Lexical factors and cerebral regions influencing verbal fluency performance in MCI
- PMID: 24384308
- DOI: 10.1016/j.neuropsychologia.2013.12.010
Lexical factors and cerebral regions influencing verbal fluency performance in MCI
Abstract
Objective: To evaluate assumptions regarding semantic (noun), verb, and letter fluency in mild cognitive impairment (MCI) and Alzheimer disease (AD) using novel techniques for measuring word similarity in fluency lists and a region of interest (ROI) analysis of gray matter correlates.
Method: Fifty-eight individuals with normal cognition (NC, n=25), MCI (n=23), or AD (n=10) underwent neuropsychological tests, including 10 verbal fluency tasks (three letter tasks [F, A, S], six noun categories [animals, water creatures, fruits and vegetables, tools, vehicles, boats], and verbs). All pairs of words generated by each participant on each task were compared in terms of semantic (meaning), orthographic (spelling), and phonemic (pronunciation) similarity. We used mixed-effects logistic regression to determine which lexical factors were predictive of word adjacency within the lists. Associations between each fluency raw score and gray matter volumes in sixteen ROIs were identified by means of multiple linear regression. We evaluated causal models for both types of analyses to specify the contributions of diagnosis and various mediator variables to the outcomes of word adjacency and fluency raw score.
Results: Semantic similarity between words emerged as the strongest predictor of word adjacency for all fluency tasks, including the letter fluency tasks. Semantic similarity mediated the effect of cognitive impairment on word adjacency only for three fluency tasks employing a biological cue. Orthographic similarity was predictive of word adjacency for the A and S tasks, while phonemic similarity was predictive only for the S task and one semantic task (vehicles). The ROI analysis revealed different patterns of correlations among the various fluency tasks, with the most common associations in the right lower temporal and bilateral dorsal frontal regions. Following correction with gray matter volumes from the opposite hemisphere, significant associations persisted for animals, vehicles, and a composite nouns score in the left inferior frontal gyrus, but for letter A, letter S, and a composite FAS score in the right inferior frontal gyrus. These regressions also revealed a lateralized association of the left subcortical nuclei with all letter fluency scores and fruits and vegetables fluency, and an association of the right lower temporal ROI with letter A, FAS, and verb fluency. Gray matter volume in several bihemispheric ROIs (left dorsal frontal, right lower temporal, right occipital, and bilateral mesial temporal) mediated the relationship between cognitive impairment and fluency for fruits and vegetables. Gray matter volume in the right lower temporal ROI mediated the relationship between cognitive impairment and five fluency raw scores (animals, fruits and vegetables, tools, verbs, and the composite nouns score).
Conclusion: Semantic memory exerts the strongest influence on word adjacency in letter fluency as well as semantic verbal fluency tasks. Orthography is a stronger influence than pronunciation. All types of fluency task raw scores (letter, noun, and verb) correlate with cerebral regions known to support verbal or nonverbal semantic memory. The findings emphasize the contribution of right hemisphere regions to fluency task performance, particularly for verb and letter fluency. The relationship between diagnosis and semantic fluency performance is mediated by semantic similarity of words and by gray matter volume in the right lower temporal region.
Keywords: Alzheimer's disease; Mild cognitive impairment; Natural language processing; Semantic memory; Verbal fluency.
Published by Elsevier Ltd.
Similar articles
-
Characterizing cognitive performance in a large longitudinal study of aging with computerized semantic indices of verbal fluency.Neuropsychologia. 2016 Aug;89:42-56. doi: 10.1016/j.neuropsychologia.2016.05.031. Epub 2016 May 28. Neuropsychologia. 2016. PMID: 27245645 Free PMC article.
-
Typicality of words produced on a semantic fluency task in amnesic mild cognitive impairment: linguistic analysis and risk of conversion to dementia.J Alzheimers Dis. 2014;42(4):1171-8. doi: 10.3233/JAD-140570. J Alzheimers Dis. 2014. PMID: 25024315
-
[Verbal fluency tests--application in neuropsychological assessment].Psychiatr Pol. 2013 May-Jun;47(3):475-85. Psychiatr Pol. 2013. PMID: 23885541 Review. Polish.
-
The neuroanatomical substrate of lexical-semantic decline in MCI APOE ε4 carriers and noncarriers.Alzheimer Dis Assoc Disord. 2011 Jul-Sep;25(3):230-41. doi: 10.1097/WAD.0b013e318206f88c. Alzheimer Dis Assoc Disord. 2011. PMID: 21192234
-
Verbal fluency performance in dementia of the Alzheimer's type: a meta-analysis.Neuropsychologia. 2004;42(9):1212-22. doi: 10.1016/j.neuropsychologia.2004.02.001. Neuropsychologia. 2004. PMID: 15178173 Review.
Cited by
-
Neuropsychological differential diagnosis of Alzheimer's disease and vascular dementia: a systematic review with meta-regressions.Front Aging Neurosci. 2023 Nov 6;15:1267434. doi: 10.3389/fnagi.2023.1267434. eCollection 2023. Front Aging Neurosci. 2023. PMID: 38020767 Free PMC article.
-
Brain-derived neurotrophic factor gene polymorphism affects cognitive function and neurofilament light chain level in patients with subcortical ischaemic vascular dementia.Front Aging Neurosci. 2023 Oct 9;15:1244191. doi: 10.3389/fnagi.2023.1244191. eCollection 2023. Front Aging Neurosci. 2023. PMID: 37876876 Free PMC article.
-
Qualitative Verbal Fluency Components as Prognostic Factors for Developing Alzheimer's Dementia and Mild Cognitive Impairment: Results from the Population-Based HELIAD Cohort.Medicina (Kaunas). 2022 Dec 9;58(12):1814. doi: 10.3390/medicina58121814. Medicina (Kaunas). 2022. PMID: 36557016 Free PMC article.
-
Reduced phonemic fluency in progressive supranuclear palsy is due to dysfunction of dominant BA6.Front Aging Neurosci. 2022 Sep 8;14:969875. doi: 10.3389/fnagi.2022.969875. eCollection 2022. Front Aging Neurosci. 2022. PMID: 36158541 Free PMC article.
-
Selecting the Most Important Features for Predicting Mild Cognitive Impairment from Thai Verbal Fluency Assessments.Sensors (Basel). 2022 Aug 3;22(15):5813. doi: 10.3390/s22155813. Sensors (Basel). 2022. PMID: 35957370 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
Research Materials
Miscellaneous