一项关于内部言语的立体脑电图研究
A stereoencephalography study of internal speech
把与说话相关的脑活动转化为脑机接口指令，是帮助重度语言或运动障碍患者恢复交流的可能途径。本研究对11名因手术前评估而植入颅内电极的癫痫患者进行立体脑电图（一种把电极植入脑深部的记录方法）记录，让他们完成出声说话、动嘴不出声、心里默念和手写等任务。结果显示，不同任务在颞叶和额叶引起不同的脑电节律变化，尤其在α波和γ波频段；心里默念时关键运动和语言区的激活更弱、更晚，与出声和动嘴说话明显不同；机器学习分类器区分三种言语状态的平均准确率约72%。研究说明颅内电极能够识别内部言语与外部言语的切换，为开发多模态脑机接口提供依据。
为什么推荐给您：以颅内电极系统刻画内部言语的独特脑电特征，为言语脑机接口提供新机制证据。
不需要生物学背景，多打比方
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摘要Abstract
UNLABELLED: With advances in intracranial recording techniques, converting speech-related brain activity into commands for brain-computer interfaces (BCIs) is becoming increasingly feasible. In this study, we explored the utility of stereoencephalography (sEEG) for decoding covert and overt speech in humans. sEEG data were collected from 11 epilepsy patients undergoing presurgical monitoring, while they performed a set of speech tasks-overt speech, articulated speech, and imagined (inner) speech, as well as a handwriting task. Time- and frequency-domain analyses revealed that each speech condition elicited distinct spectral modulations, particularly in the alpha (8-12 Hz) and gamma (50-80 Hz) bands across temporal and frontal regions. Inner speech exhibited reduced and delayed activation in key motor and language-related areas, distinguishing it from both overt and articulated speech. In contrast, handwriting evoked a different activity pattern, marked by gamma desynchronization and more sustained alpha increases. A machine learning classifier achieved an average accuracy of 72% in distinguishing the three speech conditions based on their neural spectral profiles. These findings show that imagined speech is neurally the most distinct compared to the other speech tasks and demonstrate that sEEG can reliably detect the transitions between internal and overt forms of speech. This work contributes to the development of multimodal BCIs capable of decoding covert language representations, with implications for restoring communication in individuals with severe motor or speech impairments.
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s11571-026-10554-9.