A variety of approaches are available for using computational models to help understand neural processes over many levels of description, from sub-cellular processes to behavior. Alongside purely deductive bottom-up or top-down modeling, a systems design strategy has the advantage of providing a clear goal for the behavior of a complex model. The order in which biological details are added is dictated by functional requirements in terms of the tasks that the model should perform. Ideas from engineering can be mixed with those from biology to build systems in which some constituents are modeled in detail using biologically-realistic components, while others are implemented directly in software. This allows the areas of most interest to be studied within the context of a behaving system in which each component is constrained both by the biology it is intended to represent as well as the task it is required to perform within the system. The Catacomb2 modeling package has been developed to allow rapid and flexible design and study of complex multi-level systems ranging in scale from ion channels to whole animal behavior. The methodology, internal architecture, and capabilities of the system are described. Its use is illustrated by a modeling case study in which hypotheses about how parahippocampal and hippocampal structures may be involved in spatial navigation tasks are implemented in a model of a virtual rat navigating through a virtual environment in search of a food reward. The model incorporates theta oscillations to separate encoding from retrieval and yields testable predictions about the phase relations of spiking activity to theta oscillations in different parts of the hippocampal formation at various stages of the behavioral task.