数字大脑研究的未来十年:技术与计算交汇处的神经科学愿景

K. Amunts, M. Axer, L. Bitsch, J. Bjaalie, A. Brovelli, S. Caspers, I. Costantini, E. D’Angelo, G. Bonis, J. DeFelipe, A. Destexhe, Timo Dickscheid, M. Diesmann, S. Eickhoff, Andreas K. Engel, J. Fousek, S. Furber, R. Goebel, Onur Günterkün, J. Kotaleski, C. Hilgetag, S. Hölter, Y. Ioannidis, V. Jirsa, W. Klijn, J. Kämpfer, T. Lippert, A. Meyer-Lindenberg, M. Migliore, Yannick Morel, F. Morin, Lena Oden, F. Panagiotaropoulos, P. Paolucci, C. Pennartz, S. Petkoski, Mihai A. Petrovici, P. Ritter, S. Rotter, Andreas Rowald, S. Ruland, Philippe Ryvlin, Arleen Salles, M. Sanchez-Vives, J. Schemmel, B. Thirion
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引用次数: 14

摘要

摘要 近年来,脑科学研究无可争议地进入了一个新纪元,其驱动力是方法学的长足进步以及从分子到整个大脑等多个尺度的数字化数据整合和建模。神经科学与技术和计算的交汇点正在出现重大进展。这一新的脑科学结合了高质量的研究、多尺度的数据整合、多学科大规模合作的新文化以及应用转化。正如欧洲人脑计划(HBP)所开创的那样,系统化的方法对于应对未来十年紧迫的医疗和技术挑战至关重要。本文旨在为未来十年的数字大脑研究提出一个概念,与广大研究界讨论这一新概念,找出共同点,并从中得出科学的共同目标;为 EBRAINS(由 HBP 工作产生的研究基础设施)当前和未来的发展提供一个科学框架;就未来的数字大脑研究向利益相关者、资助组织和研究机构提供信息,并使其参与其中;确定并解决综合大脑模型在人工智能(包括机器学习和深度学习)方面的变革潜力;概述一种合作方法,将伦理和社会机遇与挑战方面的反思、对话和社会参与结合起来,作为未来神经科学研究的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing
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, 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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