3 research outputs found
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Inhibitory control and the production of disfluencies in speakers with Alzheimer’s Disease
This paper presents preliminary findings from a longitudinal study that investigates the ability of speakers diagnosed with Alzheimer's Disease (AD) to manage distractions and the same speakers’ production of hesitations in semi-spontaneous speech. Previous research has found that two kinds of hesitation: silent pauses and reformulations, are significantly influenced by inhibitory control in healthy second language learners. Silent pauses are also well-known linguistic markers of disease progression in people living with AD and may evidence a speaker’s production problems, whereas reformulations promote the joint discourse. Inhibitory control is therefore associated with disfluencies that are personal and social.
It was hypothesised that first language speakers with a diagnosis of AD would make fewer reformulations and produce more silent pauses relative to healthy individuals. Data that included a Stroop task, a two-minute monologue, and a two- minute category fluency task were collected and analysed from 11 participants with AD and 13 healthy Controls.
In AD participants, only the number of silent pauses correlated with the Stroop task, while reformulations correlated with the MoCA, and silent pause duration with the MoCA and category fluency task, suggesting that the effects of disease- related cognitive decline rather than competing information were responsible for the lack of fluency
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The elusive nature of APOE e4 in mid-adulthood: understanding the cognitive profile
Objectives: The apolipoprotein E (APOE) e4 allele is an established risk factor for dementia, yet this genetic variant is associated with a mixed cognitive profile across the lifespan. This study undertakes both a systematic and meta-analytic review of research investigating APOE-related differences in cognition in mid-adulthood, when detrimental effects of the allele may first be detectable. Methods: Thirty-six papers investigating the behavioral effects of APOE e4 in mid-adulthood (defined as a mean sample age between 35 and 60 years) were reviewed. In addition, the effect of carrying an e4 allele on individual cognitive domains was assessed in separate meta-analyses. Results: The average effect size of APOE e4 status was non-significant across cognitive domains. Further consideration of genotype effects indicates preclinical effects of APOE e4 may be observable in memory and executive functioning. Conclusions: The cognitive profile of APOE e4 carriers at mid-age remains elusive. Although there is support for comparable performance by e4 and non-e4 carriers in the 5th decade, studies administering sensitive cognitive paradigms indicate a more nuanced profile of cognitive differences. Methodological issues in this field preclude strong conclusions, which future research must address, as well as considering the influence of further vulnerability factors on genotype effects
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Artificial intelligence for dementia-Applied models and digital health.
INTRODUCTION: The use of applied modeling in dementia risk prediction, diagnosis, and prognostics will have substantial public health benefits, particularly as "deep phenotyping" cohorts with multi-omics health data become available. METHODS: This narrative review synthesizes understanding of applied models and digital health technologies, in terms of dementia risk prediction, diagnostic discrimination, prognosis, and progression. Machine learning approaches show evidence of improved predictive power compared to standard clinical risk scores in predicting dementia, and the potential to decompose large numbers of variables into relatively few critical predictors. RESULTS: This review focuses on key areas of emerging promise including: emphasis on easier, more transparent data sharing and cohort access; integration of high-throughput biomarker and electronic health record data into modeling; and progressing beyond the primary prediction of dementia to secondary outcomes, for example, treatment response and physical health. DISCUSSION: Such approaches will benefit also from improvements in remote data measurement, whether cognitive (e.g., online), or naturalistic (e.g., watch-based accelerometry).</p