Semantic and Phonemic Verbal Fluency Discrepancy in Mild Cognitive Impairment: Potential Predictor of Progression to Alzheimer's Disease

2018 ◽  
Vol 66 (4) ◽  
pp. 755-759 ◽  
Author(s):  
Roisin M. Vaughan ◽  
Robert F. Coen ◽  
RoseAnne Kenny ◽  
Brian A. Lawlor
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Verbal Fluency ◽  
Potential Predictor ◽  
Phonemic Verbal Fluency

scholarly journals P2-030: 3-D mapping of verbal fluency performance in amnestic mild cognitive impairment and Alzheimer's disease

2009 ◽  
Vol 5 (4S_Part_9) ◽  
pp. P270-P270
Author(s):  
Tao Li ◽  
Mei-Yan Zhang ◽  
Jing Liao ◽  
Daniel Chang ◽  
Huishu Yuan ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Verbal Fluency ◽  
Amnestic Mild Cognitive Impairment

P3-172: Comparison of fruit vs. animal verbal fluency in the screening for mild cognitive impairment and Alzheimer's disease

2008 ◽  
Vol 4 ◽  
pp. T570-T570
Author(s):  
Marcia Radanovic ◽  
Roberta M. Mirandez ◽  
Breno S.O. Diniz ◽  
Monica S. Yassuda ◽  
Fernanda S. Pereira ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Verbal Fluency

Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer's Disease

2014 ◽  
Vol 38 (1-2) ◽  
pp. 1-9 ◽  
Author(s):  
Eric Rinehardt ◽  
Katie Eichstaedt ◽  
John A. Schinka ◽  
David A. Loewenstein ◽  
Michelle Mattingly ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Verbal Fluency

P3-271: Automated index of semantic verbal fluency in mild cognitive impairment and Alzheimer's disease

2012 ◽  
Vol 8 (4S_Part_15) ◽  
pp. P555-P555
Author(s):  
Serguei Pakhomov ◽  
Laura Hemmy ◽  
Michael Kuskowski ◽  
Rosebud Roberts ◽  
Ronald Petersen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Verbal Fluency ◽  
Semantic Verbal Fluency

Multiple category verbal fluency in mild cognitive impairment and correlation with CSF biomarkers for Alzheimer's disease

2017 ◽  
Vol 29 (6) ◽  
pp. 949-958 ◽  
Author(s):  
Roberta M. Mirandez ◽  
Ivan Aprahamian ◽  
Leda L. Talib ◽  
Orestes V. Forlenza ◽  
Marcia Radanovic
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Verbal Fluency ◽  
Csf Biomarkers ◽  
Healthy Elderly ◽  
Model Animal ◽  
Neuropsychological Evaluations ◽  
T Tau

ABSTRACTBackground:Verbal fluency (VF) tasks are widely used in neuropsychological evaluations, as a measure of executive/semantic dysfunction. The revised criteria for Alzheimer's disease (AD) diagnosis (National Institute on Aging and the Alzheimer Association, 2011) incorporating biomarkers has increased the interest in finding algorithms that combine neuropsychological and biomarkers features to better predict conversion from mild cognitive impairment (MCI) to AD. Our aim was to compare the most frequently used VF categories to determine which best discriminated cognitively healthy elderly from MCI patients, and whether cerebrospinal fluid (CSF) biomarkers levels (Aβ42, P-tau, T-tau, and Aβ42/P-tau) correlated with patient's performance in MCI.Methods:We studied 37 cognitively healthy elderly and 30 MCI patients in five VF tasks (animal, fruits, means of transportation, FAS-COWA, and verbs); 23 controls and 19 MCI patients had their CSF biomarkers for AD determined.Results:MCI group performed worse than controls in all VF tasks (p < 0.0001). The cut-off scores were: 14 (animals) (AUC = 0.794), 12 (fruits and means of transportation) (AUC = 0.740 and 0.719, respectively), 41 (FAS) (AUC = 0.744), and 11 (verbs) (AUC = 0.700). The model “animal plus FAS-COWA” was the best to discriminate both groups (AUC = 0.833) (all p < 0.05). MCI produced fewer words than controls in the second-half of the task for all categories (p < 0.001). T-tau levels were negatively correlated to animal fluency (r= −0.485, p = 0.035), and showed a trend for negative correlation with fruits fluency (r= −0.4429, p = 0.057).Conclusions:Animal fluency alone and combined to FAS-COWA was slightly superior in discriminating controls from MCI (p < 0.001), and correlated to T-tau levels.

