Topology of high-degree and high-strength hubs in the resting-state and speech-production networks in healthy subjects.
Speech production is one of the most complex and rapid motor behaviors that are uniquely human. The development of our ability to speak relies on the abilities to listen to speech, comprehend and process the meaning of the heard words, and precisely coordinate the function of more than 100 laryngeal, orofacial and respiratory muscles in order to utter speech sounds. Neural correlates of speech production have been explored for over a century. However, a number of questions remain unanswered about its structure and function in both healthy humans and patients with neurological voice and speech disorders. Our research focuses on the organization of functional brain networks during speech production, the temporal characteristics of the laryngeal motor cortical activity, and how different neurotransmitters (e.g., dopamine, GABA) influence and modulate the brain networks during voice and speech production.
Starting with the Hodgkin-Huxley model in the 1950s, the fundamental concept of computational neuroscience has always been to understand the theoretical mechanisms of information processing in the human brain. The exponential growth of computing power in recent years allowed detailed simulations of brain activity using large-scale neural models. We are developing multi-compartment neural population models based on detailed neurophysiological considerations using our experimental data. Through neural modeling we are targeting the unanswered questions about the functional networks and neurotransmitter function in speech control, which are difficult to address experimentally due to either invasiveness of applied methods or technical challenges. One example of these studies is to determine the extent of dopaminergic influence on the well-known lateralization of functional and structural brain networks controlling speech production.