Abstract: Human electroencephalograph (EEG) data driven animation is often used in neurofeedback systems for concentration training in children and adults. Visualization of the time-series data could be used in neurofeedback and for the data analysis. The paper proposes a novel method of 3D mapping of EEG data and describes visualization system VisBrain that was developed for EEG data analysis. We employed a concept of a dynamic 3D volumetric shape for showing how the electrical signal changes through time. For the shape, a time-dependent solid blobby object was used. This object is defined using implicit functions. Besides just a visual comparison, we propose to apply set-theoretic ("Boolean") operations to the moving shapes to isolate activities common for both of them per time point, as well as those that are unique for either one. The advantages of the method are demonstrated with real EEG experiments examples. New emerging applications of EEG data driven animation in e-learning, games, entertainment, and medical applications are discussed.