Distinct roles in motor sequence learning for cortico-basal ganglia circuits - PROJECT SUMMARY The ability to seamlessly link individual movements into smooth, efficient sequences is a fundamental aspect of human behavior, enabling everything from speaking to playing musical instruments. This process often feels effortless, yet it relies on complex interactions between different brain regions. When these interactions break down, as seen in movement disorders such as Parkinson’s disease, the ability to learn and execute motor sequences can become severely impaired. The basal ganglia (BG), a set of deep brain structures, is thought to play a key role in this process, but its precise contribution to learning and performance of motor sequences remains unclear. Some prominent theories suggest that the BG store and select well-learned skills, while emerging evidence instead indicates that they act as a tutor, shaping skill learning in the cortex but becoming unnecessary once a skill is well-learned. My project will test these competing ideas by examining how different BG circuits support different stages of motor learning. Using high-density Neuropixel probes, I will record activity from three key cortical regions involved in movement planning and execution—primary motor cortex (M1), supplementary motor area (SMA), and pre-supplementary motor area (pre-SMA)—as well as their anatomically-connected regions in the BG output nucleus, the internal segment of the globus pallidus (GPi). By comparing neural activity during both early learning and well-practiced sequence execution, I will determine how these circuits encode motor sequences over the course of learning at the level of both single-units and neural populations (Aim 1). To test whether these circuits are necessary for learning and recall, I will use pharmacological inactivation with the GABA-A agonist muscimol followed by permanent lesions to disrupt GPi output at different learning stages (Aim 2). This approach will reveal whether the BG is required for learning and performing new sequences but not for executing highly practiced ones, providing insight into how BG circuits interact to shape motor skill acquisition. This fellowship will provide rigorous technical training in multi- area electrophysiology, pharmacological inactivation, and computational analysis of population-level neural data. I will conduct this work within the Systems Neuroscience Institute at the University of Pittsburgh, which offers a uniquely collaborative environment with extensive expertise in nonhuman primate neuroscience. Professional development in mentorship, scientific communication, and leadership will complement my technical training. Together, this research and training plan will prepare me to lead an independent research program focused on the neural basis of skilled behavior.
