Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
IEEE Trans Biomed Eng. 2010 Jun;57(6):1297-305. doi: 10.1109/TBME.2009.2039213. Epub 2010 Feb 17.
Placement of deep brain stimulating electrodes in the subthalamic nucleus (STN) to treat Parkinson's disease (PD) also allows the recording of single neuron spiking activity. Analyses of these unique data offer an important opportunity to better understand the pathophysiology of PD. Despite the point process nature of PD neural spiking activity, point process methods are rarely used to analyze these recordings. We develop a point process representation of PD neural spiking activity using a generalized linear model to describe long- and short-term temporal dependencies in the spiking activity of 28 STN neurons from seven PD patients and 35 neurons from one healthy primate (surrogate control) recorded, while the subjects executed a directed-hand movement task. We used the point process model to characterize each neuron's bursting, oscillatory, and directional tuning properties during key periods in the task trial. Relative to the control neurons, the PD neurons showed increased bursting, increased 10-30 Hz oscillations, and increased fluctuations in directional tuning. These features, which traditional methods failed to capture accurately, were efficiently summarized in a single model in the point process analysis of each neuron. The point process framework suggests a useful approach for developing quantitative neural correlates that may be related directly to the movement and behavioral disorders characteristic of PD.
在丘脑底核 (STN) 中放置深部脑刺激电极以治疗帕金森病 (PD) 也允许记录单个神经元的尖峰活动。对这些独特数据的分析为更好地了解 PD 的病理生理学提供了重要机会。尽管 PD 神经尖峰活动具有点过程性质,但很少使用点过程方法来分析这些记录。我们使用广义线性模型对点过程表示 PD 神经尖峰活动进行了开发,以描述 7 名 PD 患者的 28 个 STN 神经元和 1 个健康灵长类动物(替代对照)的 35 个神经元的尖峰活动中的长短期时间依赖性,同时记录了这些神经元。被试执行定向手部运动任务。我们使用点过程模型来描述每个神经元在任务试验关键时期的爆发、振荡和方向调谐特性。与对照神经元相比,PD 神经元显示出爆发增加、10-30 Hz 振荡增加和方向调谐波动增加。这些特征是传统方法无法准确捕捉到的,在每个神经元的点过程分析中,这些特征都可以通过单个模型进行高效总结。点过程框架为开发可能与 PD 运动和行为障碍直接相关的定量神经相关性提供了一种有用的方法。