Synchronous and asynchronous bursting states: role of intrinsic neural dynamics
Synchronous and asynchronous bursting states: role of intrinsic neural dynamics
复制标题
DOI：
10.1007/s10827-007-0027-9
复制
发表时间：
2007-10-01
影响因子：
1.2
通讯作者：
Fukai, Tomoki
中科院分区：
文献类型：
--
作者：
Takekawa, Takashi;Aoyagi, Toshio;Fukai, Tomoki
在各种认知任务中，诸如局部场电位的脑信号通常显示伽马波段振荡（30-70 Hz）。这些振荡活动可能反映了参与认知功能的细胞集合体的同步。一种锥体神经元，即，震颤神经元在γ频率范围内表现出快速节律爆发（FRB），并且可能在大脑皮层中产生γ带振荡中起积极作用。我们以前的相位响应分析表明，耦合爆发神经元之间的同步显着依赖于爆发模式，定义为在每个突发的尖峰的数量。也就是说，通过Ca 2+停止依赖机制爆发的神经元网络表现出同步和异步放电状态之间的急剧转变，当神经元在单线态、双线态等之间转换爆发模式时，然而，是否广泛的爆发神经元模型普遍表现出这样的网络行为尚不清楚。在这里，我们使用数学上易于处理的神经元模型来分析这种网络行为的机制。然后，我们将我们的结果扩展到NaP电流为基础的神经元模型的多室版本，并证明了在这个模型中的突发模式的变化和网络状态的变化之间的类似的紧密关系。因此，同步行为紧密耦合到一个广泛的一类网络的爆发模式的爆发神经元。
Brain signals such as local field potentials often display gamma-band oscillations (30-70 Hz) in a variety of cognitive tasks. These oscillatory activities possibly reflect synchronization of cell assemblies that are engaged in a cognitive function. A type of pyramidal neurons, i.e., chattering neurons, show fast rhythmic bursting (FRB) in the gamma frequency range, and may play an active role in generating the gamma-band oscillations in the cerebral cortex. Our previous phase response analyses have revealed that the synchronization between the coupled bursting neurons significantly depends on the bursting mode that is defined as the number of spikes in each burst. Namely, a network of neurons bursting through a Ca2+ stop-dependent mechanism exhibited sharp transitions between synchronous and asynchronous firing states when the neurons exchanged the bursting mode between singlet, doublet and so on. However, whether a broad class of bursting neuron models commonly show such a network behavior remains unclear. Here, we analyze the mechanism underlying this network behavior using a mathematically tractable neuron model. Then we extend our results to a multi-compartment version of the NaP current-based neuron model and prove a similar tight relationship between the bursting mode changes and the network state changes in this model. Thus, the synchronization behavior couples tightly to the bursting mode in a wide class of networks of bursting neurons.