Determining the neuronal architecture underlying certain visual functions is of fundamental importance for understanding how sensory processing is implemented in the brain. The wealth of anatomical, physiological and biophysical data that is being currently acquired on the neocortex could be used to constrain its functional architecture. However, given the intrinsic complexity and diversity of the data, it is difficult to provide a comprehensive framework to use these data in order to characterize structure-function relationships. Here, we discuss the use of biophysically plausible models of dynamics of neuronal networks, constructed to reflect the known properties of neocortical connectivity and modularity, as a tool to bring together anatomy and physiology. We illustrate the utility and rationale of the neuro-dynamics modelling approach by considering recent studies on the relationship between functional structure of the visual cortex and its response timing, and on the cellular and network origin of neuronal oscillations in the gamma frequency range. We also critically discuss how an interaction between theory and experiments could help this approach to become directly relevant for clinical applications.