期刊
JOURNAL OF NEUROSCIENCE METHODS
卷 165, 期 2, 页码 165-174出版社
ELSEVIER
DOI: 10.1016/j.jneumeth.2007.05.033
关键词
spike detection; spike discrimination; extracellular neuronal recordings; spike train; action potential; matched filter; eigenfilter; threshold selection
Recordings of extracellular neural activity are used in many clinical applications and scientific studies. In most cases, these signals are analyzed as a point process, and a spike detection algorithm is required to estimate the times at which action potentials occurred. Recordings from high-density microelectrode arrays (MEAs) and low-impedance ruicroelectrodes often have a low signal-to-noise ratio (SNR < 10) and contain action potentials from more than one neuron. We describe a new detection algorithm based on template matching that only requires the user to specify the minimum and maximum firing rates of the neurons. The algorithm iteratively estimates the morphology of the most prominent action potentials. It is able to achieve a sensitivity of > 90% with a false positive rate of < 5 Hz in recordings with an estimated SNR = 3, and it performs better than an optimal threshold detector in recordings with an estimated SNR > 2.5. (c) 2007 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据