The Human Brain Project (HBP) is a major European scientific research initiative to improve our understanding of the brain and the role it plays in making us human, and to exploit the opportunities offered by the resulting knowledge. The size and complexity of the brain make this an expensive undertaking, but the costs associated with our current ignorance are rising and the potential gains from better insight into the brain are increasing. Brain-related diseases, many of which are age-related, now represent a major part of the global health burden and there are both ethical and economic imperatives to keep the growing number of older people healthier and more productive. Economic advantage is increasingly linked to artificial intelligence (AI), our ability to create technology to extract, manipulate and harness knowledge. The HBP’s comprehension of what makes the human brain so efficient and flexible should help to maintain Europe’s competitiveness and innovation potential in this area.
The HBP is one of several brain research initiatives and projects around the world, albeit one of the first, but it is unique in a number of ways. Only the HBP has an explicit focus on both neuroscience and computing. It is also the broadest and most integrated brain initiative, and the only one aiming to build a research infrastructure to accelerate brain research.
The HBP is a FET Flagship which started under FP7 and continues under H2020 with a succession of Specific Grant Agreements (SGAs) under a Framework Partnership Agreement (FPA). In its FP7 Ramp-Up Phase (2013-16) and subsequent SGA1 funding period (2016-18), the HBP implemented a scientific project of rare ambition, breadth
and scale, and forged its diverse constituents into a functioning entity. On the scientific side, it not only identified critical gaps in our understanding of the brain, but also created tools and obtained data to fill many of them. It designed, built and demonstrated six ICT research platforms, supporting neuroinformatics, brain simulation, high- performance analytics and computing, medical informatics, brain-inspired computing and linking of simulated brains to robotic bodies. The results have been made available to the scientific community. The HBP also learnt to address underperformance and conflicts, and opened up the Project via competitive calls and the integration of Partnering Projects.
In the upcoming SGA2 funding period (2018-20), the HBP will continue to strengthen global brain research efforts by extending coordination with other brain initiatives and projects. Internally, it will continue its unique inter-disciplinary co-design approach, developing research infrastructure capabilities via use cases built around specific research needs. This approach will underpin its critical scientific work of understanding how to bridge between the different scales of brain organisation, a key prerequisite to understand the principles of brain organisation. It will include gathering data to support detailed modelling, notably of the human hippocampus, as well as structural, functional and connectivity data to improve systemic understanding of the whole brain. The HBP will also investigate brain similarities and differences between individuals and between species. It will model key brain functions, including visual recognition, slow-wave activity, episodic memory and consciousness in rodents and humans, and elaborate their cognitive architectures. In addition, it will develop simplified brain models to support further development of brain- inspired computing.
SGA2 will see the individual infrastructure platforms extended and integrated into the HBP Joint Platform (HBP- JP). The JP will make HBP services more robust and improve the user experience, encouraging wider use of its tools. SGA2 should thus see a shift from supplier-driven to user-driven capabilities, while the infrastructure underpinning them will be tied closely into EU efforts to integrate and strengthen HPAC capabilities to support broad range of scientific needs such as PRACE. The HBP will prepare researchers to harness future novel and extreme-scale computing resources to their scientific work, while allowing them shape the design of those resources. In this way, emerging brain-inspired AI will be driven by better neuroscientific insights, dramatically improving our ability to replicate the functionalities of the brain and understand its connectional architecture. In particular, emulating the brain’s ability to learn will enable a major advancement over current deep learning approaches.
