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首页> 外文期刊>Brain research bulletin >Complex analysis of neuronal spike trains of deep brain nuclei in patients with Parkinson's disease.
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Complex analysis of neuronal spike trains of deep brain nuclei in patients with Parkinson's disease.

机译:帕金森氏病患者深部神经核神经元突波序列的复杂分析。

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摘要

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been used to alleviate symptoms of Parkinson's disease. During image-guided stereotactic surgery, signals from microelectrode recordings are used to distinguish the STN from adjacent areas, particularly from the substantia nigra pars reticulata (SNr). Neuronal firing patterns based on interspike intervals (ISI) are commonly used. In the present study, arrival time-based measures, including Lempel-Ziv complexity and deviation-from-Poisson index were employed. Our results revealed significant differences in the arrival time-based measures among non-motor STN, motor STN and SNr and better discrimination than the ISI-based measures. The larger deviations from the Poisson process in the SNr implied less complex dynamics of neuronal discharges. If spike classification was not used, the arrival time-based measures still produced statistical differences among STN subdivisions and SNr, but the ISI-based measures only showed significant differences between motor and non-motor STN. Arrival time-based measures are less affected by spike misclassifications, and may be used as an adjunct for the identification of the STN during microelectrode targeting.
机译:丘脑底核(STN)的深部脑刺激(DBS)已用于缓解帕金森氏病的症状。在图像引导的立体定向手术期间,微电极记录的信号用于区分STN与邻近区域,特别是与黑质网状组织(SNr)。通常使用基于钉间间隔(ISI)的神经元放电模式。在本研究中,采用了基于到达时间的度量,包括Lempel-Ziv复杂度和Poisson偏离指数。我们的结果表明,非运动STN,运动STN和SNr之间基于到达时间的度量存在显着差异,并且比基于ISI的度量具有更好的区分度。 SNr中与Poisson过程的偏差较大,意味着神经元放电的动力学较不复杂。如果不使用峰值分类,则基于到达时间的测度仍会在STN细分和SNr之间产生统计差异,但基于ISI的测度仅显示运动和非运动STN之间的显着差异。基于到达时间的度量受尖峰错误分类的影响较小,可以用作微电极靶向过程中STN识别的辅助手段。

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