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Automated Detection of Speech Timing Alterations in Autopsy-Confirmed Nonfluent/Agrammatic Variant Primary
Adolfo M García1, Ariane E Welch1, Maria Luisa Mandelli1
1From the Global Brain Health Institute (A.M.G.), University of California, San Francisco; Cognitive Neuroscience Center (A.M.G.), Universidad de San Andrés, Buenos Aires; National Scientific and Technical Research Council (CONICET) (A.M.G.), Buenos Aires, Argentina; Departamento de Lingüística y Literatura, Facultad de Humanidades (A.M.G.), Universidad de Santiago de Chile; Memory and Aging Center (A.E.W., M.L.M., S.L., J.D., B.M.R., D.L.L.P., B.L.M., W.S., M.L.G.-T.), Department of Neurology, University of California, San Francisco; Department of Communication Sciences and Disorders (M.L.H.), University of Texas at Austin; Department of Communication Sciences and Disorders (S.L.), Adelphi University, Garden City, NY; Cognitive Neurology and Aphasia Unit (M.J.T.P.), Centro de Investigaciones Médico-Sanitarias (M.J.T.P.), University of Malaga; Instituto de Investigación Biomédica de Málaga - IBIMA (M.J.T.P.), Malaga; Area of Psychobiology (M.J.T.P.), Faculty of Psychology and Speech Therapy, University of Malaga, Malaga, Spain; Sección Neurología (D.L.L.P.), Departamento de Especialidades, Facultad de Medicina, Universidad de Concepción, Chile; Centre for Neuroscience of Speech (A.P.V.), Department of Audiology & Speech Pathology, The University of Melbourne; and Redenlab (A.P.V.), Melbourne, Australia.
Automated speech timing analysis accurately identifies nonfluent/agrammatic primary progressive aphasia (nfvPPA) by detecting speech alterations. This objective method aids in diagnosing nfvPPA and differentiating it from other conditions.
Area of Science:
- Neurology
- Speech Science
- Computational Linguistics
Background:
- Motor speech function, particularly speech timing, is crucial for diagnosing nonfluent/agrammatic variant primary progressive aphasia (nfvPPA).
- Current diagnostic methods rely on subjective evaluations, limiting reliability and scalability.
- Few studies have linked speech alterations to specific neuropathological findings in autopsy-proven cases.
Purpose of the Study:
- To investigate the utility of automated speech timing analyses in diagnosing nfvPPA.
- To correlate speech timing deficits with neuroanatomical changes in autopsy-proven nfvPPA.
- To differentiate nfvPPA from semantic variant PPA (svPPA) and healthy controls (HCs).
Main Methods:
- A cross-sectional study involving an overt reading task.
- Quantification of articulation rate, syllable/pause durations, and their variability.
- Assessment of neuroanatomical disruptions via cortical thickness and white matter atrophy analysis in 22 nfvPPA, 15 svPPA, and 10 HCs.
Main Results:
- Speech timing measures were significantly altered in nfvPPA compared to HC and svPPA groups.
- Articulation rate effectively discriminated nfvPPA from HCs (AUC=0.95), outperforming clinical assessments.
- nfvPPA showed structural abnormalities in frontal regions, with articulation rate correlating to specific motor area atrophy.
Conclusions:
- Automated speech timing analysis offers objective and scalable markers for nfvPPA diagnosis.
- This approach can potentially distinguish between different tauopathies underlying nfvPPA.
- Automated speech analysis can supplement standard clinical speech assessments.
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