We aim to provide an understanding of higher-order cognitive functions, focusing on perception, learning, inference, and decision making, with an integrated approach that bridges across scales, from molecules to neurons, large populations of neurons, cortical and cortical-subcortical circuits, complex cognitive processes and behavior, using computational modeling.

Our computational approach ranges from abstract models of the quantities that ought to be computed by the brain (e.g. predictions in a task), to algorithmic descriptions of these models and the mapping of their constituents onto brain structures and brain dynamics, to the neural code of internal representations.