Neuronal systems can be described by their transfer functions, which can be represented by a Volterra series expansion. While the high level of abstraction which characterizes this representation enables a global description, it is problematic, to some extent, in the context of linking the formal representation of the system to its actual structure. The formal representation is unique, yet there are multiple physical realizations of this representation. Separating the system's output into its logical components (linear, cross-linear, and self nonlinear, in this study), and inspecting the relative contribution of these components, might provide a key towards a linkage between the formal and actual representations. Based on results drawn from identification of MGB cells of the squirrel monkey, it is shown that the relative contributions can be described in neurobiological terms such as excitation and inhibition and thus be attributed to actual sybsystems.