Neuroimaging studies using positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) have revealed the involvement of distributed brain regions in memory processes mainly by the use of subtraction strategy based data analyses. Covariance analysis based data analysis strategies have been introduced more recently which allow functional interactions between brain regions of a neuronal network to be assessed. This contribution focuses on studies aiming to (1) establish the functional topography of episodic and working memory processes in young and old normal volunteers, (2) to assess functional interactions between modules of networks of brain regions by means of covariance based analyses and systems level modelling, (3) to characterise the temporal dynamics by the use of magnetoencephalography (MEG) and (4) to relate neuroimaging data to the underpinning neural networks. Male normal young and old volunteers without neurological or psychiatric illness participated in neuroimaging studies (PET, fMRI, MEG). Studies were approved by the ethical committee and federal authorities. Our results in young volunteers show distributed brain areas that are involved in memory processes (episodic and working memory) and show much of an overlap with respect to the network components. Systems level modelling analyses support the hypothesis of bihemispheric, asymmetric networks subserving memory processes and revealed both similarities in general and differences in the interactions between brain regions during episodic encoding and retrieval as well as working memory. Changes in memory function with ageing are evident from functional topographic studies in old volunteers activating more brain regions as compared to young volunteers. There are more and stronger influences of prefrontal regions in elderly volunteers comparing the functional models between old and young subjects. We discuss the way that the systems level models of the PET and fMRI results have implications for the underlying neural network functioning of the brain. This is done by developing simplifying assumptions, which lead from the equations describing the activities of the coupled neural modules to the systems level model equations. The resulting implications for the neural interactions are then discussed, in terms of a set of synaptically coupled neural modules. Finally, we consider how a similar analysis could be extended from the spatial to the temporal domain thus including the EEG and MEG results. The implication of preliminary MEG results presented here for the temporality arising in the interaction between the coupled neural modules in a working memory paradigm is discussed in terms of the previously developed neural network models arising from the PET and fMRI data.