  To learn how cognition is implemented in the brain, we must build
computational models that can perform cognitive tasks, and test such models
with brain and behavioral experiments. Cognitive science has developed
computational models of human cognition, decomposing task performance into
computational components. However, its algorithms still fall short of human
intelligence and are not grounded in neurobiology. Computational neuroscience
has investigated how interacting neurons can implement component functions of
brain computation. However, it has yet to explain how those components interact
to explain human cognition and behavior. Modern technologies enable us to
measure and manipulate brain activity in unprecedentedly rich ways in animals
and humans. However, experiments will yield theoretical insight only when
employed to test brain-computational models. It is time to assemble the pieces
of the puzzle of brain computation. Here we review recent work in the
intersection of cognitive science, computational neuroscience, and artificial
intelligence. Computational models that mimic brain information processing
during perceptual, cognitive, and control tasks are beginning to be developed
and tested with brain and behavioral data.
