The Applications Subproject represents the first step towards achieving the ambitious goals of the HBP for the Operational Phase. The goals for the Ramp-Up Phase were to test and refine the pre-release versions of the ICT platforms, to provide early, small-scale demonstrations of their potential for research in neuroscience, medicine and computing, and to prepare for more ambitious research in the Operational Phase. The Subproject is broken down into three areas: future neuroscience, future medicine and future computing.

Future Neuroscience

The tools provided by the Neurorobotics Platform will allow cognitive neuroscientists to create set-ups in which a brain model (a model of a specific circuit, region of system, a whole brain model) is coupled with a simulated robot (a virtual "tissue sample", or a "virtual animal") that interacts with a virtual environment (a simulated experimental set-up). The objective of the pilot project planned in the Ramp-Up Phase will be to use the capabilities provided by the Brain Simulation, High Performance Computing and Neurorobotics Platforms to perform proof-of-concept simulation-based research into the multi-level brain mechanisms responsible for visual perception. As a test case, the HBP used the well-known Weber-Fechner law. The study makes it possible to characterise the psychometric function calculated by the brain model, and compare activity data for simulated neurons at each stage of visual processing against documented physiological responses. This will provide insights into the detailed neuronal mechanisms responsible for the response, while simultaneously helping to refine and validate the brain model. HBP will use similar methods to calibrate the brain model for other closed loop experiments involving selected actuators and sensors.

Future Medicine

The HBP aims to provide researchers in medicine and pharmacology with the tools they need to accelerate research into the causes, diagnosis and treatment of neurological and psychiatric disease. In the long term, the HBP aims to:

  1. Identify differential disease signatures from clinical data made available through the Medical Informatics Platform, and to develop new nosological classifications based on predisposing factors and biological dysfunctions rather than symptoms and syndromes.
  2. Use biological signatures of disease as a source of insights into disease processes, testing specific hypotheses of disease simulation through modelling and simulation.
  3. Use disease models to identify potential drug targets and other possible treatment strategies, and to predict desirable and adverse effects.
  4. Develop strategies for personalised medicine, allowing the development of treatments adapted to the specific condition of individual or specific subgroups of sensitive or vulnerable patients.

The pilot project in the Ramp-Up Phase developed a model for the identification of biological signatures of neurological and psychiatric disease, and demonstrated its validity for the case of Alzheimer's Disease.

Future Computing

One of the HBP's main goals is to use results from brain modelling to develop new computing technologies. The ICT platforms will make it possible to build and test novel software, hardware and robotic systems, inspired by knowledge of the brain, and to explore their applications. Such systems have the potential to overcome critical limitations of current ICT, including limits on programmability, power consumption and reliability. The HBP will implement early projects to demonstrate these possibilities and will dedicate a significant part of its funding to support for projects proposed by researchers from outside the Project. If these initiatives are successful, the end result will be novel applications with a potentially revolutionary impact on manufacturing, services, health care, the home, and other sectors of the economy. In the Ramp-Up Phase, SP11 began a pilot project using neuromorphic computing technology as the basis for an automated, self-training computing system that will make it possible to analyse massive science-, business- and security-related datasets that are intractable for conventional machine learning.

What People are Saying

  • Collaborate, collaborate, collaborate. This is our opportunity.

    Prof. Karlheinz Meier, University of Heidelberg,
    Co-leader of the Neuromorphic Computing Subproject

  • The Human Brain is the most complex system that we know of. We would like to develop some kind of ‘google' brain where we can zoom in and out, see it from different perspectives and understand how brain structure and function is related. The ultimate aim of the Human Brain Project is to understand the human brain. This is only possible when we understand the structural organization of the human brain.

    Prof. Katrin Amunts, Institute of Neuroscience and Medicine,
    Forschungszentrum Jülich

  • The Human Brain Project will become a major driver of ICT in Europe.

    Prof. Thomas Lippert, Institute for Advanced Simulation, Jülich Supercomputing Centre,
    leader of the High Peformance Computing subproject