With National Science Foundation support, Dr. Xiong will develop imaging and modeling strategies to study mechanisms underlying adaptive changes of the human brain. The focus of this proposal is to explore the mechanisms underlying motor learning. Learning-induced neural plasticity and functional reorganization are well-established and well-documented, but not well-understood. Current neuroimaging studies investigate neural mechanisms underlying learning by exploring the changes in regional neural activity and inter-regional activity of task-performance. Little effort has been given to studying the more fundamental changes of neural connections and synaptic weighting. On the technical front, human functional imaging research sorely needs more rigorous approaches, as can be provided by mathematical modeling. A modeling framework - Structural Equation Modeling - is now accepted as appropriate for human imaging data. Structural equation modeling however, is currently performed with anatomical constraints based on neuroanatomical studies in non-human species. The performance of structural equation modeling might be greatly enhanced if anatomical constraints are individually optimized using the same subject's task-independent anatomical connectivity data. To date, this strategy has not been reported by any laboratory. The present proposal seeks to develop system-level modeling strategies for neuroimaging and to apply these novel strategies to mechanisms of action of motor learning. The overall goal of this proposal will be accomplished through the following four goals. First, developing and optimizing imaging strategies for detecting anatomical connectivity for each individual subject. Second, developing a structural equation modeling strategy by incorporating individual anatomical constraints to enhance those models' performance. Third, investigating changes in regional neural activity and inter-regional activity of task-performance induced by motor learning using the enhanced modeling strategy. Fourth, investigating synaptic plasticity by applying the enhanced modeling and demonstrating that synaptic plasticity is an underlying mechanism of action of motor learning. When completed, this research project will increase the understanding of mechanisms of adaptive learning and has the potential of defining a new strategy by which functional imaging can be applied to study mechanisms of action and disease pathophysiology.
