The coming decade of digital brain research – A vision for neuroscience at the intersection of technology and computing

Submitted by philipp on Tue, 01/30/2024 - 18:59
Abstract
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 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.
While we do not claim that there is a ‘one-size-fits-all’ approach to addressing these aspects, we are
convinced that discussions around the theme of digital brain research will help drive progress in the
broader field of neuroscience.
Amunts et al. The coming decade of digital brain research – A vision for neuroscience at the intersection of technology and computing, preprint, 10.5281/zenodo.10035197
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