Brain science accelerates the study of intelligence and behavior, contributes fundamental insights into human cognition, and offers prospective treatments for brain disease. Faced with the challenges posed by imaging technologies and deep learning computational models, big data and high-performance computing (HPC) play essential roles in studying brain function, brain diseases, and large-scale brain models or connectomes. We review the driving forces behind big data and HPC methods applied to brain science, including deep learning, powerful data analysis capabilities, and computational performance solutions, each of which can be used to improve diagnostic accuracy and research output. This work reinforces predictions that big data and HPC will continue to improve brain science by making ultrahigh-performance analysis possible, by improving data standardization and sharing, and by providing new neuromorphic insights.
脑科学加速了人类对智力和行为的研究，它不仅为了解人类认知奠定基础，同时还不断为解决脑疾病提供前瞻性治疗方法。如今，面对由于影像技术和深度学习模型应用于脑科学研究所带来的挑战，大数据和高性能计算在研究大脑功能机制、脑疾病和大规模脑模型或连接组等方面发挥着巨大作用。本文回顾了深度学习、大数据分析和计算性能解决方案等大数据和高性能方法如何驱动脑科学研究的发展，尤其是在提高诊断准确性和突破研究成果方面。未来，为了应对不断增加的大脑数据和模拟计算的挑战，这些大数据和高性能计算方法将持续朝着实现超高性能分析、改进数据标准化和共享、以及提供新的神经形态计算机等方向发展来深化其推动作用。





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