双极和拉普拉斯编辑适用于高马调制语言映射与立体电脑图谱
Takumi Mitsuhashi1,2, Yasushi Iimura1,2, Hiroharu Suzuki1,2
1Department of Neurosurgery, Juntendo University, Tokyo, Japan.
Frontiers in neurology
|October 31, 2024
概括
双极和拉普拉斯编辑通过减少不需要的信号,通过立体电脑图学来改善高马语言映射. 隐蔽的回应可能更好地表明灰色物质活动,以准确地定位语言.
科学领域:
- 神经科学是一个神经科学.
- 临床电生理学 临床电生理学
背景情况:
- 通过立体电脑学 (SEEG) 测量的高马调制对于语言映射至关重要.
- 为了准确地绘制高马语言的地图,需要最佳的电极组装和发音条件.
研究的目的:
- 为了确定最佳的电极安装和高马语言映射的发音条件,使用SEEG.
- 评估不同安装和响应条件对高马振幅测量的影响.
主要方法:
- 研究了使用深度电极进行SEEG的12名患者.
- 听觉命名任务被用来测量高马波 (60-140 Hz) 调制.
- 分析了常见平均参考,双极和拉普拉斯编辑的效果,以及公开与隐蔽的发音.
主要成果:
- 与常见的平均参考组合相比,双极和拉普拉斯组合显著减少了白质和大脑外围膜中的信号偏移.
- 这些组装在皮层水平上保持了高马信号幅度.
- 隐蔽的发声反应减少了大脑外围膜外的信号偏移.
结论:
- 双极和拉普拉斯安装适用于使用SEEG测量灰色物质中与听觉命名相关的高马调制.
- 隐蔽的响应可能会在语言映射过程中增强灰色物质活动的检测.
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