Lindsay Grace W
Gatsby Computational Neuroscience Unit, Sainsbury Wellcome Centre, University College London, London, United Kingdom.
Front Comput Neurosci. 2020 Apr 16;14:29. doi: 10.3389/fncom.2020.00029. eCollection 2020.
Attention is the important ability to flexibly control limited computational resources. It has been studied in conjunction with many other topics in neuroscience and psychology including awareness, vigilance, saliency, executive control, and learning. It has also recently been applied in several domains in machine learning. The relationship between the study of biological attention and its use as a tool to enhance artificial neural networks is not always clear. This review starts by providing an overview of how attention is conceptualized in the neuroscience and psychology literature. It then covers several use cases of attention in machine learning, indicating their biological counterparts where they exist. Finally, the ways in which artificial attention can be further inspired by biology for the production of complex and integrative systems is explored.
注意力是灵活控制有限计算资源的重要能力。它已与神经科学和心理学中的许多其他主题结合进行研究，包括意识、警觉、显著性、执行控制和学习。最近它也被应用于机器学习的多个领域。生物注意力研究与其作为增强人工神经网络工具的用途之间的关系并不总是清晰的。本综述首先概述了注意力在神经科学和心理学文献中的概念化方式。然后介绍了注意力在机器学习中的几个应用案例，并指出了它们存在的生物学对应物。最后，探讨了如何通过生物学进一步启发人工注意力以产生复杂的综合系统。
