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首页> 外文期刊>Journal of neurosurgery. >Identification of the subthalamic nucleus in deep brain stimulation surgery with a novel wavelet-derived measure of neural background activity.
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Identification of the subthalamic nucleus in deep brain stimulation surgery with a novel wavelet-derived measure of neural background activity.

机译:用一种新的基于小波的神经背景活动量来识别深部脑刺激手术中的丘脑下核。

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OBJECT: The authors developed a wavelet-based measure for quantitative assessment of neural background activity during intraoperative neurophysiological recordings so that the boundaries of the subthalamic nucleus (STN) can be more easily localized for electrode implantation. METHODS: Neural electrophysiological data were recorded in 14 patients (20 tracks and 275 individual recording sites) with dopamine-sensitive idiopathic Parkinson disease during the target localization portion of deep brain stimulator implantation surgery. During intraoperative recording, the STN was identified based on audio and visual monitoring of neural firing patterns, kinesthetic tests, and comparisons between neural behavior and the known characteristics of the target nucleus. The quantitative wavelet-based measure was applied offline using commercially available software to measure the magnitude of the neural background activity, and the results of this analysis were compared with the intraoperative conclusions. Wavelet-derived estimates were also compared with power spectral density measurements. RESULTS: The wavelet-derived background levels were significantly higher in regions encompassed by the clinically estimated boundaries of the STN than in the surrounding regions (STN, 225 +/- 61 microV; ventral to the STN, 112 +/- 32 microV; and dorsal to the STN, 136 +/- 66 microV). In every track, the absolute maximum magnitude was found within the clinically identified STN. The wavelet-derived background levels provided a more consistent index with less variability than measurements with power spectral density. CONCLUSIONS: Wavelet-derived background activity can be calculated quickly, does not require spike sorting, and can be used to identify the STN reliably with very little subjective interpretation required. This method may facilitate the rapid intraoperative identification of STN borders.
机译:目的:作者开发了一种基于小波的测量方法,用于在术中进行神经生理学记录期间定量评估神经本底活动,以便可以更轻松地将丘脑下核(STN)的边界定位于电极植入。方法:在深部脑刺激器植入手术的目标定位部分,对多巴胺敏感的特发性帕金森病的14例患者(20条轨迹和275个单独的记录部位)记录了神经电生理数据。在术中记录过程中,根据对神经放电模式的视听监视,动觉测试以及神经行为与靶核已知特征之间的比较来识别STN。使用可商购的软件离线应用基于小波的定量测量,以测量神经本底活动的强度,并将该分析结果与术中结论进行比较。小波衍生的估计值也与功率谱密度测量值进行了比较。结果:在临床估计的STN边界所包围的区域中,小波衍生的背景水平显着高于周围区域(STN,225 +/- 61 microV; STN腹侧,112 +/- 32 microV;以及背对STN,136 +/- 66 microV)。在每个轨道中,在临床鉴定出的STN中都发现了绝对最大量值。与功率谱密度测量相比,小波衍生的背景水平提供了更一致的索引,并且具有较小的可变性。结论:基于小波的背景活动可以快速计算,不需要峰值分类,并且可以在不需要很少的主观解释的情况下可靠地识别STN。该方法可以促进术中STN边界的快速识别。

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