Department of Electrical Engineering, Chang Gung University, Taoyuan, Taiwan.
Brain Res Bull. 2010 Apr 5;81(6):534-42. doi: 10.1016/j.brainresbull.2010.01.001. Epub 2010 Jan 7.
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.
深部脑刺激（DBS）核STN 的(subthalamic nucleus) 已被用于减轻帕金森病的症状。在图像引导的立体定向手术中，使用微电极记录的信号来区分 STN 与相邻区域，特别是与黑质网状部（SNr）区分。基于 interspike intervals (ISI) 的神经元放电模式通常被使用。在本研究中，使用了基于到达时间的测量方法，包括 Lempel-Ziv 复杂度和偏离泊松指数。我们的结果表明，在非运动 STN、运动 STN 和 SNr 之间，基于到达时间的测量方法存在显著差异，并且比基于 ISI 的测量方法具有更好的区分能力。SNr 中偏离泊松过程的较大偏差意味着神经元放电的动态过程不那么复杂。如果不使用尖峰分类，基于到达时间的测量方法仍然可以在 STN 细分和 SNr 之间产生统计学差异，但基于 ISI 的测量方法仅显示运动和非运动 STN 之间的显著差异。基于到达时间的测量方法受尖峰分类错误的影响较小，可作为微电极靶向时识别 STN 的辅助手段。
