From Exploration to Expertise: Mechanisms of Motor Learning in Cortico-Basal Ganglia Circuits

/Abstract Research Project: The ability to learn new behaviors, or movements to achieve a goal, is fundamental to all animals. This ability largely relies on trial-and-error, or reinforcement, learning, in which different behaviors are attempted and reinforced if successful. Although the core concept of reinforcement learning is relatively simple, the neural computations supporting it are remarkably complex. Neural circuits must purposely generate high behavioral variability during early learning to explore candidate solutions, drawing on prior knowledge to efficiently “guess” which behaviors to try. As successful behaviors are learned, circuits must then store the solutions without overwriting instructions for behaviors used in other tasks. In the motor domain, these processes are widely believed to depend on cortico-basal ganglia (BG) circuitry. Yet, the specific mechanisms by which it accomplishes these operations for motor learning remain poorly understood. How do the BG leverage prior knowledge (i.e. previously learned behaviors) to generate and constrain motor variability for the purposes of learning new behaviors? How does the circuit modify synaptic weights for new skills while preserving prior learning? Progress on these questions has been hindered by the lack of methodologies to probe and track neural activity over long timescales of learning while simultaneously tracking evolving motor outputs, as well as a lack of candidate models with the power to link neural data with putative mechanisms. However, recent advances in theory and experimental techniques can now overcome these challenges. These include machine vision-based methods to track 3D behavior, techniques for monitoring neural activity over long learning timescales, and optogenetics to test key mechanisms. Using these tools, the proposed research will view these questions through the lens of two critical nodes of the cortico-BG circuit: dorsolateral striatum (DLS), the input nucleus of the motor BG, and its main input, the motor cortex (MC). This will involve using optogenetics to test hypotheses regarding how MC-DLS interactions generate motor variability (Aim 1) and using models and long-term recording to investigate how DLS stores the neural instructions for task-specific movements without overwriting existing ones (Aim 2). Techniques and insights from these aims will then fuel an investigation for how MC may store prior experience and leverage it to expedite learning on future tasks by constraining the activity of downstream structures (Aim 3). These studies will provide crucial insight into how neural circuits balance flexibility for learning with robustness in execution and illuminate principles driving adaptive behavior. Crucially, this work will also shed light on how BG dysfunction in disorders such as Parkinson’s and Huntington’s Disease result in such profound motor learning deficits. The proposed research will be conducted in the Ölveczky Lab at Harvard, which provides an excellent scientific and training environment, and under the guidance of an expert team of mentors and collaborators to advise experimental and computational aspects and professional skills. Together, this will propel the candidate towards her goal of launching a career as an independent researcher. Project Number: 1K99NS146555-01 | Fiscal Year: 2026 | NIH Institute/Center: National Institute of Neurological Disorders and Stroke (NINDS) | Principal Investigator: Kiah Hardcastle | Institution: HARVARD UNIVERSITY, CAMBRIDGE, MA | Award Amount: $120,582 | Activity Code: K99 | Study Section: Special Emphasis Panel[ZRG1 CN-J (90)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11283097