Computational cognitive neuroscience of natural scene perception

The goal of our work is to understand how the fundamental cognitive functions of natural scene perception are implemented in the computations of the human brain. Specifically, our research seeks to reverse engineer the representations and algorithms of human visual cognition through neuroimaging, computational modeling, and behavioral experiments. Our work relies heavily on deep artificial neural networks as theoretical models of information processing in the human brain, and we broadly make use of large-scale computational methods to characterize how the human visual system makes sense of real-world visual scenes.