.trci.2017.01.006. View

Ferrario A, Luo M, Polsinelli A, Moseley S, Mehl M, Yordanova K . Predicting Working Memory in Healthy Older Adults Using Real-Life Language and Social Context Information: A Machine Learning Approach. JMIR Aging. 2022; 5(1):e28333. PMC: 8941438. DOI: 10.2196/28333. View

Pakhomov S, Chacon D, Wicklund M, Gundel J . Computerized assessment of syntactic complexity in Alzheimer's disease: a case study of Iris Murdoch's writing. Behav Res Methods. 2011; 43(1):136-44. DOI: 10.3758/s13428-010-0037-9. View

10.

Pell M, Rothermich K, Liu P, Paulmann S, Sethi S, Rigoulot S . Preferential decoding of emotion from human non-linguistic vocalizations versus speech prosody. Biol Psychol. 2015; 111:14-25. DOI: 10.1016/j.biopsycho.2015.08.008. View

11.

Mueller K, Hermann B, Mecollari J, Turkstra L . Connected speech and language in mild cognitive impairment and Alzheimer's disease: A review of picture description tasks. J Clin Exp Neuropsychol. 2018; 40(9):917-939. PMC: 6198327. DOI: 10.1080/13803395.2018.1446513. View

12.

Yamada Y, Shinkawa K, Shimmei K . Atypical Repetition in Daily Conversation on Different Days for Detecting Alzheimer Disease: Evaluation of Phone-Call Data From Regular Monitoring Service. JMIR Ment Health. 2020; 7(1):e16790. PMC: 6996758. DOI: 10.2196/16790. View

13.

Crutch S, Warrington E . Abstract and concrete concepts have structurally different representational frameworks. Brain. 2004; 128(Pt 3):615-27. DOI: 10.1093/brain/awh349. View

14.

Papagno C, Capasso R, Miceli G . Reversed concreteness effect for nouns in a subject with semantic dementia. Neuropsychologia. 2009; 47(4):1138-48. DOI: 10.1016/j.neuropsychologia.2009.01.019. View

15.

Mesulam M . Primary progressive aphasia--a language-based dementia. N Engl J Med. 2003; 349(16):1535-42. DOI: 10.1056/NEJMra022435. View

16.

Taler V, Phillips N . Language performance in Alzheimer's disease and mild cognitive impairment: a comparative review. J Clin Exp Neuropsychol. 2008; 30(5):501-56. DOI: 10.1080/13803390701550128. View

17.

Yang Q, Xu F, Ling Z, Li X, Li Y, Fang D . Selecting and Analyzing Speech Features for the Screening of Mild Cognitive Impairment. Annu Int Conf IEEE Eng Med Biol Soc. 2021; 2021:1906-1910. DOI: 10.1109/EMBC46164.2021.9630752. View

18.

Ahmed S, de Jager C, Haigh A, Garrard P . Semantic processing in connected speech at a uniformly early stage of autopsy-confirmed Alzheimer's disease. Neuropsychology. 2013; 27(1):79-85. DOI: 10.1037/a0031288. View

19.

Jeste D, Glorioso D, Lee E, Daly R, Graham S, Liu J . Study of Independent Living Residents of a Continuing Care Senior Housing Community: Sociodemographic and Clinical Associations of Cognitive, Physical, and Mental Health. Am J Geriatr Psychiatry. 2019; 27(9):895-907. PMC: 7172111. DOI: 10.1016/j.jagp.2019.04.002. View

20.

Dodge H, Mattek N, Gregor M, Bowman M, Seelye A, Ybarra O . Social Markers of Mild Cognitive Impairment: Proportion of Word Counts in Free Conversational Speech. Curr Alzheimer Res. 2015; 12(6):513-9. PMC: 4526336. DOI: 10.2174/1567205012666150530201917. View