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Application Domains
Bilateral Contracts and Grants with Industry
Bibliography
Application Domains
Bilateral Contracts and Grants with Industry
Bibliography


Section: Partnerships and Cooperations

European Initiatives

FP7 & H2020 Projects

VirtualBrainCloud
  • Title:

  • Programm: H2020 FET Open

  • Duration: 01/01/2019 - 31/12/2022

  • Coordinator: Petra Ritter

  • Inria contact: Bertrand Thirion

  • Summary:

    The central goal of this project is the development of a cloud-based platform for biomedical research and clinical decision-making that helps to improve early patient-specific diagnosis and treatment of NDD and has substantial potential for significant positive socioeconomic impact.

    The platform integrates several aims that revolve around early diagnosis, prognosis, and personalized treatment of neurodegenerative diseases (NDD) like Alzheimer’s disease (AD) and Parkinson’s disease (PD). It is becoming increasingly clear that meeting this objective requires a multifactorial approach that takes into account individual genetic, metabolic and environmental aspects, and that integrates them with the understanding of the biophysical processes underlying NDD.

    More information can be found here https://virtualbraincloud-2020.eu/tvb-cloud-main.html.

Neurolang
  • Title: Accelerating Neuroscience Research by Unifying Knowledge Representation and Analysis Through a Domain Specific Language

  • Programm: ERC Starting researcher

  • Duration: 01/03/2018 - 28/02/2023

  • Coordinator: Demian Wassermann

  • Inria contact: Demian Wassermann

  • Summary:

    Neuroscience is at an inflection point. The 150-year old cortical specialization paradigm, in which cortical brain areas have a distinct set of functions, is experiencing an unprecedented momentum with over 1000 articles being published every year. However, this paradigm is reaching its limits. Recent studies show that current approaches to atlas brain areas, like relative location, cellular population type, or connectivity, are not enough on their own to characterize a cortical area and its function unequivocally. This hinders the reproducibility and advancement of neuroscience.

    Neuroscience is thus in dire need of a universal standard to specify neuroanatomy and function: a novel formal language allowing neuroscientists to simultaneously specify tissue characteristics, relative location, known function and connectional topology for the unequivocal identification of a given brain region.

    The vision of NeuroLang is that a unified formal language for neuroanatomy will boost our understanding of the brain. By defining brain regions, networks, and cognitive tasks through a set of formal criteria, researchers will be able to synthesize and integrate data within and across diverse studies. NeuroLang will accelerate the development of neuroscience by providing a way to evaluate anatomical specificity, test current theories, and develop new hypotheses.

    NeuroLang will lead to a new generation of computational tools for neuroscience research. In doing so, we will be shedding a novel light onto neurological research and possibly disease treatment and palliative care. Our project complements current developments in large multimodal studies across different databases. This project will bring the power of Domain Specific Languages to neuroscience research, driving the field towards a new paradigm articulating classical neuroanatomy with current statistical and machine learning-based approaches.

SLAB (698)
  • Title: Signal processing and Learning Applied to Brain data

  • Programm: ERC Starting researcher

  • Duration: 01/04/2017 - 31/08/2021

  • Coordinator: Alexandre Gramfort

  • Partner: LTCI , Telecom ParisTech (France)

  • Inria contact: Alexandre Gramfort

  • Summary:

    Understanding how the brain works in healthy and pathological conditions is considered as one of the challenges for the 21st century. After the first electroencephalography (EEG) measurements in 1929, the 90’s was the birth of modern functional brain imaging with the first functional MRI and full head magnetoencephalography (MEG) system. In the last twenty years, imaging has revolutionized clinical and cognitive neuroscience.

    After pioneering works in physics and engineering, the field of neuroscience has to face two major challenges. The size of the datasets keeps growing. The answers to neuroscience questions are limited by the complexity of the signals observed: non-stationarity, high noise levels, heterogeneity of sensors, lack of accurate models. SLAB will provide the next generation of models and algorithms for mining electrophysiology signals which offer unique ways to image the brain at a millisecond time scale.

    SLAB will develop dedicated machine learning and signal processing methods and favor the emergence of new challenges for these fields. SLAB focuses on five objectives: 1) source localization with M/EEG for brain imaging at high temporal resolution 2) representation learning to boost statistical power and reduce acquisition costs 3) fusion of heterogeneous sensors 4) modeling of non-stationary spectral interactions to identify functional coupling between neural ensembles 5) development of fast algorithms easy to use by non-experts.

    SLAB aims to strengthen mathematical and computational foundations of brain data analysis. The methods developed will have applications across fields (computational biology, astronomy, econometrics). Yet, the primary impact of SLAB will be on neuroscience. The tools and high quality open software produced in SLAB will facilitate the analysis of electrophysiology data, offering new perspectives to understand how the brain works at a mesoscale, and for clinical applications (epilepsy, autism, tremor, sleep disorders).

HBP SGA2
  • Title: Interactive Computing E-Infrastructure for the Human Brain Project

  • Programm: FET Flagship

  • Duration: 01/04/2018 - 31/03/2020

  • Coordinator: Katrin Amunts

  • Partners: see https://www.humanbrainproject.eu/en/open-ethical-engaged/contributors/partners/

  • Inria contact: Bertrand Thirion

  • Summary:

    The HBP Flagship was launched by the European Commission's Future and Emerging Technologies (FET) scheme in October 2013, and is scheduled to run for ten years. The Flagships, represent a new partnering model for visionary, long-term European cooperative research in the European Research Area, demonstrating the potential for common research efforts. The HBP has the following main objectives:

    • Create and operate a European scientific Research Infrastructure for brain research, cognitive neuroscience, and other brain-inspired sciences

    • Gather, organise and disseminate data describing the brain and its diseases

    • Simulate the brain

    • Build multi-scale scaffold theory and models for the brain

    • Develop brain-inspired computing, data analytics and robotics

    • Ensure that the HBP's work is undertaken responsibly and that it benefits society.

    More information on the HBP's Flagship Objectives is available in the Framework Partnership Agreement.

    The timeline of the Project is split into multiple phases, each of which will be covered by a separate funding agreement. The current phase is Specific Grant Agreement Two (SGA2), which spans the two-year period from April 2018–April 2020. The HBP is funded via several sources. Total funding is planned to be in the region of EUR 1 billion; around one half of which will be provided by the European Union, and the other by Member States and private funding sources. The European Union contributed EUR 54 million to the Project in the Ramp-Up Phase (October 2013 to March 2016), EUR 89 million for the second phase (SGA1), and EUR 88 million for the current phase (SGA2). The FET Flagships Staff Working Document provides further information on how Flagships are funded.