How language flows when movements don't: An automated analysis of spontaneous discourse in Parkinson's disease.
Garcia, Adolfo M. a,b,c,*; Carrillo, Facundo b,d; Orozco-Arroyave, Juan Rafael e,f; Trujillo, Natalia g,h; Vargas Bonilla, Jesus F. e; Fittipaldi, Sol a; Adolfi, Federico a; Noth, Elmar f; Sigman, Mariano i; Fernandez Slezak, Diego b,d; Ibanez, Agustin a,b,j,k,l; Cecchi, Guillermo A. m,*
[Article]
Brain & Language.
162:19-28, November 2016.
(Format: HTML, PDF)
: To assess the impact of Parkinson's disease (PD) on spontaneous discourse, we conducted computerized analyses of brief monologues produced by 51 patients and 50 controls. We explored differences in semantic fields (via latent semantic analysis), grammatical choices (using part-of-speech tagging), and word-level repetitions (with graph embedding tools). Although overall output was quantitatively similar between groups, patients relied less heavily on action-related concepts and used more subordinate structures. Also, a classification tool operating on grammatical patterns identified monologues as pertaining to patients or controls with 75% accuracy. Finally, while the incidence of dysfluent word repetitions was similar between groups, it allowed inferring the patients' level of motor impairment with 77% accuracy. Our results highlight the relevance of studying naturalistic discourse features to tap the integrity of neural (and, particularly, motor) networks, beyond the possibilities of standard token-level instruments.
Highlights:
* We assessed spontaneous discourse in Parkinson's disease (PD) with automatized tools.
* Compared to controls, patients used fewer action concepts and more subordinators.
* Analysis of grammar choices allowed classifying patients and controls above chance.
* The incidence of word repetitions predicted the patients' level of motor impairment.
* Naturalistic discourse features may index the integrity of specific neural networks.
(C) 2016Elsevier, Inc.
