Eichelbaum, SebastianWiebel, AlexanderHlawitschka, MarioAnwander, AlfredKnösche, ThomasScheuermann, GerikReinhard Koch and Andreas Kolb and Christof Rezk-Salama2014-02-012014-02-012010978-3-905673-79-1https://doi.org/10.2312/PE/VMV/VMV10/155-162Diffusion tensor images and higher-order diffusion images are the foundation for neuroscience researchers who are trying to gain insight into the connectome, the wiring scheme of the brain. Although modern imaging devices allow even more detailed anatomical measurements, these pure anatomical connections are not sufficient for understanding how the brain processes external stimuli. Anatomical connections constraint the causal influences between several areas of the brain, as they mediate causal influence between them. Therefore, neuroscientists developed models to represent the causal coherence between several pre-defined areas of the brain, which has been measured using fMRI, MEG, or EEG. The dynamic causal modeling (DCM) technique is one of these models and has been improved to use anatomical connection as informed priors to build the effective connectivity model. In this paper, we present a visualization method allowing neuroscientists to perceive both, the effective connectivity and the underlying anatomical connectivity in an intuitive way at the same time. The metaphor of moving information packages is used to show the relative intensity of information transfer inside the brain using a GPU based animation technique. We provide an interactive way to selectively view one or multiple effective connections while conceiving their anatomical connectivity. Additional anatomical context is supplied to give further orientation cues.Categories and Subject Descriptors (according to ACM CCS): Computer Graphics [I.3.3]: Display algorithms- Computer Graphics [I.3.7]: Animation