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Electroencephalography (EEG) from scalp potentials is a crucial non-invasive technique for imaging the electric brain activity. EEG is of primary importance in several scenarios of substantial societal impact ranging from electric characterization of epileptic seizures to the development of brain computer interfaces. One of the key technologies in advanced EEG imaging is the source imaging/localization procedure where the volume electric current responsible for the scalp potential is obtained solving an inverse source problem, in turn requiring several solutions of the EEG forward problem. The imaging of the brain currents is what turns a standard EEG scalp device into an high resolution EEG brain imaging technology. Lamentably, the standard EEG forward problem has cubical computational complexity resulting in an eight times increase in computational time and computer memory required every time the problem doubles in size. This substantially limits the impact of EEG imaging, especially in application scenarios where only low power computational systems are available either because of portability (ambulances) or budget limitations (small medical centers). The goal of the “TurboEEG” project is to radically change this paradigm: we will translate the outcomes of the ERC Consolidator Grant project “321” into the field of EEG neuroimaging obtaining and distributing the first existing EEG open source package that will solve the EEG imaging problem in linear complexity, speeding up standard EEG imaging of orders of magnitude and making high resolution EEGs widely available and cheap. The new open source tool will have a substantial impact on society by making available high resolution EEG technology in environments where top computational power is not available such as small hospitals or ambulances, but also schools and universities. The new open-source tool will in fact also have a substantial impact on education, professional training, and brain research.