scholarly journals Total output and switching in ategory fluency successfully iscriminates Alzheimer's disease from Mild Cognitive Impairment, but not from frontotemporal dementia

2015 ◽  
Vol 9 (3) ◽  
pp. 251-257 ◽  
Author(s):  
Siddharth Ramanan ◽  
Jwala Narayanan ◽  
Tanya Perpetua D'Souza ◽  
Kavita Shivani Malik ◽  
Ellajosyula Ratnavalli
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Frontotemporal Dementia ◽  
Verbal Fluency ◽  
Total Output ◽  
Time Period ◽  
Phonemic Fluency

Verbal fluency tasks require generation of words beginning with a letter (phonemic fluency; PF) or from a category (category fluency; CF) within a limited time period. Generally, total output on CF has been used to discriminate Mild Cognitive Impairment (MCI) from Alzheimer's disease (AD), while poor PF has been used as a marker for behavioral-variant frontotemporal dementia (bvFTD). However, in the absence of this disparate performance, further characterization of the task becomes necessary. Objective: We examined whether fluency, as well as its components, clustering (successively generated words belonging to a category) and switching (shifting between categories) carried diagnostic utility in discriminating AD from MCI and bvFTD. Methods: PF (letter 'P') and CF ('animals') tasks were administered in English to patients with MCI (n=25), AD (n=37), and bvFTD (n=17). Clustering and switching scores were calculated using established criteria. Results: Our findings suggested that up to 85% of AD and MCI could be successfully discriminated based on total number of responses and switching in CF alone. PF-CF disparity was not noted in AD or bvFTD. Performance on clustering or switching also proved insufficient to discriminate AD from bvFTD. Conclusion: Switching was found to be useful when differentiating AD from MCI. In AD and bvFTD, the course of progression of the disease may lead to attenuation of total number of responses produced on both tasks to an extent where clustering and switching may not be useful measures to discriminate these dementias from each other.

Voice Markers of Lexical Access in Mild Cognitive Impairment and Alzheimer's Disease

2018 ◽  
Vol 15 (2) ◽  
pp. 111-119 ◽  
Author(s):  
Juan J.G. Meilan ◽  
Francisco Martinez-Sanchez ◽  
Juan Carro ◽  
Nuria Carcavilla ◽  
Olga Ivanova
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Lexical Access ◽  
Verbal Memory ◽  
Verbal Fluency ◽  
Acoustic Analysis ◽  
Acoustic Parameters ◽  
Voice And Speech

Background: Recent studies have identified the correlation between dementia and certain vocal features, such as voice and speech changes. Vocal features may act as early markers of Alzheimer's disease (AD). Despite being present in non-pathological senescence and Mild Cognitive Impairment, especially in its amnesic subtype (aMCI), these voice- and speech-related symptoms are the first signs of AD. The purpose of this study is to verify whether these signs are related to deficits in lexical access, which appear early in AD. Method: Anomic deficits in persons with MCI and AD are assessed through tests on verbal memory, denomination by confrontation, and verbal fluency. In addition, an acoustic analysis of speech is conducted in a reading task to identify the acoustic parameters associated with the groups analyzed, and their relation to the degree of anomic impairment observed in each one of them. Results and Conclusions: The results show a direct relationship between the different acoustic parameters present in AD and the verbal fluency tests results.

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