Fluorescence in situ hybridization (FISH) of neural activity-regulated, immediate-early gene (IEG) expression provides a method of functional brain imaging with cellular resolution. This enables the identification, in one brain, of which specific principal neurons were active during each of two distinct behavioral epochs. The unprecedented potential of this differential method for large-scale analysis of functional neural circuits is limited, however, by the time-intensive nature of manual image analysis. A comprehensive software tool for processing three-dimensional, multi-spectral confocal image stacks is described which supports the automation of this analysis. Nuclei counterstained with conventional DNA dyes and FISH signals indicating the sub-cellular distribution of specific, IEG RNA species are imaged using different spectral channels. The DNA channel data are segmented into individual nuclei by a three-dimensional multi-step algorithm that corrects for depth-dependent attenuation, non-isotropic voxels, and imaging noise. Intra-nuclear and cytoplasmic FISH signals are associated spatially with the nuclear segmentation results to generate a detailed tabular/database and graphic representation. Here we present a comprehensive validation of data generated by the automated software against manual quantification by human experts on hippocampal and parietal cortical regions (96.5% concordance with multi-expert consensus). The high degree of reliability and accuracy suggests that the software will generalize well to multiple brain areas and eventually to large-scale brain analysis.