Errors in estimation of the input signal for integrate-and-fire neuronal models

被引：9

作者：

Bibbona, Enrico ^{[1
,2
]}

Lansky, Petr ^{[3
]}

Sacerdote, Laura ^{[2
,4
]}

Sirovich, Roberta ^{[2
]}

机构：

[1] INRIM, I-10135 Turin, Italy

[2] Univ Turin, Dept Math, I-10123 Turin, Italy

[3] Acad Sci Czech Republ, Inst Physiol, CR-14220 Prague 4, Czech Republic

[4] NIT, I-10123 Turin, Italy

来源：

PHYSICAL REVIEW E | 2008年 / 78卷 / 01期

关键词：

D O I：

10.1103/PhysRevE.78.011918

中图分类号：

O35 [流体力学]; O53 [等离子体物理学];

学科分类号：

070204 ; 080103 ; 080704 ;

摘要：

Estimation of the input parameters of stochastic (leaky) integrate-and-fire neuronal models is studied. It is shown that the presence of a firing threshold brings a systematic error to the estimation procedure. Analytical formulas for the bias are given for two models, the randomized random walk and the perfect integrator. For the third model considered, the leaky integrate-and-fire model, the study is performed by using Monte Carlo simulated trajectories. The bias is compared with other errors appearing during the estimation, and it is documented that the effect of the bias has to be taken into account in experimental studies.

引用

页数：10

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