Speech motor control in relation to phonology : neurocomputational modeling of disordered development

The production of speech constitutes one of the most complex skills that humans perform. It takes years to acquire the pragmatic, linguistic, and perceptual-motor knowledge and skills that are necessary for the effortless production (and perception) of fluent speech. Although most children come through successfully, children with speech sound disorders (SSD) keep struggling at the stage where they want to produce meaningful speech. The differential diagnosis of SSD and its subtypes, in particular Childhood Apraxia of Speech (CAS) constitutes one of the main questions in the field of language- and speech pathology. CAS is defined as a neuromotor speech disorder but is considered a controversial clinical entity, with respect to both clinical signs and underlying neuromotor deficit. This dissertation follows a modeling approach in which a computational neural model of speech acquisition and production is utilized in order to find the neuromotor deficits that underlie the diversity of phonological and speech-motor symptoms of CAS. First, specific hypotheses about the underlying deficits were generated based on behavioral data. These hypotheses were then tested in a series of computer simulations, and the resulting speech patterns were compared to behavioral data. Finally, the model was used to derive further predictions that can be tested empirically in behavioral experiments and possible new approaches for clinical intervention. In clinical practice, the treatment of developmental speech disorders requires an approach of individual profile analysis. The findings reported in this dissertation provide valuable insights into the cognitive and neurological processes involved and provide a more stable theoretical basis to put this into practice.