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DIVA Meets EEG: Model Validation Using Formant-Shift Reflex.
Cuadros, Jhosmary; Z-Rivera, Lucía; Castro, Christian; Whitaker, Grace; Otero, Mónica; Weinstein, Alejandro; Martínez-Montes, Eduardo; Prado, Pavel; Zañartu, Matías.
Afiliación
  • Cuadros J; Department of Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile.
  • Z-Rivera L; Advanced Center for Electrical and Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile.
  • Castro C; Grupo de Bioingeniería, Decanato de Investigación, Universidad Nacional Experimental del Táchira, San Cristóbal 5001, Venezuela.
  • Whitaker G; Advanced Center for Electrical and Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile.
  • Otero M; Escuela de Ingeniería Civil Biomédica, Facultad de Ingeniería, Universidad de Valparaíso, Valparaíso 2350026, Chile.
  • Weinstein A; Advanced Center for Electrical and Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile.
  • Martínez-Montes E; Escuela de Ingeniería Civil Biomédica, Facultad de Ingeniería, Universidad de Valparaíso, Valparaíso 2350026, Chile.
  • Prado P; Advanced Center for Electrical and Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile.
  • Zañartu M; Facultad de Ingeniería, Arquitectura y Diseño, Universidad San Sebastián, Santiago 8420524, Chile.
Appl Sci (Basel) ; 13(13)2023 Jul 01.
Article en En | MEDLINE | ID: mdl-38435340
ABSTRACT
The neurocomputational model 'Directions into Velocities of Articulators' (DIVA) was developed to account for various aspects of normal and disordered speech production and acquisition. The neural substrates of DIVA were established through functional magnetic resonance imaging (fMRI), providing physiological validation of the model. This study introduces DIVA_EEG an extension of DIVA that utilizes electroencephalography (EEG) to leverage the high temporal resolution and broad availability of EEG over fMRI. For the development of DIVA_EEG, EEG-like signals were derived from original equations describing the activity of the different DIVA maps. Synthetic EEG associated with the utterance of syllables was generated when both unperturbed and perturbed auditory feedback (first formant perturbations) were simulated. The cortical activation maps derived from synthetic EEG closely resembled those of the original DIVA model. To validate DIVA_EEG, the EEG of individuals with typical voices (N = 30) was acquired during an altered auditory feedback paradigm. The resulting empirical brain activity maps significantly overlapped with those predicted by DIVA_EEG. In conjunction with other recent model extensions, DIVA_EEG lays the foundations for constructing a complete neurocomputational framework to tackle vocal and speech disorders, which can guide model-driven personalized interventions.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Appl Sci (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Chile Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Appl Sci (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Chile Pais de publicación: Suiza