Predicting neuronal activity with simple models of the threshold type:: Adaptive Exponential Integrate-and-Fire model with two compartments

被引:50
|
作者
Clopath, Claudia [1 ]
Jolivet, Renaud
Rauch, Alexander
Luescher, Hans-Rudolf
Gerstner, Wulfram
机构
[1] Ecole Polytech Fed Lausanne, Sch Comp & Commun Sci, CH-1015 Lausanne, Switzerland
[2] Ecole Polytech Fed Lausanne, Brain Mind Inst, CH-1015 Lausanne, Switzerland
[3] Max Planck Inst Biol Cybernet, D-72012 Tubingen, Germany
[4] Univ Bern, Inst Physiol, CH-3012 Bern, Switzerland
关键词
adaptation; Exponential Integrate-and-Fire; neuron; spike timing;
D O I
10.1016/j.neucom.2006.10.047
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An adaptive Exponential Integrate-and-Fire (aEIF) model was used to predict the activity of layer-V-pyramidal neurons of rat neocortex under random current injection. A new protocol has been developed to extract the parameters of the aEIF model using an optimal filtering technique combined with a black-box numerical optimization. We found that the aEIF model is able to accurately predict both subthreshold fluctuations and the exact timing of spikes, reasonably close to the limits imposed by the intrinsic reliability of pyramidal neurons. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:1668 / 1673
页数:6
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