Neural Systems and Machine Learning Lab

We are an interdisciplinary team that focuses on understanding how distributed neural circuits give rise to coordinated behaviors and perceptions. We take a multi-pronged approach to this problem by developing novel theoretical frameworks for neural circuit function, conducting in vivo neuroscience experiments, and developing state of the art machine learning tools to address diverse systems biology questions.

• On the neuroscience side, we investigate functional organization and dynamic coordination in the brain by combining in vivo multi-scale electrophysiology and optogenetics in rodents. This multi-modal, multi-scale approach provides the simultaneous breadth of coverage and spatio-temporal resolution required to determine neural computations at the speed of thought.
• On the computational side, we aim to reveal the processes that generate complex (neuro-) biological data by combining ideas from control theory, information theory, high-dimensional statistical learning, statistical mechanics, and modern deep learning to develop novel methods and apply them to general biological and neuroscience problems.