In recent years it has become possible to differentiate separable aspects of attention and to characterize the anatomical structure and dynamic states of their underlying networks. When individual differences in the structure and dynamics of these networks are used as dependent measures in associations with individual genetic variation, it becomes possible to assign cellular and molecular changes that occur over the course of normal development to specific aspects of network structure and function. In this way, a more granular understanding of the physiology of neural networks can be obtained. Here we review a translational research strategy focused on how genetic variation contributes to the normal development of attentional function. We seek to use genetic information to help construct a multinode, multinetwork model that can explain, in part, individual differences in the development of attention over the course of development.