A novel unsupervised spike sorting implementation with variable number of features

被引：0
作者：
Chaure, F. J. [1 ,2 ,3 ,4 ]
Quiroga, Quian R. [2 ]
Kochen, S. S. [3 ]
Rey, H. G. [2 ]
机构：
[1] UBA, Inst Ingn Biomed, Caba, Argentina
[2] Univ Leicester, Ctr Syst Neurosci, Leicester, Leics, England
[3] CONICET Hosp El Cruce UNAJ, Estudios Neurociencias & Sistemas Complejos, Florencio Varela, Argentina
[4] UBA, Fac Med, Inst Biol Celular & Neurociencias Prof E De Rober, Caba, Argentina
来源：
2017 XVII WORKSHOP ON INFORMATION PROCESSING AND CONTROL (RPIC) | 2017年
关键词：
neurophysiology; signal processing; spike sorting; LARGE-SCALE; RECORDINGS; NEURONS;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We propose a new fully automatic spike sorting algorithm that is able to match, or even improve, the performance of semiautomatic solutions with supervised intervention from expert users. We achieved this by incorporating: 1) a set of heuristic criteria inspired by the expert actions following the solution from semiautomatic algorithms, and 2) an improved feature selection method that increases the number of units that can be isolated from a single electrode recording. We evaluated the performance of the proposed method with real and simulated data.
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页数：6
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