Functional positron emission tomography (fPET) imaging using [18F]FDG serves as an index of neuronal activity independent of neurovascular coupling (Villien 2014). However, its absolute quantification through arterial blood sampling requires substantial resources (Hahn 2016). We investigate whether task-specific metabolism can be assessed without blood sampling.52 healthy subjects (23.2 ± 3.3 years, 24 female) performed Tetris® during an [18F]FDG fPET scan. Data acquisition, processing and analysis was performed as in (Hahn 2020). The general linear model (GLM) was used to identify task-specific changes in metabolism, the cerebral metabolic rate of glucose (CMRGlu) was calculated with Patlak plot. Group-averaged patterns (voxel-wise whole-brain analysis) were compared for three different parameters (CMRGlu, percent signal change (%SC) of GLM beta values and %SC of CMRGlu; p<0.05 FWE corrected cluster level following p<0.001 uncorrected height threshold). The association of %SC of betas and CMRGlu was assessed with ROI-wise (i.e., frontal eye field (FEF), intraparietal sulcus (IPS) and occipital cortex (Occ)) Pearson correlation analysis.All three parameters exhibited highly similar activation patterns in the OCC, FEF and IPS (Fig. 1). The ROI-wise Pearson analysis revealed a strong correlation between %SC of both CMRGlu and betas (all r > 0.998).Functional PET can measure changes in glucose metabolism during task performance compared to baseline without the need for blood sampling, however, with the trade-off of being unable to quantify the baseline metabolism. In consequence, fPET becomes more accessible for any imaging center equipped with a PET scanner, in both clinical and research settings.