Because the human brain consumes a disproportionate fraction of the resting body's energy, positron emission tomography (PET) measurements of absolute glucose metabolism (CMR_glc) can serve as disease biomarkers. Global mean normalization (GMN) of PET data reveals disease-based differences from healthy individuals as fractional changes across regions relative to a global mean. To assess the impact of GMN applied to metabolic data, we compared CMR_glc with and without GMN in healthy awake volunteers with eyes closed (i.e., control) against specific physiological/clinical states, including healthy/awake with eyes open, healthy/awake but congenitally blind, healthy/sedated with anesthetics, and patients with disorders of consciousness. Without GMN, global CMR_glc alterations compared to control were detected in all conditions except in congenitally blind where regional CMR_glc variations were detected in the visual cortex. However, GMN introduced regional and bidirectional CMR_glc changes at smaller fractions of the quantitative delocalized changes. While global information was lost with GMN, the quantitative approach (i.e., a validated method for quantitative baseline metabolic activity without GMN) not only preserved global CMR_glc alterations induced by opening eyes, sedation, and varying consciousness but also detected regional CMR_glc variations in the congenitally blind. These results caution the use of GMN upon PET-measured CMR_glc data in health and disease.