This proposal outlines specific enhancements to the process of very large-field 3D laser-scanning light microscopy and electron tomography to increase the throughput of generating structural data to be assembled into multi-resolution "visible" cells for computational neuroscience. For each processing stream, this proposal identifies data, computation time, and labor intensive tasks, and it outlines solutions enhanced by grid resources for increasing end-to-end performance, accelerating computation, enhancing visualization, and archiving and managing data. To foster modeling studies, this project also outlines the development of software solutions for improving the accuracy and continuity of rendered surfaces, aligning "serial" volumes, and isolating the areas containing specific densities or types of "effecter molecules" (post-synaptic densities, channels, proteins, etc.) and functional components derived from literature, light and/or EM studies. Each processing stream will be further integrated into a web-based application environment where users can securely and collaboratively perform each operation from data acquisition to database deposition, and provides an end-to-end solution for automatically scheduling instruments, performing the necessary data movements, coordinating and scheduling the data processing stages, acquiring specialized visualization resources, and managing and staging distributed data. The data produced by both imaging processes is of great value to researchers and students using simulation programs like MCell, Neuron, and GENESIS. The incorporation of realistic structure into the computational models increases the accuracy of the simulation output as well as the utility and validity of the results. Ultimately, the use of accurate derived "visible" neurons will create an unprecedented opportunity to probe the effects of structure in the behavior of the nervous system. Moreover, the technologies to richly integrate instruments, grid infrastructure and services, automated data management, and user-friendly web-based collaborative control will be broadly extensible to other scientific domains and will continue to enable and enrich opportunities for education and outreach.