A comparison of different connected-speech tasks for detecting mild cognitive impairment using multivariate pattern analysis.
Background: It is common for the elderly population to have age-associated cognitive decline and/or develop neurodegenerative diseases such as dementia. Several studies have suggested that classification algorithms based on linguistic features may be useful for the early detection of mild cognitive...
| Publicado en: | Aphasiology Vol. 39; no. 4; pp. 476 - 500 |
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| Autores principales: | , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Apr2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=183941019&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 183941019 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02687038 B6J jtl: Aphasiology issn: 02687038 maglogo: N pubinfo: dt: Apr2025 vid: 39 iid: 4 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 183941019 177550458 183941019 183941019 10.1080/02687038.2024.2358556 183941019 ppf: 476 ppct: 24 formats: tig: atl: A comparison of different connected-speech tasks for detecting mild cognitive impairment using multivariate pattern analysis. aug: au: Chen, Yiting Hartsuiker, Robert J. Pistono, Aurélie affil: Department of Experimental Psychology, Ghent University, Ghent, Belgium sug: subj: Mild Cognitive Impairment Diagnosis Speech Production Measurement Speech Physiology Language Processing Semantics Human Univariate Statistics Multivariate Analysis Delaware Storytelling ab: Background: It is common for the elderly population to have age-associated cognitive decline and/or develop neurodegenerative diseases such as dementia. Several studies have suggested that classification algorithms based on linguistic features may be useful for the early detection of mild cognitive impairment (MCI). Aims: The current study aimed to examine connected-speech performance in people with MCI and cognitively healthy controls (HC). It tests whether patterns of lexical-semantic features extracted from these tasks could distinguish participants with MCI from HC, using univariate and multivariate analyses. Methods & procedure: We selected 16 English-speaking participants with MCI and 16 matched HC from the Delaware corpus. Four connected-speech tasks (a picture description, a story narrative, a story recall, and a procedural narrative). Eight lexical-semantic features were selected for analyses. Outcomes & results: Univariate analyses showed inter-group differences in revision ratio, core lexicon, or open/closed class words ratio, depending on the task. Multivariate pattern analysis (MVPA) results demonstrated that the story recall task is the only task that can discriminate the two groups above chance. Conclusion: To conclude, results showed that connected-speech tasks have the potential to detect subtle language changes in people with MCI. In particular, the story recall task had the potential to predict the group of a participant (MCI or HC). pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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