Mathematical models help the analysis of experimental data and the understanding of observed features. Two examples are discussed with reference to neuronal modeling to suggest different applications of stochastic leaky integrate and fire models. The first one allows to explain the existence of preferential spiking times while the second suggests a classification method for simultaneous recorded data.
Stochastic leaky integrate and fire neuronal model: examples of its application to neuronal coding study
SACERDOTE, Laura Lea;SIROVICH, ROBERTA;ZUCCA, CRISTINA
2005-01-01
Abstract
Mathematical models help the analysis of experimental data and the understanding of observed features. Two examples are discussed with reference to neuronal modeling to suggest different applications of stochastic leaky integrate and fire models. The first one allows to explain the existence of preferential spiking times while the second suggests a classification method for simultaneous recorded data.
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