基于电导的积分发放神经元网络的福克-普朗克描述
Fokker-Planck description of conductance-based integrate-and-fire neuronal networks.
作者信息
Kovacic Gregor, Tao Louis, Rangan Aaditya V, Cai David
机构信息
Department of Mathematical Sciences, Rensselaer Polytechnic Institute, Troy, New York 12180, USA.
出版信息
Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Aug;80(2 Pt 1):021904. doi: 10.1103/PhysRevE.80.021904. Epub 2009 Aug 6.
Steady dynamics of coupled conductance-based integrate-and-fire neuronal networks in the limit of small fluctuations is studied via the equilibrium states of a Fokker-Planck equation. An asymptotic approximation for the membrane-potential probability density function is derived and the corresponding gain curves are found. Validity conditions are discussed for the Fokker-Planck description and verified via direct numerical simulations.
通过福克 - 普朗克方程的平衡态，研究了在小波动极限下基于电导耦合的积分发放神经元网络的稳定动力学。推导了膜电位概率密度函数的渐近近似，并找到了相应的增益曲线。讨论了福克 - 普朗克描述的有效性条件，并通过直接数值模拟进行了验证。
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