Department of Bioengineering, 254 Agricultural Engineering, Columbia, MO, USA; Dalton Cardiovascular Research Center, University of Missouri, Columbia, MO, USA.
Department of Bioengineering, 254 Agricultural Engineering, Columbia, MO, USA; Department of Medical Pharmacology and Physiology, 1 Hospital Dr., Columbia, MO, USA; Dalton Cardiovascular Research Center, University of Missouri, Columbia, MO, USA.
J Neurosci Methods. 2018 Jan 1;293:338-346. doi: 10.1016/j.jneumeth.2017.10.019. Epub 2017 Oct 20.
Electrochemical microelectrodes located immediately adjacent to the cell surface can detect spikes of amperometric current during exocytosis as the transmitter released from a single vesicle is oxidized on the electrode surface. Automated techniques to detect spikes are needed in order to quantify the spike rate as a measure of the rate of exocytosis.
We have developed a Matched Filter (MF) detection algorithm that scans the data set with a library of prototype spike templates while performing a least-squares fit to determine the amplitude and standard error. The ratio of the fit amplitude to the standard error constitutes a criterion score that is assigned for each time point and for each template. A spike is detected when the criterion score exceeds a threshold and the highest-scoring template and the time of peak score is identified. The search for the next spike commences only after the score falls below a second, lower threshold to reduce false positives. The approach was extended to detect spikes with double-exponential decays with the sum of two templates.
Receiver Operating Characteristic plots (ROCs) demonstrate that the algorithm detects >95% of manually identified spikes with a false-positive rate of ∼2%.
ROCs demonstrate that the MF algorithm performs better than algorithms that detect spikes based on a derivative-threshold approach.
The MF approach performs well and leads into approaches to identify spike parameters.
电化学微电极与细胞表面紧邻，可以在递质从单个囊泡释放并在电极表面氧化时检测到电化学电流的尖峰。需要开发自动化技术来检测尖峰，以便将尖峰率作为胞吐率的度量来量化。
我们开发了一种匹配滤波器 (MF) 检测算法，该算法使用原型尖峰模板库扫描数据集，同时进行最小二乘拟合以确定幅度和标准误差。拟合幅度与标准误差的比值构成每个时间点和每个模板的准则分数。当准则分数超过阈值且确定最高得分模板和得分峰值时间时，就会检测到尖峰。只有在分数降至第二个较低的阈值以下以减少误报后，才开始搜索下一个尖峰。该方法扩展到使用两个模板的和来检测具有双指数衰减的尖峰。
接收者操作特征曲线 (ROC) 表明，该算法可以检测到超过 95%的手动识别尖峰，假阳性率约为 2%。
ROC 表明，MF 算法比基于导数阈值方法检测尖峰的算法性能更好。
MF 方法性能良好，并可进一步确定尖峰参数。
