Hybrid modeling in computational neuropsychiatry.

The aim of building mathematical models is to provide a formal structure to explain the behaviour of a whole in terms of its parts. In the particular case of neuropsychiatry, the available information upon which models are to be built is distributed over several fields of expertise. Molecular and cellular biologists, physiologists and clinicians all hold valuable information about the system which has to be distilled into a unified view. Furthermore, modelling is not a sequential process in which the roles of field and modelling experts are separated. Model building is done through iterations in which all the parts have to keep an active role. This work presents some modelling techniques and guidelines on how they can be combined in order to simplify modelling efforts in neuropsychiatry. The proposed approach involves two well known modelling techniques, Petri nets and Biochemical System Theory that provide a general well proven structured definition for biological models.