This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The focus of this proposal is to explore the mechanisms of action underlying motor learning. Current neuroimaging studies investigate mechanisms of action of 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. 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. Imaging studies will be performed to map task-performance strategy (measured as regional neural activity of task performance), information flow (measured as effective inter-regional connectivity during task performance), synaptic weighting (measured as task-independent effective inter-regional connectivity during the resting state), and changes in these measures before and after motor training. Task-performance strategy will be determined using functional magnetic resonance imaging (fMRI). Task-independent connectivity will be measured with concurrent transcranial magnetic stimulation/positron emission tomography (TMS/PET) and with resting-state fMRI. Structural Equation Modeling, using anatomical constraints individually defined by the TMS/PET and resting-state fMRI measurements, will be performed to investigate the effective inter-regional connectivity during task performance. Synaptic weighting measurements will be performed on the resting-state fMRI data using SEM.
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