Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia

Journal
Alzheimer's & Dementia
ISSN
1552-5260
1552-5279
Date Issued
2023
Author(s)
Franco J. Ferrante
Joaquín Migeot
Agustina Birba
Lucía Amoruso
Gonzalo Pérez
Eugenia Hesse
Enzo Tagliazucchi
Claudio Estienne
Cecilia Serrano
Diana Matallana
Agustín Ibáñez
Sol Fittipaldi
Cecilia Gonzalez Campo
Adolfo M. García
Type
Resource Types::text::journal::journal article
Scopus ID
2-s2.0-85173891203
WoS ID
WOS:001082121200001
DOI
URL
URL Institutional Repository
Abstract
<jats:title>Abstract</jats:title><jats:sec><jats:title>INTRODUCTION</jats:title><jats:p>Verbal fluency tasks are common in Alzheimer's disease (AD) assessments. Yet, standard valid response counts fail to reveal disease‐specific semantic memory patterns. Here, we leveraged automated word‐property analysis to capture neurocognitive markers of AD vis‐à‐vis behavioral variant frontotemporal dementia (bvFTD).</jats:p></jats:sec><jats:sec><jats:title>METHODS</jats:title><jats:p>Patients and healthy controls completed two fluency tasks. We counted valid responses and computed each word's frequency, granularity, neighborhood, length, familiarity, and imageability. These features were used for group‐level discrimination, patient‐level identification, and correlations with executive and neural (magnetic resonanance imaging [MRI], functional MRI [fMRI], electroencephalography [EEG]) patterns.</jats:p></jats:sec><jats:sec><jats:title>RESULTS</jats:title><jats:p>Valid responses revealed deficits in both disorders. Conversely, frequency, granularity, and neighborhood yielded robust group‐ and subject‐level discrimination only in AD, also predicting executive outcomes. Disease‐specific cortical thickness patterns were predicted by frequency in both disorders. Default‐mode and salience network hypoconnectivity, and EEG beta hypoconnectivity, were predicted by frequency and granularity only in AD.</jats:p></jats:sec><jats:sec><jats:title>DISCUSSION</jats:title><jats:p>Word‐property analysis of fluency can boost AD characterization and diagnosis.</jats:p></jats:sec><jats:sec><jats:title>Highlights</jats:title><jats:p><jats:list list-type="bullet">
<jats:list-item><jats:p>We report novel word‐property analyses of verbal fluency in AD and bvFTD.</jats:p></jats:list-item>
<jats:list-item><jats:p>Standard valid response counts captured deficits and brain patterns in both groups.</jats:p></jats:list-item>
<jats:list-item><jats:p>Specific word properties (e.g., frequency, granularity) were altered only in AD.</jats:p></jats:list-item>
<jats:list-item><jats:p>Such properties predicted cognitive and neural (MRI, fMRI, EEG) patterns in AD.</jats:p></jats:list-item>
<jats:list-item><jats:p>Word‐property analysis of fluency can boost AD characterization and diagnosis.</jats:p></jats:list-item>
</jats:list></jats:p></jats:sec>
Cite this document
Ferrante, F. J., Migeot, J., Birba, A., Amoruso, L., Pérez, G., Hesse, E., Tagliazucchi, E., Estienne, C., Serrano, C., Slachevsky, A., Matallana, D., Reyes, P., Ibáñez, A., Fittipaldi, S., Campo, C. G., & García, A. M. (2024). Multivariate word properties in fluency tasks reveal markers of Alzheimer’s dementia. Alzheimer’s & Dementia, 20(2), 925-940. https://doi.org/10.1002/alz.13472
Subjects
electroencephalography

; 

machine learning

; 

neurodegeneration

; 

neuroimaging

; 

semantic memory

; 

word properties

; 

alzheimer disease

; 

brain

; 

frontotemporal dementia

; 

humans

; 

magnetic resonance imaging

; 

memory

; 

memory disorders

; 

neuropsychological tests

; 

aged

; 

alzheimer disease

; 

article

; 

clinical article

; 

clinical outcome

; 

cognition

; 

controlled study

; 

cortical thickness (brain)

; 

default mode network

; 

dementia

; 

electroencephalography

; 

female

; 

frequency

; 

frontal variant frontotemporal dementia

; 

functional connectivity

; 

functional magnetic resonance imaging

; 

functional neuroimaging

; 

human

; 

male

; 

neighborhood

; 

neuroimaging

; 

nuclear magnetic resonance imaging

; 

salience network

; 

alzheimer disease

; 

brain

; 

diagnostic imaging

; 

frontotemporal dementia

; 

memory

; 

memory disorder

; 

neuropsychological assessment