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| Hauptseite > Publikationsdatenbank > The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing > print |
| Hauptseite > Publikationsdatenbank > The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing > print |
| 001 | 1024884 | ||
| 005 | 20250930132713.0 | ||
| 024 | 7 | _ | |a 10.1162/imag_a_00137 |2 doi |
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| 082 | _ | _ | |a 050 |
| 100 | 1 | _ | |a Amunts, Katrin |0 P:(DE-Juel1)131631 |b 0 |e Corresponding author |u fzj |
| 245 | _ | _ | |a The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing |
| 260 | _ | _ | |a Cambridge, MA |c 2024 |b MIT Press |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
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| 520 | _ | _ | |a In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modelling at multiple scales— from molecules to the whole brain. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain combines high-quality research, data integration across multiple scales, a new culture of multidisciplinary large-scale collaboration and translation into applications. As pioneered in Europe’s Human Brain Project (HBP), a systematic approach will be essential for meeting the coming decade’s pressing medical and technological challenges. The aims of this paper are to: develop a concept for the coming decade of digital brain research, discuss this new concept with the research community at large, to identify points of convergence, and derive therefrom scientific common goals; provide a scientific framework for the current and future development of EBRAINS, a research infrastructure resulting from the HBP’s work; inform and engage stakeholders, funding organisations and research institutions regarding future digital brain research; identify and address the transformational potential of comprehensive brain models for artificial intelligence, including machine learning and deep learning; outline a collaborative approach that integrates reflection, dialogues and societal engagement on ethical and societal opportunities and challenges as part of future neuroscience research. |
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