Spike sorting based on multi-class support vector machine with superposition resolution
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A new spike sorting method based on the support vector machine (SVM) is proposed to resolve the superposition problem. The spike superposition is generally resolved by the template matching. Previous template matching methods separate the spikes through linear classifiers. The classification performance is severely influenced by the background noise included in spike trains. The nonlinear classifiers with high generation ability are required to deal with the task. A multi-class SVM classifier is therefore applied to separate the spikes, which contains several binary SVM classifiers. Every binary SVM classifier corresponding to one spike class is used to identify the single and superposition spikes. The superposition spikes are decomposed through template extraction. The experimental results on the simulated and real data demonstrate the utility of the proposed method.
KeywordsSpike sorting Template matching Multi-class Support vector machine Extracellular recording
This study is supported by the National Natural Science Foundation of China (Grant No. 60574038) and the Specialized Research Fund for the Doctoral Program of Higher Education China (Grant No.20060248015).
- 5.Chen AH, Zhou Y, Gong HQ, Liang PJ (2003) Chicken retinal ganglion cells response characteristics: multi-channel electrode recording study. Sci China Ser C 33:82–88Google Scholar
- 6.Cristianini N, Shawe-Taylor J (2000) An introduction to support vector machines. Cambridge University Press, CambridgeGoogle Scholar
- 7.Fee MS, Mitra PP, Kleinfeld D (1996) Variability of extracellular spike waveforms of cortical neurons. J Neurophysiol 76:3823–3833Google Scholar
- 8.Harris KD, Henze DA, Csicsvari J, Hirase H (2000) Accuracy of tetrode spike separation as determined by simultaneous intracellular and extracellular measurements. J Neurophysiol 84:401–414Google Scholar
- 20.Vogelstein RJ, Murari K, Thakur PH, Cauwenberghs G, Chakrabartty S, Diehl C (2004) Spike sorting with support vector machines. In: Proceedings of 26th annual international conference on IEEE engineering in medicine and biology societyGoogle Scholar