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.