behavior, models, & neural data
We believe behavior is an essential component to understanding neural function. As part of our quest to better understand behavior, we develop new tools to study more complex and natural movements. We develop tools, like DeepLabCut, to perform markerless pose estimation and behavioral analysis from any species in a multitude of settings. We also have developed a set of skilled motor tasks where mice can learn from a dynamically changing sensory landscape.
By combining concepts from machine learning and optimal motor control with the power of the mouse's genetics and accessibility, our lab aims to uncover fundamental principles that guide motor adaptation, learning, and motor control.
We are using the latest techniques in 2-photon and deep brain imaging (including utilizing multi-area imaging with a 2-photon mesoscope), to uncover the neural correlates of adaptive behavior. We use optogenetics and chemogenetics to test what roles diverse areas have during behavior. Furthermore, we develop new computational models and tools to generate testable hypotheses and analyze our data.