D G Clark1, V G Wadley2, P Kapur3, T P DeRamus4, B Singletary5, A P Nicholas6, P D Blanton7, K Lokken7, H Deshpande8, D Marson9, G Deutsch8. 1. Birmingham VA Medical Center, USA; Department of Neurology, University of Alabama at Birmingham, USA. Electronic address: dgclark@uab.edu. 2. Division of Gerontology, Geriatrics, and Palliative Care, Department of Medicine, University of Alabama at Birmingham, USA. 3. Department of Medicine, Mount Sinai School of Medicine, USA. 4. Department of Psychology and Behavioral Neuroscience, University of Alabama at Birmingham, USA. 5. Department of Surgery, University of Alabama at Birmingham, USA. 6. Birmingham VA Medical Center, USA; Department of Neurology, University of Alabama at Birmingham, USA. 7. Birmingham VA Medical Center, USA. 8. Department of Radiology, University of Alabama at Birmingham, USA. 9. Department of Neurology, University of Alabama at Birmingham, USA.
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. Published by Elsevier Ltd.
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. Published by Elsevier Ltd.
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