We believe science should be driven by good questions. Once the right question has been identified and our curiosity sparked, we use whatever tools the question requires, build new ones when we can, and collaborate with others to push the science forward.
Our papers use: neurophysiology, neuropharmacology, optogenetics, chemogenetics, sonogenetics (ultrasound with viral gene delivery), and computational approaches including reinforcement learning, deep learning, spiking neural networks, and econometric modeling.
We also love designing sophisticated learning, economic, and perceptual paradigms to test our theories in human and animal behavior and in computational agents. In our view, behavior and theory are as important for establishing causality as perturbing circuits or discovering molecular pathways, and real insight requires combining across all of these levels.