Neuroinformatics “combines neuroscience and the information sciences to develop and apply advanced tools for a major advancement in understanding the structure and function of the brain.” After introducing the speaker’s neuroinformatics research group, we will address issues related to the use and misuse of independent component analysis. Departing from the traditionally simple evoked response paradigm, into the more natural neurocinematics one, also the neuronal responses are expected to take on rather complex network configurations. We will review two approaches to identify such communication strategies. In a functional magnetic resonance imaging setup, the first one is a hierarchical method, and assumes the existence of basic focal activation areas, which are combined to account for the complex neuronal responses. Additional information is gathered directly from the stimuli. The second uses phase synchrony as the acting principle for the extraction of communication/control in high temporal resolution data, such as electro- and magnetoencephalograms.