Spike detection using the continuous wavelet transform
Spike detection using the continuous wavelet transform
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DOI：
10.1109/tbme.2004.839800
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发表时间：
2005-01-01
影响因子：
4.6
通讯作者：
Burdick, JW
中科院分区：
文献类型：
--
作者：
Nenadic, Z;Burdick, JW
将小波变换与基本检测理论相结合，提出了一种新的无监督噪声神经记录棘波检测与定位新方法。该方法不需要模板的构建或阈值的监督设置。我们提出了广泛的蒙特卡罗模拟，基于实际的细胞外记录，表明该技术在各种记录条件下都超过了其他常用的方法。我们进一步证明，与我们的方法相对应的错误检测的尖峰比其他技术(如幅度阈值)的假阳性更类似于实际的尖峰。此外，该方法的简单性允许近乎实时的执行。
This paper combines wavelet transforms with basic detection theory to develop a new unsupervised method for robustly detecting and localizing spikes in noisy neural recordings. The method does not require the construction of templates, or the supervised setting of thresholds. We present extensive Monte Carlo simulations, based on actual extracellular recordings, to show that this technique surpasses other commonly used methods in a wide variety of recording conditions. We further demonstrate that falsely detected spikes corresponding to our method resemble actual spikes more than the false positives of other techniques such as amplitude thresholding. Moreover, the simplicity of the metho allows for nearly real-time execution.