We identify animal behaviors and abilities that exemplify the computational challenges faced by the brains of many species, including humans.
We engineer controlled behavioral tasks in the lab that distill down and retain the core computational principles of natural behavior (i.e. “behavior clamp”).
We use electrical, optical and pharmacological techniques to monitor and manipulate the activity of networks, neurons and synapses to identify the neural circuit elements important for a behavior.
Finally, we circle back to the natural behaviors upon which our engineered behaviors were modeled to understand brain function in natural environments.
Our research aims to understand how sensory, motor, and learning systems converge to make predictions about the future.
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.
By studying brain activity and connectivity as animals engage in natural behaviors and virtual reality, we aim to understand how the brain stores memories about the past and makes predictions about the future.