Exploring the Subthalamic Nucleus Role in Variability Regulation - PROJECT SUMMARY. Though behavioral variability is often considered to have deleterious effects on performance, it is critical for identifying new solutions to learn new behaviors and adapt old ones. However, the mechanisms underlying transitions between high and low states of behavioral variability and the generation of adaptive variability are yet to be fully understood. Notably, the basal ganglia have been implicated in this regulation, with the Dorsomedial Striatum (DMS) promoting exploratory, variable behavior, while the Dorsolateral Striatum (DLS) drives stereotyped actions. Imbalances between DMS and DLS activity can be found across numerous disorders such as autism, substance use disorders, and obsessive-compulsive disorder. This imbalance results in invariable and disruptive behavioral patterns with limited therapeutic approaches. However, the neural circuits and mechanisms through which the DMS-DLS balance and thus behavioral variability is regulated are yet to be fully understood. Motor skill learning provides rich and continuous readouts of behavioral variability, making it a great model to study the neural circuits that regulate DMS-DLS mediated variability. Consistent with clinical and basic scientific findings, our preliminary experiments suggest that the Subthalamic Nucleus (STN) is involved in behavioral variability regulation. We identified novel projections from the STN to the DMS via the Anterior Thalamic Nuclei that promote variability during motor skill learning. This finding leads to our hypothesis that the STN→ATN→DMS pathway regulates motor variability. Given that behavioral variability is not only important for de novo learning but also for adaptation upon changes in task conditions, we will test if this pathway promotes variability to adapt learned motor behaviors in Aim 1. In Aim 2, we will test the synaptic mechanisms which underlie the contributions of this pathway to transitions between high and low states of variability during motor skill learning. To address these aims, we will combine viral circuit silencing, complex behavioral training paradigms, machine learning-based behavioral quantification and whole-cell patch clamp electrophysiology. Successful completion of this proposal will improve our understanding of the regulation of the DMS-DLS balance and of the resulting behavioral variability, not only in motor skill learning, but across various behaviors. Importantly, DMS-DLS balance and variability regulation are a critical aspect of learning and behavior and are severely impaired in a myriad of neurological and neuropsychiatric disorders. Furthermore, our results will provide insights into novel roles of the STN and into the basal ganglia at large. Finally, this innovative proposal provides substantial conceptual and technical training opportunities for the PI to build a strong background in scientific experimentation and data-analysis to fuel the path toward research independence. .
