dc.description.abstract | “Speech production” is an extremely complex action. In addition to the coordination of articulators, the transmission of neural signals and control of articulators are also important. With the advent of functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), the neural correlation between brain and speech has gradually been uncovered. Apart from the control function of cortical areas, the influence of subcortical areas on speech has received more and more attention. However, the research methods on the basal ganglia (BG) is still limited, and there are no effective treatments for many speech disorders so far. Therefore, the purpose of this study is to investigate the correlation between basal ganglia and speech production. By simulating the process of the basal ganglia participating in speech production with a computational model, we predict the possible motor speech disorders from simulation results under abnormal conditions. Finally, we combined our model with the articulation model previously studied in our laboratory to find out effective ways for speech therapy.
GODIVA (Gradient Order Direction Into Velocities Articulator), a neural network based model, simulated the left inferior frontal sulcus, the pre-supplementary motor area, the frontal operculum and the caudate nucleus circuits to generate brain signals used in speech production in this study. Our approach was to add new blocks such as the supplementary motor area and the putamen nucleus circuits to the model and then simulate the process of speech production in three different conditions. After that, we compared simulation results with the original GODIVA model. In normal condition, even though passing through caudate nucleus circuit causes a delay with the first syllable at about 100 milliseconds compared to the original GODIVA model, the accuracy of the simulation results could be significantly improved. It suggests that the basal ganglia have control ability for sequential speech tasks. In another condition, abnormal level of dopamine would affect the activity of dopamine receptor D1 and D2. D1 would cause delays in all syllables, but the delays of syllables would be different. D2 would decrease the intensity of the syllable switching activity, causing delays to the switch point of syllable. In the last condition, white matter fiber impairments would also reduce the intensity of the activity so that the syllable could not be changed to the next one. The above-mentioned abnormal conditions suggest that the impairment of basal ganglia would lead to motor speech disorders. The major source of the disorder is not always originated from a single factor, but may also from the results of multiple factors.
Finally, we combined the GODIVA model with the DIVA model previously developed in our laboratory with Chinese tones to build the function that the GODIVA model transmits brain signal instruction to control DIVA model for producing speech sound. In this way, we could find out the correlation between brain and motor speech disorder. Unfortunately, due to the limit of number of control parameters used in the GODIVA model and integrity of vocal tract used in DIVA model, the model only can simulate vowels and some consonants, and produce stuttered-like repeated sounds. In future studies, we hope more factors could be considered such as the indirect pathway of caudate nucleus circuit, so the model could simulate other motor speech disorder such as aphasia. Besides, the vocal tract shape of the DIVA model could be modified to accurately simulate all syllables. | en_US |