Learning control and computational models of human motor systems. With the aim of understanding how humans learn their body movements, this project addresses fundamental cross-disciplinary issues of learning control, robotics and computational models of human motor systems. The results will lead to improvements in smart industrial automation and the development of more effective rehabilitation stategies.
The structure and function of the human spinal connectome. This project will use complex network analysis to map the interactions between the brain and body, to understand how the central nervous system controls our movements. The project will provide fundamental insights into mechanisms that coordinate activity in the human motor system, and how the breakdown of coordination may lead to movement disorders. By integrating advanced computational analyses with state-of-the-art recording techniques ....The structure and function of the human spinal connectome. This project will use complex network analysis to map the interactions between the brain and body, to understand how the central nervous system controls our movements. The project will provide fundamental insights into mechanisms that coordinate activity in the human motor system, and how the breakdown of coordination may lead to movement disorders. By integrating advanced computational analyses with state-of-the-art recording techniques, the project will generate new knowledge of the neural basis of human motor coordination. Expected outcomes may support future applications to restore motor function through brain stimulation, prosthetics and robotics design.Read moreRead less
Platform technology to decode motor control through ultra high-field MRI. This project aims to advance our understanding of the poorly understood neural circuits that enable fine motor control in humans. To obtain this knowledge, new platform technology will be developed to capture the full kinematics of the hand during concurrent functional magnetic resonance imaging at ultra high-field. This device will allow testing of fundamental theories describing the canonical microcircuits involved in ha ....Platform technology to decode motor control through ultra high-field MRI. This project aims to advance our understanding of the poorly understood neural circuits that enable fine motor control in humans. To obtain this knowledge, new platform technology will be developed to capture the full kinematics of the hand during concurrent functional magnetic resonance imaging at ultra high-field. This device will allow testing of fundamental theories describing the canonical microcircuits involved in hand motion. Expected outcomes include new evidence of mirror neurons and observation of predictive error signals in the motor cortex. This new knowledge paves the way towards improved computer-brain interface technology which is likely to create benefits through translation to applications such as artificial limb control.Read moreRead less
Developmental trajectory of tongue control for speech with real-time MRI. This project aims to evaluate the developmental trajectory of tongue control during speech, relating dynamic 3D vocal tract modelling to the acoustic signal. By optimising real-time MRI technology to capture and model articulatory movements, the project expects to accelerate understanding of how tongue control for speech is developed, mastered, and perturbed by factors such as rapid growth and foreign accent. Expected outc ....Developmental trajectory of tongue control for speech with real-time MRI. This project aims to evaluate the developmental trajectory of tongue control during speech, relating dynamic 3D vocal tract modelling to the acoustic signal. By optimising real-time MRI technology to capture and model articulatory movements, the project expects to accelerate understanding of how tongue control for speech is developed, mastered, and perturbed by factors such as rapid growth and foreign accent. Expected outcome is a new understanding of how different speakers' vocal tracts change and how speech is reshaped, informed by real physiological data. Significant benefits will be realised through refined methods and theory development for diverse fields e.g. linguistics, speech science, and automatic speech recognition/synthesis. Read moreRead less