This description should include at least interconnectivity between subsystems, neuron response functions, neuron tuning curves, subsystem functional relations, and overall system behavior. Next, we express the functional description in mathematical terms. In particular, the relevant mathematical variables should be specified in such a way that they can be used to write mathematical transformations that describe the previously specified functions. The goal here is to translate the functional description provided in neurobiological terms into a description in mathematical terms. The second step of the methodology consists in precisely specifing the real-world limitations on that are known or assumed for the neural system of interest.
Implementational constraints are of paramount importance when modeling neurobiological systems.
This second step in the methodology helps make these constraints central to generating a good model. Similarly, the temporal characterisitics, such as bandwidth and power spectrum, must be specified. All such specifications should be made on the basis of available data, if possible. Together, these specifications will clearly define the real-world operating constraints that the system must satisfy in order to successfully perform its function. Not surprisingly, these specifications can significantly affect the final model that is generated.