Youth antisocial behavior (AB) is associated with deficits in socioemotional processing, reward processing and threat detection, and executive functioning. These deficits are thought to emerge from differences in neural functioning, particularly within brain regions associated with the default, salience, and frontoparietal networks, respectively. Although a growing literature has linked these deficits to abnormalities in the structure, functioning, and connectivity of specific regions within these networks, recent advances in graph analysis provide a novel means of investigating the overall organization, or topology, of entire neural networks. However, no research has yet used graph metrics to examined whether youth AB is associated with alterations in the topologies of specific neural networks. The current study addresses this gap by applying unweighted, undirected graph analyses to resting-state fMRI data collected from an adolescent sample in the community at higher risk for AB due to urbancity and exposure to poverty-related adversity. This talk will discuss findings related to the relationship between youth AB and neural network topology, as well as provide an overview on some ways in which we can apply graph analysis to advance our understanding of the overall architecture of the brain across development.