Camp C, Pinsker H
Brain Res. 1979 Jun 29;169(3):455-79. doi: 10.1016/0006-8993(79)90397-4.
A practical and efficient off-line computer technique is described for automatically separating unitary waveforms from multiunit whole-nerve spike train data with no a priori knowledge about the number of units or their waveforms. The procedure requires two recording eletrodes which provide 3 measures on each putative unit: (1) peak-to-peak amplitude on the proximal channel, (2) amplitude on the distal channel, and (3) temporal offset (depends on conduction velocity) between proximal and distal spikes. On the basis of these 3 measurements, individual unitary spikes are automatically separated into clusters according to empirically-determined limits of variability. The results of the program are displayed in 3-D plots of the 3 measures on each unitary spike and in plots of superimposed waveforms from each cluster. These plots can be used to interactively correct clustering errors. The procedure is illustrated with a 1-min segment of spike train data recorded in vivo from the siphon nerve of a freely-behaving Aplysia. We routinely obtain about 10 relatively well-isolated units in such segments. By utilizing the average waveforms and conduction velocities for individual clusters, it may eventually be possible to separate unitary spikes from compound waveforms resulting from simultaneous of two or more units.
本文描述了一种实用且高效的离线计算机技术，可在无需事先了解单元数量或其波形的情况下，自动从多单元全神经尖峰序列数据中分离出单一波形。该过程需要两个记录电极，它们对每个假定单元提供三种测量：（1）近端通道上的峰峰值幅度，（2）远端通道上的幅度，以及（3）近端和远端尖峰之间的时间偏移（取决于传导速度）。基于这三种测量，根据经验确定的变异性限制，将单个单一尖峰自动分离成簇。该程序的结果以每个单一尖峰的三种测量的三维图以及每个簇的叠加波形图显示。这些图可用于交互式校正聚类错误。通过记录自由活动的海兔虹吸神经体内1分钟的尖峰序列数据片段来说明该过程。我们通常在这样的片段中获得大约10个相对分离良好的单元。通过利用各个簇的平均波形和传导速度，最终有可能从两个或更多单元同时活动产生的复合波形中分离出单一尖峰。
