Aging alters brain structure and function, and studying such changes may help understand the neural basis underlying aging and devise interventions to detect deviations from healthy progression. Electroencephalogram (EEG) offers an effective way to study healthy aging owing to its high temporal resolution and affordability. Recent studies have shown that narrow-band stimulus-induced gamma oscillations (20-70 Hz) in EEG, induced with cartesian gratings in a fixation task paradigm, weaken with healthy aging and onset of Alzheimer’s Disease (AD) while remaining highly reproducible for a given subject, and thus hold promise as potential biomarkers. However, functional connectivity (FC) sometimes changes in a different way compared to sensor power with aging. This difference could be potentially addressed by studying how underlying gamma sources change with aging, since either a reduction in source power or a shrinkage of the sources (or both) could reduce the power in the sensors but may have different effects on other measures such as FC. We therefore reconstructed EEG gamma sources through a linear inverse method called exact Low-resolution Tomography Analysis (eLORETA) on a large (N=217) cohort of healthy elderly subjects (>50 years). We further characterized gamma distribution in cortical space as an exponential fall-off from a seed voxel with maximal gamma source power to delineate a reduction in magnitude versus shrinkage. We found significant reduction in magnitude but not shrinkage with healthy aging. Overall, our results shed light on changes in EEG gamma source distribution with healthy aging, which could provide clues about underlying neural mechanisms.