Medición de correlación en Trenes de Espigas con Coeficientes Estadísticos no- Paramétricos (Measuring Spike Train Correlation with Non-Parametric Statistics Coefficient)

Jorge Soletta (jorge.soletta@gmail.com)1, Fernando Farfán (ffarfán@herrera.unt.edu.ar)2, Carmelo Felice (cfelice@herrera.unt.edu.ar)2


1Laboratorio de Medios e Interfases (LAMEIN), Universidad Nacional de Tucumán, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)
2Laboratorio de Medios e Interfases (LAMEIN), Universidad Nacional de Tucumán, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET

This paper appears in: Revista IEEE América Latina

Publication Date: Dec. 2015
Volume: 13,   Issue: 12 
ISSN: 1548-0992


Abstract:
Measure correlation between spike trains is a fundamental step for the study of neural systems. There are many alternatives to measure correlation, but not all possess the required properties. In this paper we propose to use non-parametric coefficients of correlation, coefficients Spearman and Kendall. To analyze their properties were generated computationally trains of spikes that simulate different experimental conditions, then the proposed coefficients were calculated and compared with the Pearson coefficient. The results show that under certain experimental conditions Kendall coefficient is more appropriate to quantify correlations between spikes trains

Index Terms:
Neural Correlation, Spike Train, Kendall Coefficient, Spearman Coefficient   


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