fPET enables the identification of stimulation-induced changes in glucose metabolism and neurotransmitter action as well as molecular connectivity. The toolbox offers various analysis approaches, including the General Linear Model (GLM), Independent Component Analysis (ICA) as well as molecular connectivity and covariance computation. It is optimized to handle fPET data that has been acquired using a bolus + constant infusion protocol with high temporal resolution (1–60 seconds), but other settings may be feasible.

The fPET Toolbox has been rigorously tested and validated across a wide range of experimental settings. It has been applied to studies involving diverse stimulation paradigms, including visual, motor, Tetris, working memory, monetary incentive delay, and optogenetic tasks. Validation has been performed across multiple species, including humans, non-human primates, and rodents, and on a variety of PET systems, such as GE Advance, Siemens Biograph mMR 3T, Siemens Biograph Vision 600 Edge, Siemens Biograph Quadra, Brain Biosciences CerePET, and a Bruker small-animal PET insert for the 7T ClinScan. The toolbox supports multiple radioligands, including [¹⁸F]FDG, 6-[¹⁸F]FDOPA, and [¹¹C]AMT.

Across these diverse applications, the toolbox has been successfully used in numerous studies, demonstrating its robustness and reliability for analyzing stimulation-induced metabolic changes and molecular connectivity measures.