Di Nardo E, Nobile A G, Pirozzi E, Ricciardi L M
Dipartimento di Matematica, University of Basilicata, Potenza, Italy.
Biosystems. 1998 Sep-Dec;48(1-3):29-35. doi: 10.1016/s0303-2647(98)00047-1.
Single neuron's activity modeling is considered with reference to some earlier contributions in which a non-Markov Gaussian process is assumed to describe the time course of the neuron's membrane potential. After re-formulating the problem in a rigorous framework and pinpointing the limits of validity of such a model, the available results on the firing probability density are compared with those obtained by us by means of an ad hoc numerical algorithm implemented for the leaky integrator diffusion firing model and with some data constructed by a simulation procedure of non-Markov Gaussian processes with pre-assigned covariances. Throughout this paper, the notion of 'correlation time' plays a fundamental role for the neuronal coding process modeling.
本文参考了一些早期研究成果来考虑单个神经元的活动建模，这些研究假设非马尔可夫高斯过程来描述神经元膜电位的时间进程。在将该问题重新构建于一个严格框架并明确该模型有效性的限制之后，将关于发放概率密度的现有结果与我们通过为泄漏积分器扩散发放模型实现的特定数值算法所获得的结果，以及与通过具有预先设定协方差的非马尔可夫高斯过程模拟程序构建的一些数据进行比较。在整篇论文中，“相关时间”的概念在神经元编码过程建模中起着基础性作用。
