Han Ruixue, Wang Jiang, Yu Haitao, Deng Bin, Wei Xilei, Qin Yingmei, Wang Haixu
School of Electrical Engineering and Automation, Tianjin University, Tianjin, 300072, People's Republic of China.
School of Automation and Electrical Engineering, Tianjin University of Technology and Education Tianjin, Tianjin 300222, China.
Chaos. 2015 Apr;25(4):043108. doi: 10.1063/1.4917014.
Reliable signal propagation across distributed brain areas is an essential requirement for cognitive function, and it has been investigated extensively in computational studies where feed-forward network (FFN) is taken as a generic model. But it is still unclear how distinct local network states, which are intrinsically generated by synaptic interactions within each layer, would affect the ability of FFN to transmit information. Here we investigate the impact of such network states on propagating transient synchrony (synfire) and firing rate by a combination of numerical simulations and analytical approach. Specifically, local network dynamics is attributed to the competition between excitatory and inhibitory neurons within each layer. Our results show that concomitant with different local network states, the performance of signal propagation differs dramatically. For both synfire propagation and firing rate propagation, there exists an optimal local excitability state, respectively, that optimizes the performance of signal propagation. Furthermore, we find that long-range connections strongly change the dependence of spiking activity propagation on local network state and propose that these two factors work jointly to determine information transmission across distributed networks. Finally, a simple mean field approach that bridges response properties of long-range connectivity and local subnetworks is utilized to reveal the underlying mechanism.
可靠的信号在分布式脑区之间传播是认知功能的基本要求，并且在以前馈网络（FFN）作为通用模型的计算研究中已得到广泛研究。但是，尚不清楚由每层内的突触相互作用内在产生的不同局部网络状态将如何影响FFN传输信息的能力。在这里，我们通过数值模拟和分析方法相结合，研究了这种网络状态对传播瞬态同步（同步发放）和发放率的影响。具体而言，局部网络动力学归因于每层内兴奋性和抑制性神经元之间的竞争。我们的结果表明，伴随着不同的局部网络状态，信号传播的性能有显著差异。对于同步发放传播和发放率传播，分别存在一个最优的局部兴奋性状态，可优化信号传播的性能。此外，我们发现长程连接强烈改变了发放活动传播对局部网络状态的依赖性，并提出这两个因素共同作用以确定跨分布式网络的信息传输。最后，利用一种简单的平均场方法来连接长程连接和局部分子网的响应特性，以揭示潜在机制。
