Human Brain Project (HBP)

The Human Brain Project is a European-funded research initiative involving more than 100 institutions all over the continent. The goal of the project is to unveil the secrets of the human brain and uncover the mechanisms responsible for cognitive processes, learning and consciousness. The key-word for HBP is multi-disciplinarity: HBP is not only a fruitful ground for pioneering research in the field of neuroscience, but also a successful experiment of collaboration between several different scientists, bridging together medical doctors, biologists, physicists, computer scientists, engineers and philosophers, and linking experimental data with theoretical models and high-performance computer simulations. 

HBP started in 2013, with the so-called ramp-up phase, during which the backbone and the main scientific targets of the project have been defined. In this starting phase, calls have been opened to the scientific community in order to extend the objectives of research and to address specific goals.  A dedicated scientific board selected the projects that won the competition among the several applicants, forming what is now called the Systems and Cognitive Neuroscience Sub-Project (SP3). One of the 4 winner projects was WaveScalES, led by Pier Stanislao Paolucci. With it, APE Lab and INFN entered the HBP project since its first Scientific Grant Agreement phase (SGA1, 2016-2018), guiding an international collaboration aimed at investigating the role of the different expressions of electrophysiological activity of the cortex during deep sleep. Activities went on during the SGA2 (2018-2020), followed by SGA3 in 2020 and came to a conclusion in 2023. In these years, we have consolidated our position in the field, gaining experience and extending our network and lines of actions. Our past and present research interests and efforts are focused on several items (theses available):

  • hardware and software co-design for distributed spiking neural network simulations on parallel computing architectures (DPSNN)
  • hardware and software co-design for neuromorphic computing systems (focus on network, latency, scalability)
  • data analysis (electrophysiological and imaging data from rodents and monkeys)
  • data-driven inference-based mean-field models 
  • thalamo-cortical spiking models of sleep and wakefulness 
  • software tools for the HBP-EBRAINS infrastructure platforms