Spike sorting: Bayesian clustering of non-stationary data
Spike sorting: Bayesian clustering of non-stationary data
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DOI：
10.1016/j.jneumeth.2006.04.023
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发表时间：
2006-10-30
影响因子：
3
通讯作者：
Stark, Eran
中科院分区：
文献类型：
--
作者：
Bar-Hillel, Aharon;Spiro, Adam;Stark, Eran
锋电位分类涉及根据源神经元对微电极记录的锋电位进行聚类。这是一项复杂的任务，需要大量的人力，部分原因是数据的非平稳性。我们建议在贝叶斯框架中自动化聚类过程，将源神经元建模为非平稳高斯混合。在第一搜索阶段，将数据划分为短时间帧，并且针对每个帧分别计算作为高斯混合的数据的候选描述。在第二阶段，候选混合物之间的转移概率计算，并找到一个全局最优的聚类解决方案作为最大后验概率模型的解决方案。转移概率的计算使用本地平稳性假设，并基于高斯版本的詹森-香农发散。我们采用综合生成的尖峰数据来说明该方法，并表明它优于其他尖峰排序方法在非平稳的情况下。然后，我们使用真实的尖峰数据，并找到高协议的方法与专家人类分类器在两种模式下的操作：一个完全无监督和半监督模式。因此，这种方法在两个方面不同于其他方法：它能够解释非平稳数据。它接近人类的表现。(c)2006 Elsevier B.V.保留所有权利。
Spike sorting involves clustering spikes recorded by a micro-electrode according to the source neurons. It is a complicated task, which requires much human labor, in part due to the non-stationary nature of the data. We propose to automate the clustering process in a Bayesian framework, with the source neurons modeled as a non-stationary mixture-of-Gaussians. At a first search stage, the data are divided into short time frames, and candidate descriptions of the data as mixtures-of-Gaussians are computed for each frame separately. At a second stage, transition probabilities between candidate mixtures are computed, and a globally optimal clustering solution is found as the maximum-a-posteriori solution of the resulting probabilistic model. The transition probabilities are computed using local stationarity assumptions, and are based on a Gaussian version of the Jensen-Shannon divergence. We employ synthetically generated spike data to illustrate the method and show that it outperforms other spike sorting methods in a non-stationary scenario. We then use real spike data and find high agreement of the method with expert human sorters in two modes of operation: a fully unsupervised and a semi-supervised mode. Thus, this method differs from other methods in two aspects: its ability to account for non-stationary data. and its close to human performance. (c) 2006 Elsevier B.V. All rights reserved.