Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Terrassa, Spain; Neuroheuristic Research Group, Faculty of Business and Economics, University of Lausanne, Lausanne, Switzerland.
Neuroheuristic Research Group, Faculty of Business and Economics, University of Lausanne, Lausanne, