Jump-diffusion processes as models for neuronal activity
Jump-diffusion processes as models for neuronal activity
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DOI：
10.1016/0303-2647(96)01632-2
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发表时间：
1997-01-01
期刊：
影响因子：
1.6
通讯作者：
Sacerdote, L
中科院分区：
文献类型：
--
作者：
Giraudo, MT;Sacerdote, L
为了改进现有的神经元模型，我们考虑连续扩散和泊松时间分布脉冲序列的叠加所产生的混合过程，并将我们的注意力集中在放电时间的时刻。特别是，我们考虑三种不同的情况：大跳跃模型，其中每次跳跃都会引起神经元放电，重置模型的特征是向静息电位跳跃，以及更一般的模型，其中恒定幅度的兴奋性和抑制性跳跃叠加在扩散上。通过借助于分析论证和数值计算，概述了所考虑模型的主要行为差异。
Aiming at an improvement of the existing neuronal models, we consider a mixed process ensuing from the superposition of continuous diffusions and of Poisson time-distributed sequence of impulses and focus our attention on the moments of the firing time. In particular, we consider three different instances: the large jumps model in which each jump causes the neuron firing, the reset model characterized by jumps towards the resting potential and a more general model where constant amplitude excitatory and inhibitory jumps are superimposed on diffusion. By resorting to analytical arguments and to numerical computations, the main behavioral differences of the considered models are outlined.