Felix Dörr, Loris Grandjean, Johannes Tröger, Jessica Peter
{"title":"当包括语义语言流畅性任务的练习效果时,轻度认知障碍或健康老龄化的分类得到改善。","authors":"Felix Dörr, Loris Grandjean, Johannes Tröger, Jessica Peter","doi":"10.1002/dad2.70127","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Practice effects are an improvement in task performance with repeated testing. Their absence may indicate compromised learning and may help discriminate healthy from pathological ageing.</p><p><strong>Methods: </strong>We recorded semantic verbal fluency three times in <i>n</i> = 58 healthy older adults or patients with amnestic mild cognitive impairment (MCI) (72.16 ± 4.83 years old, 33 women). We extracted speech features and trained a machine learning classifier on them at each cognitive assessment. We examined which variables were informative for classification and whether they correlated with episodic memory performance.</p><p><strong>Results: </strong>We found smaller practice effects in patients with amnestic MCI. There was a 13% improvement in classification performance with features from the third cognitive assessment as compared to the first assessment. Practice effects correlated with episodic memory performance in healthy adults.</p><p><strong>Discussion: </strong>Speech features became more informative for classification when repeatedly assessed. They may be a promising tool for identifying individuals at risk of cognitive decline.</p><p><strong>Highlights: </strong>In MCI, practice effects in verbal fluency tasks were smaller than in healthy adults.Smaller practice effects in MCI indicated compromised learning.Including practice effects improved the classification of MCI vs. healthy ageing.In MCI, practice effects were independent of episodic memory performance.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 2","pages":"e70127"},"PeriodicalIF":4.0000,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136091/pdf/","citationCount":"0","resultStr":"{\"title\":\"The classification of mild cognitive impairment or healthy ageing improves when including practice effects derived from a semantic verbal fluency task.\",\"authors\":\"Felix Dörr, Loris Grandjean, Johannes Tröger, Jessica Peter\",\"doi\":\"10.1002/dad2.70127\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Practice effects are an improvement in task performance with repeated testing. Their absence may indicate compromised learning and may help discriminate healthy from pathological ageing.</p><p><strong>Methods: </strong>We recorded semantic verbal fluency three times in <i>n</i> = 58 healthy older adults or patients with amnestic mild cognitive impairment (MCI) (72.16 ± 4.83 years old, 33 women). We extracted speech features and trained a machine learning classifier on them at each cognitive assessment. We examined which variables were informative for classification and whether they correlated with episodic memory performance.</p><p><strong>Results: </strong>We found smaller practice effects in patients with amnestic MCI. There was a 13% improvement in classification performance with features from the third cognitive assessment as compared to the first assessment. Practice effects correlated with episodic memory performance in healthy adults.</p><p><strong>Discussion: </strong>Speech features became more informative for classification when repeatedly assessed. They may be a promising tool for identifying individuals at risk of cognitive decline.</p><p><strong>Highlights: </strong>In MCI, practice effects in verbal fluency tasks were smaller than in healthy adults.Smaller practice effects in MCI indicated compromised learning.Including practice effects improved the classification of MCI vs. healthy ageing.In MCI, practice effects were independent of episodic memory performance.</p>\",\"PeriodicalId\":53226,\"journal\":{\"name\":\"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring\",\"volume\":\"17 2\",\"pages\":\"e70127\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2025-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136091/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/dad2.70127\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/4/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/dad2.70127","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
The classification of mild cognitive impairment or healthy ageing improves when including practice effects derived from a semantic verbal fluency task.
Introduction: Practice effects are an improvement in task performance with repeated testing. Their absence may indicate compromised learning and may help discriminate healthy from pathological ageing.
Methods: We recorded semantic verbal fluency three times in n = 58 healthy older adults or patients with amnestic mild cognitive impairment (MCI) (72.16 ± 4.83 years old, 33 women). We extracted speech features and trained a machine learning classifier on them at each cognitive assessment. We examined which variables were informative for classification and whether they correlated with episodic memory performance.
Results: We found smaller practice effects in patients with amnestic MCI. There was a 13% improvement in classification performance with features from the third cognitive assessment as compared to the first assessment. Practice effects correlated with episodic memory performance in healthy adults.
Discussion: Speech features became more informative for classification when repeatedly assessed. They may be a promising tool for identifying individuals at risk of cognitive decline.
Highlights: In MCI, practice effects in verbal fluency tasks were smaller than in healthy adults.Smaller practice effects in MCI indicated compromised learning.Including practice effects improved the classification of MCI vs. healthy ageing.In MCI, practice effects were independent of episodic memory performance.
期刊介绍:
Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.