Literature DB >> 22659109

Automated semantic indices related to cognitive function and rate of cognitive decline.

Serguei V S Pakhomov1, Laura S Hemmy, Kelvin O Lim.   

Abstract

The objective of our study is to introduce a fully automated, computational linguistic technique to quantify semantic relations between words generated on a standard semantic verbal fluency test and to determine its cognitive and clinical correlates. Cognitive differences between patients with Alzheimer's disease and mild cognitive impairment are evident in their performance on the semantic verbal fluency test. In addition to the semantic verbal fluency test score, several other performance characteristics sensitive to disease status and predictive of future cognitive decline have been defined in terms of words generated from semantically related categories (clustering) and shifting between categories (switching). However, the traditional assessment of clustering and switching has been performed manually in a qualitative fashion resulting in subjective scoring with limited reproducibility and scalability. Our approach uses word definitions and hierarchical relations between the words in WordNet(®), a large electronic lexical database, to quantify the degree of semantic similarity and relatedness between words. We investigated the novel semantic fluency indices of mean cumulative similarity and relatedness between all pairs of words regardless of their order, and mean sequential similarity and relatedness between pairs of adjacent words in a sample of patients with clinically diagnosed probable (n=55) or possible (n=27) Alzheimer's disease or mild cognitive impairment (n=31). The semantic fluency indices differed significantly between the diagnostic groups, and were strongly associated with neuropsychological tests of executive function, as well as the rate of global cognitive decline. Our results suggest that word meanings and relations between words shared across individuals and computationally modeled via WordNet and large text corpora provide the necessary context to account for the variability in language-based behavior and relate it to cognitive dysfunction observed in mild cognitive impairment and Alzheimer's disease.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22659109      PMCID: PMC3404821          DOI: 10.1016/j.neuropsychologia.2012.05.016

Source DB:  PubMed          Journal:  Neuropsychologia        ISSN: 0028-3932            Impact factor:   3.139


  42 in total

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Journal:  J Clin Exp Neuropsychol       Date:  2000-06       Impact factor: 2.475

2.  On the dissociation between clustering and switching in verbal fluency: comment on Troyer, Moscovitch, Winocur, Alexander and Stuss.

Authors:  Ulrich Mayr
Journal:  Neuropsychologia       Date:  2002       Impact factor: 3.139

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6.  Classification of Alzheimer disease, mild cognitive impairment, and normal cognitive status with large-scale network analysis based on resting-state functional MR imaging.

Authors:  Gang Chen; B Douglas Ward; Chunming Xie; Wenjun Li; Zhilin Wu; Jennifer L Jones; Malgorzata Franczak; Piero Antuono; Shi-Jiang Li
Journal:  Radiology       Date:  2011-01-19       Impact factor: 11.105

7.  Abnormal cortical networks in mild cognitive impairment and Alzheimer's disease.

Authors:  Zhijun Yao; Yuanchao Zhang; Lei Lin; Yuan Zhou; Cunlu Xu; Tianzi Jiang
Journal:  PLoS Comput Biol       Date:  2010-11-18       Impact factor: 4.475

Review 8.  Concepts and categories: a cognitive neuropsychological perspective.

Authors:  Bradford Z Mahon; Alfonso Caramazza
Journal:  Annu Rev Psychol       Date:  2009       Impact factor: 24.137

9.  A plateau in pre-Alzheimer memory decline: evidence for compensatory mechanisms?

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Journal:  Neurology       Date:  2007-07-10       Impact factor: 9.910

10.  Comparisons of verbal fluency tasks in the detection of dementia of the Alzheimer type.

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Journal:  Arch Neurol       Date:  1992-12
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  8 in total

1.  A computational linguistic measure of clustering behavior on semantic verbal fluency task predicts risk of future dementia in the nun study.

Authors:  Serguei V S Pakhomov; Laura S Hemmy
Journal:  Cortex       Date:  2013-06-14       Impact factor: 4.027

2.  Language networks associated with computerized semantic indices.

Authors:  Serguei V S Pakhomov; David T Jones; David S Knopman
Journal:  Neuroimage       Date:  2014-10-12       Impact factor: 6.556

3.  Characterizing cognitive performance in a large longitudinal study of aging with computerized semantic indices of verbal fluency.

Authors:  Serguei V S Pakhomov; Lynn Eberly; David Knopman
Journal:  Neuropsychologia       Date:  2016-05-28       Impact factor: 3.139

4.  CANTAB object recognition and language tests to detect aging cognitive decline: an exploratory comparative study.

Authors:  Fernanda Cabral Soares; Thaís Cristina Galdino de Oliveira; Liliane Dias e Dias de Macedo; Alessandra Mendonça Tomás; Domingos Luiz Wanderley Picanço-Diniz; João Bento-Torres; Natáli Valim Oliver Bento-Torres; Cristovam Wanderley Picanço-Diniz
Journal:  Clin Interv Aging       Date:  2014-12-19       Impact factor: 4.458

5.  Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline?

Authors:  Daniela Beltrami; Gloria Gagliardi; Rema Rossini Favretti; Enrico Ghidoni; Fabio Tamburini; Laura Calzà
Journal:  Front Aging Neurosci       Date:  2018-11-13       Impact factor: 5.750

6.  Comprehensive verbal fluency features predict executive function performance.

Authors:  Julia Amunts; Julia A Camilleri; Simon B Eickhoff; Kaustubh R Patil; Stefan Heim; Georg G von Polier; Susanne Weis
Journal:  Sci Rep       Date:  2021-03-25       Impact factor: 4.379

7.  A comparison of techniques for deriving clustering and switching scores from verbal fluency word lists.

Authors:  Justin Bushnell; Diana Svaldi; Matthew R Ayers; Sujuan Gao; Frederick Unverzagt; John Del Gaizo; Virginia G Wadley; Richard Kennedy; Joaquín Goñi; David Glenn Clark
Journal:  Front Psychol       Date:  2022-09-14

8.  On the selection of non-invasive methods based on speech analysis oriented to automatic Alzheimer disease diagnosis.

Authors:  Karmele López-de-Ipiña; Jesus-Bernardino Alonso; Carlos Manuel Travieso; Jordi Solé-Casals; Harkaitz Egiraun; Marcos Faundez-Zanuy; Aitzol Ezeiza; Nora Barroso; Miriam Ecay-Torres; Pablo Martinez-Lage; Unai Martinez de Lizardui
Journal:  Sensors (Basel)       Date:  2013-05-21       Impact factor: 3.576

  8 in total

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