In quest of the missing neuron: Spike sorting based on dominant-sets clustering

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• 作者：Dimitrios A. Adamos^a ; ^{dadam@bio.auth.gr} ; ^{d.adamos@ieee.org} ; Nikolaos A. Laskaris^b ; ^{laskaris@aiia.csd.auth.gr} ; Efstratios K. Kosmidis^c ; ^{kosmidef@med.auth.gr} ; George Theophilidis^a ; ^{theophil@bio.auth.gr}
• 关键词：Sparsely-firing neuron ; Graph-theoretic clustering ; ISOMAP ; Dominant sets
• 刊名：Computer Methods and Programs in Biomedicine
• 出版年：2012
• 期刊代码：68_01692607
• 类别：med
• 出版时间：July, 2012
• 卷：107
• 期：1
• 页码：28-35
• 文件大小：813 K

摘要

Spike sorting algorithms aim at decomposing complex extracellular signals to independent events from single neurons in the electrode's vicinity. The decision about the actual number of active neurons is still an open issue, with sparsely firing neurons and background activity the most influencing factors. We introduce a graph-theoretical algorithmic procedure that successfully resolves this issue. Dimensionality reduction coupled with a modern, efficient and progressively executable clustering routine proved to achieve higher performance standards than popular spike sorting methods. Our method is validated extensively using simulated data for different levels of SNR.