Systems Neuroscience Lab

Our lab investigates how cortical circuits interact to form transformation-invariant object representations that can guide behavior. Natural environment contains large number of objects with overlapping sensory input, and our brain is capable of using information from different sensory modalities to extract their identities with ease. Yet, despite extensive research in the last few decades, we are still far from having a complete understanding of how the brain creates untangled object representations. If we understood how cortex achieves this extraordinary ability at the algorithmic level, this would represent a significant advance in our understanding of brain computation in general. To address this question, we combine advanced imaging techniques for recording neural activity with high-throughput behavioral training and computational modeling to understand the algorithm used by the mouse visual cortex to extract relevant features from complex environments and guide natural behaviors.