In the mammalian brain, learning and behavior are carried out by cortical circuits composed of diverse neuronal cell types. The distinct gene expression patterns of cell types define their role in the circuit. Determining how cell types are organized into cortical circuit motifs provides an understanding for how neural computations are implemented to give rise to learning and behavior. By extension, genetic variation across an animal population can potentially alter cell type properties. These functional differences may result in individual variability in learning and behavior. My research program seeks to identify common principles of cortical circuit function and how they vary across individuals. I will present recently developed vertically-integrated methods that enable simultaneous behavioral, functional, anatomical, and molecular measurements to be performed on individual mice. I will describe the application of these methods to dissect parahippocampal circuits involved in perception and abstract sensory learning. In addition, I will present new efforts to survey the genetic correlates of individual learning by performing large-scale, automated task training on recombinant outbred mice. These complementary efforts will reveal how the nervous system serves as a link between our genome and our phenome.