Theoretical Neuroscience Group, Laboratoire Mouvement & Perception UMR6152 CNRS, F-13288, Marseille, France,
Cogn Neurodyn. 2008 Mar;2(1):29-38. doi: 10.1007/s11571-007-9030-0. Epub 2007 Oct 16.
We study spike-burst neural activity and investigate its transitions to synchronized states under electrical coupling. Our reported results include the following: (1) Synchronization of spike-burst activity is a multi-time scale phenomenon and burst synchrony is easier to achieve than spike synchrony. (2) Synchrony of networks with time-delayed connections can be achieved at lower coupling strengths than within the same network with instantaneous couplings. (3) The introduction of parameter dispersion into the network destroys the existence of synchrony in the strict sense, but the network dynamics in major regimes of the parameter space can still be effectively captured by a mean field approach if the couplings are excitatory. Our results on synchronization of spiking networks are general of nature and will aid in the development of minimal models of neuronal populations. The latter are the building blocks of large scale brain networks relevant for cognitive processing.
我们研究了尖峰-爆发神经活动，并在电耦合下研究了其向同步状态的转变。我们的研究结果包括：（1）尖峰-爆发活动的同步是一个多时间尺度的现象，爆发同步比尖峰同步更容易实现；（2）具有时滞连接的网络的同步可以在比具有瞬时连接的相同网络更低的耦合强度下实现；（3）在网络中引入参数分散会破坏严格意义上的同步的存在，但如果耦合是兴奋性的，那么在参数空间的主要区域中，网络动力学仍然可以通过平均场方法有效地捕捉。我们关于尖峰网络同步的结果具有普遍性，将有助于发展神经元群体的最小模型。后者是与认知处理相关的大规模脑网络的构建块。
