© 2016 Rübel, Dougherty, Prabhat, Denes, Conant, Chang and Bouchard.Neuroscience continues to experience a tremendous growth in data; in terms of the volume and variety of data, the velocity at which data is acquired, and in turn the veracity of data. Thes

Today scientists are producing large volumes of data that they wish to explore and visualize. In this paper we describe a system that combines range-based queries with fast lookup to allow a scientist to quickly and efficiently ask "what if?" questions. Unique to our system is the ability to perform "cumulative queries" that work on both an intra- and inter-time step basis. The results of such queries are visualized as frequency histograms and are the input for secondary queries, the results of which are then visualized.