After decades of independent morphological and functional brain research, a key point in neuroscience nowadays is to understand the combined relationships between the structure of the brain and its components and their dynamics on multiple scales, ranging from circuits of neurons at micro or mesoscale to brain regions at macroscale. With such a goal in mind, there is a vast amount of research focusing on modeling and simulating activity within neuronal structures, and these simulations generate large and complex datasets which have to be analyzed in order to gain the desired insight. In such context, this paper presents ViSimpl, which integrates a set of visualization and interaction tools that provide a semantic view of brain data with the aim of improving its analysis procedures. ViSimpl provides 3D particle-based rendering that allows visualizing simulation data with their associated spatial and temporal information, enhancing the knowledge extraction process. It also provides abstract representations of the time-varying magnitudes supporting different data aggregation and disaggregation operations and giving also focus and context clues. In addition, ViSimpl tools provide synchronized playback control of the simulation being analyzed. Finally, ViSimpl allows performing selection and filtering operations relying on an application called NeuroScheme. All these views are loosely coupled and can be used independently, but they can also work together as linked views, both in centralized and distributed computing environments, enhancing the data exploration and analysis procedures.