**Faculty Candidate - Systems Neuroscience**

We constantly make predictions, ranging from whether it will rain today to who will be the next president. But some of the most important predictions that we make are much less obvious, such as what my voice will sound like when I speak or what the next note will sound like when I strike a key on the piano. This ability to predict the acoustic consequences of our actions is vital for learning and maintaining complex behaviors such as speech. More fundamentally, without this ability, we would be surprised by every sound we made. Yet we understand remarkably little about how the brain learns, stores and recalls statistical associations about the world that are important for making predictions. To address this question, I combine electrophysiology, circuit tracing, calcium imaging, and optogenetics to study neural circuit function in mice engaged in virtual reality and natural behaviors. Using this experimental platform, I have identified a cortical circuit that integrates sensory signals with ongoing behavioral plans to predict and suppress neural responses to self-generated sounds. These findings form the basis for a research program aimed at understanding how the brain learns and stores statistical regularities about the world and uses this information to guide behavior.