Correlated transition between two activity states of neurons.
Correlated transition between two activity states of neurons.
复制标题
神经元两种活动状态之间的相关转换。
DOI：
10.1103/physreve.73.031910
复制
发表时间：
2006
期刊：
影响因子：
--
通讯作者：
M. Tanifuji
中科院分区：
文献类型：
--
作者：
G. Uchida;M. Fukuda;M. Tanifuji
为了理解神经网络的动态特性，表征网络中两个神经元的脉冲序列之间的关系是很重要的。在本研究中，我们发现在猕猴下颞叶皮层的一些神经元对中，一对神经元的脉冲序列用二维泊松过程来描述，其均值由普通的两态马尔可夫过程调节。常见的两态马尔可夫过程描述了一对组成神经元的放电和非放电状态之间的相关状态转换。
In order to understand the dynamical properties of a neural network, it is important to characterize the relation between spike trains of two neurons in the network. In this study, we show that in some neuron pairs in inferior temporal cortices of macaque monkeys, spike trains of a pair are described by a two-dimensional Poisson process whose means are modulated by a common two-state Markov process. The common two-state Markov process describes a correlated state transition between firing and nonfiring states of the constituent neurons of the pair.