Neural systems integration

A need is identified to build models of the central nervous system that are semi-complete, applied within multiple contexts to multiple tasks, using methodologies that span multiple levels of abstraction. The issues and constraints in building such models are discussed with respect to completeness, validation, cost, scalability and robustness. An approach currently being explored is described that is suited to the creation of large heterogenous models by small independently collaborating research groups. It is based on a network model interface, a software wrapper that abstracts the interaction between a generic component and a generic framework.