Laboratory for Advanced Brain Functions, Institute for Protein Research, Osaka University, Osaka, Japan.
Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, NY, USA.
Neural Netw. 2021 Dec;144:603-613. doi: 10.1016/j.neunet.2021.09.018. Epub 2021 Sep 28.
Neuroscience and artificial intelligence (AI) share a long history of collaboration. Advances in neuroscience, alongside huge leaps in computer processing power over the last few decades, have given rise to a new generation of in silico neural networks inspired by the architecture of the brain. These AI systems are now capable of many of the advanced perceptual and cognitive abilities of biological systems, including object recognition and decision making. Moreover, AI is now increasingly being employed as a tool for neuroscience research and is transforming our understanding of brain functions. In particular, deep learning has been used to model how convolutional layers and recurrent connections in the brain's cerebral cortex control important functions, including visual processing, memory, and motor control. Excitingly, the use of neuroscience-inspired AI also holds great promise for understanding how changes in brain networks result in psychopathologies, and could even be utilized in treatment regimes. Here we discuss recent advancements in four areas in which the relationship between neuroscience and AI has led to major advancements in the field; (1) AI models of working memory, (2) AI visual processing, (3) AI analysis of big neuroscience datasets, and (4) computational psychiatry.
神经科学和人工智能（AI）有着长期的合作历史。神经科学的进步，以及过去几十年计算机处理能力的巨大飞跃，催生了新一代受大脑结构启发的计算神经网络。这些 AI 系统现在能够实现许多生物系统的高级感知和认知能力，包括目标识别和决策。此外，人工智能现在越来越多地被用作神经科学研究的工具，并正在改变我们对大脑功能的理解。特别是，深度学习已被用于模拟大脑皮层中的卷积层和循环连接如何控制重要功能，包括视觉处理、记忆和运动控制。令人兴奋的是，受神经科学启发的 AI 的使用也为理解大脑网络的变化如何导致精神病理学提供了巨大的希望，并可能用于治疗方案。在这里，我们讨论了神经科学和 AI 之间的关系在四个领域取得重大进展的最新进展；（1）工作记忆的 AI 模型，（2）AI 视觉处理，（3）AI 对大型神经科学数据集的分析，以及（4）计算精神病学。
