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

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.
Neuromat III: Computational Neurosciences
Milano
13-14 settembre 2004.
Industry days
Società Editrice Esculapio
204
214
9788874881093
Noisy Leaky Integrate and Fire; characteristic times; synchronization; first exit times; inverse first passage time
Sacerdote L.; Sirovich R.; Zucca C.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/13929
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