Symptom network analysis is now commonly used in psychopathology research. Network analysis results in networks with symptoms represented as nodes, while edges represent conditional associations between these. Direct causal relations between symptoms will produce nonzero conditional associations, but these associations can also be produced in other ways. In this chapter, Borsboom discusses six plausible mechanisms that could produce edges in symptom networks. The first is resource competition, where the presence of a symptom depletes resources, which causes another symptom to arise. The second is evidential overlap, in which judgments central to different symptoms involve a subjective assessment of the same evidence. The third is shared mechanisms, in which symptomatology involves processes that are shared among different symptoms. The fourth are consistency drives, which arise when individuals are prone to align their cognitions, affect states, and behavior. The fifth are statistical processes involved in research design and analysis (marginalization and conditioning). The sixth is the presence of unobserved common causes that affect multiple symptoms at the same time. The author argues that, in realistic situations, the mechanisms in question are not mutually exclusive, which preempts standard scientific approaches that pit one model against another to derive critically divergent predictions. Instead, making sense of symptom networks will require more advanced theory development and modeling.