arXivDaily arXiv每日学术速递 周一至周五更新

科学与医疗

脑机接口 / BCI

脑机接口、EEG、神经信号解码、神经假体和脑控交互。

2026-05-29 至 2026-05-29 共收录 2 信号源:q-bio.NC, eess.SP, cs.LG, cs.HC, cs.RO

1. BCI数据与评测 2 篇

2605.29591 2026-05-29 cs.AI 67%

Mind-Omni: A Unified Multi-Task Framework for Brain-Vision-Language Modeling via Discrete Diffusion

Mind-Omni:通过离散扩散实现脑-视觉-语言建模的统一多任务框架

Yizhuo Lu, Changde Du, Qingyu Shi, Hang Chen, Jie Peng, Liuyun Jiang, Shuangchen Zhao, Huiguang He

机构 * NeuBCI Lab, State Key Laboratory of Brain Cognition Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China School of Future Technology, University of Chinese Academy of Sciences, Beijing, China School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China Zhongguancun Academy, Beijing, China Peking University, Beijing, China

专题命中 BCI数据与评测 :BCI(abstract_cn);brain-computer interface(abstract)

AI总结 提出Mind-Omni框架,利用离散扩散范式统一七种编码与解码任务,通过脑分词器将连续脑信号转化为离散令牌,实现多模态交互,并构建脑问答指令调优数据集,在多项任务上达到或超越专用模型性能。

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2510.16658 2026-05-29 cs.AI cs.CE 67%

Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review

大规模人工智能与基础模型在神经科学中的应用:综合综述

Shihao Yang, Xiying Huang, Danilo Bernardo, Jun-En Ding, Andrew Michael, Guoan Wang, Jingmei Yang, Alison Anderson, Dinesh Giritharan, Patrick Kwan, Ashish Raj, Yu Zhang, Feng Liu

机构 * Department of Systems Engineering, Stevens Institute of Technology(系统工程系,史蒂文斯理工学院) Department of Neurology and Weill Institute for Neurosciences, University of California San Francisco(神经病学系和Weill神经科学研究所,旧金山大学) Duke Institute for Brain Sciences, Duke University(杜克大学脑科学研究所) Division of Systems Engineering, Department of Electrical and Computer Engineering, Boston University(系统工程 division,电气与计算机工程系,波士顿大学) Department of Neuroscience, School of Translational Medicine, Monash University(神经科学系,转化医学学院,莫纳什大学) Department of Neurology, Alfred Hospital, Melbourne, Victoria, Australia(神经病学系,阿尔弗雷德医院,墨尔本,维多利亚州,澳大利亚) Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA(放射学与生物医学成像系,旧金山大学,加州,美国) Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University(精神病学与行为科学系,医学院,斯坦福大学) Wu Tsai Neurosciences Institute, Stanford University(吴氏神经科学研究所,斯坦福大学) Stanford Institute for Human-Centered AI, Stanford University(斯坦福大学人本人工智能研究所)

专题命中 BCI数据与评测 :brain-computer interface(abstract);neural decoding(abstract)

AI总结 本文综述了大规模AI模型在神经科学四个主要领域(神经影像与数据处理、脑机接口与神经解码、临床决策支持与转化框架、神经系统与精神疾病特定应用)的应用,展示了其在多模态数据整合、时空模式解释和临床转化方面的潜力,并强调了严格评估、领域知识整合、临床验证和伦理指南的重要性。

Comments Accepted for publication in Meta-Radiology

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