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Double sliding-window technique: a new method to calculate the neuronal response onset latency.

机译:双滑窗技术:一种计算神经元反应发作潜伏期的新方法。

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摘要

Neuronal response onset latency provides important data on the information processing within the central nervous system. In order to enhance the quality of the onset latency estimation, we have developed a 'double sliding-window' technique, which combines the advantages of mathematical methods with the reliability of standard statistical processes. This method is based on repetitive series of statistical probes between two virtual time windows. The layout of the significance curve reveals the starting points of changes in neuronal activity in the form of break-points between linear segments. A second-order difference function is applied to determine the position of maximum slope change, which corresponds to the onset of the response. In comparison with Poisson spike-train analysis, the cumulative sum technique and the method of Falzett et al., this 'double sliding-window, technique seems to be a more accurate automated procedure to calculate the response onset latency of a broad range of neuronal response characteristics.
机译:神经元反应发作潜伏期提供了有关中枢神经系统内信息处理的重要数据。为了提高发病潜伏期估计的质量,我们开发了一种“双重滑动窗口”技术,该技术结合了数学方法的优势和标准统计过程的可靠性。此方法基于两个虚拟时间窗口之间重复的统计探测序列。显着性曲线的布局以线性段之间的断点的形式揭示了神经元活动变化的起点。应用二阶差分函数来确定最大斜率变化的位置,该位置对应于响应的开始。与Poisson峰值训练分析,累积和技术以及Falzett等人的方法相比,这种“双滑动窗口”技术似乎是一种更准确的自动化程序,可以计算各种神经元的反应开始潜伏期响应特征。

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