脑电信号的解码和应用场景

        脑电信号是大脑神经元活动产生的电信号。侵入式脑电是一种通过直接植入电极到大脑皮层来记录神经元活动的技术，可以准确地记录神经元活动的细节，从而有助于更深入地理解大脑的工作机制。非侵入式脑电不需要在大脑中植入电极，对于临床和人类研究而言更为安全，但信噪比相对较低。

        神经信号对视觉刺激的编码方式，其实可以从两个方向来研究刺激与反应之间的关系。神经编码试图建立从刺激到反应的映射，着眼于理解神经元如何对不同的刺激做出反应，建立模型来预测神经元对特定刺激的反应。而神经解码研究的是相反方向的映射，从已知的反应来推算外界刺激，试图从被激发的动作电位序列来重建外界刺激或者刺激的某些特征。对于视觉脑机接口而言，神经编码的主要目标是理解神经元如何对自然视觉信息进行感知和响应，脑电信号的解码旨在尽可能多地恢复来自神经响应的原始刺激。

        近几十年，许多研究关注视觉通路中的各种脑电解码机制问题。根据不同的解码目标，可大致将这些机制划分为三大类：1）视觉刺激分类，即特定刺激被划分至最佳匹配图像组；2）视觉刺激识别，即视觉刺激被识别为特定的物体种类；3）视觉刺激重建，引起神经响应的视觉刺激被重建。

        考虑到线性方法具有可解释性、计算效率高的特点，早期脑电信号解码方法依赖于线性解码这种范式。虽然线性解码方法能够从神经响应中解码出空间均匀分布的白噪音刺激以及自然场景刺激的大致结构，但难以重构自然图像中的视觉细节信息。最新的神经解码方法运用非线性方法对复杂视觉刺激进行精确重构。许多研究者已经将深度学习方法成功应用于脑电信号解码，这些研究成果为人工视觉领域带来巨大的推动。

        2022年中国信通院发布的《脑机接口总体愿景与关键技术研究报告》分析了采集技术、刺激技术、范式编码技术和解码算法技术等4种核心技术的发展现状及趋势，并指出脑机接口技术的应用场景按照信息流向分为脑状态检测、神经调控和对外交互三类。从信息流向来看，脑状态检测是信息从大脑流向外部和外设，神经调控则是信息从外部和外设流向大脑，而对外交互则是信息的双向流动，因此信息的利用、交互和反馈是脑机接口系统的三个重要环节。

参考文献：

Zhang Y J, Yu Z F, Liu J K, et al. Neuraldecoding of visual information across different neural recording modalities andapproaches[J]. Machine Intelligence Research, 2022, 19(5): 350-365.

Edelman B J, Zhang S, Schalk G, et al.Non-invasive Brain-Computer Interfaces: State of the Art and Trends[J]. IEEEReviews in Biomedical Engineering, 2024.

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