Determining the Relevance of Prediction Errors to Auditory-Motor Adaptation

In this study, I used two computational models (state-space model and simple DIVA model) to determine the speech motor system’s sensitivity to auditory errors that are relevant vs. irrelevant and introduced gradually or suddenly. I applied formant perturbations (first and second formants of /ɛ/ were shifted toward formants of /æ/) to generate auditory errors. Then I measured subjects’ adaptive responses to the formant perturbations. I examined (a) the accuracy of models in explaining the adaptive responses (b) the relationship between the models’ parameters and the adaptive responses. My results showed that both models predict the adaptive responses to errors. However, the models’ parameters differently correlated with the adaptive responses, suggesting that while the models perform similarly, they provide different insights about adaptive responses to auditory errors. These results have important implications for speech motor learning and production models and shed light on neural processes involved in generating adaptive responses.