Research in computational neuroscience has been following a model-based approach where data is comprised of digitized streams of sampled analog data, images and voice. The data are generally contained in files and specialized programs are used to analyze the data. In this study we developed a prototype system for indexing and retrieving information for use by an application that analyzes data. The data in the files consist of channels derived from analog and event driven sources. It is also linked to video images associated with the data acquisition. In this research, we developed an indexing capability that threads into the data acquisition and analysis programs to give the system a broad data base capability. We designed tables and relations within the database for indexing the files and information contained within the file. The system has the potential of giving us retrieval capabilities that include analog, event, and video data types.