DIVA Meets EEG: Model Validation Using Formant-Shift Reflex

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.

Childhood Apraxia of Speech: A Descriptive and Prescriptive Model of Assessment and Diagnosis

“…The DIVA/GODIVA neurocomputational framework provides a comprehensive model for understanding the apraxia of speech. DIVA_EEG, an extension of DIVA, incorporates electroencephalography to enhance the model’s physiological validation [ 24 ]. The GODIVA model, an extension of DIVA, focuses on learning individual sounds and chunking frequently produced phoneme sequences, crucial to speech motor control development in infants [ 25 ].…”