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头皮脑电图对骨缺陷的有用性,用于解码肌肉活动

Tomoyuki Yamashita¹, Masahiro Sawada¹, Ai Demura¹

¹Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan.

World neurosurgery

|November 29, 2025

概括

脑电图 (EEG) 在脑损伤后的骨缺陷上捕获了丰富的神经信号. 这种最少的侵入性方法能够有效地控制治疗的人工神经连接 (ANC),与侵入性方法相比.

科学领域:

神经科学是一个神经科学.
生物医学工程生物医学工程
康复医学康复医学康复医学

背景情况:

大脑机器接口 (BMI) 使用人工神经连接 (ANC) 将神经活动转化为控制命令,以恢复患者的运动功能.
诸如脑电图 (EEG),心电图 (ECoG) 和皮质内微电极等侵入性技术为ANC提供了高质量的信号,但非侵入性EEG受到头骨衰减的限制.
这项研究调查了EEG记录在解压切除骨缺陷上是否保留了足够的神经信息来有效控制ANC.

研究的目的:

为了确定经过解压脑膜切除术后记录在骨缺陷上的EEG信号是否含有丰富的神经信息.
评估使用这些EEG信号控制人工神经连接 (ANC) 的有效性.
为了比较EEG在骨缺陷上的性能与侵入性电皮质谱 (ECoG) 来解码神经活动.

主要方法:

在手握任务期间,从脑膜切除术患者身上记录了头皮脑电图信号,分析了高马频率 (65-300 Hz).
基于回归的解码模型从EEG信号预测了手部肌肉活动.
来自醒着的瘤切除患者的ECoG信号被用于比较,肌肉活动也被类似地解码.

主要成果:

脑膜切除部位的EEG成功地解码了中高精度的肌肉活动 (R = 0.74 ± 0.21).
使用EEG对骨缺陷的解码精度与使用侵入性ECoG信号 (R = 0.55 ± 0.18) 实现的精度相当.
结果表明,在骨缺陷上保留了大量的神经活动,并可解码.

结论:

在骨缺陷上记录的EEG保留了丰富的皮质信号,质量类似于侵入性ECoG.
这一发现为开发有效的基于ANCs的疗法建立了一个最小入侵的平台.
这种方法对脑损伤需要恢复运动功能的患者来说是有前途的.

关键词:

人工神经连接的人工神经连接骨缺陷头皮EEG脑电图大脑机器界面是大脑机器界面.减压式骨切除术是什么?电皮质谱学电皮质谱学电皮质谱学

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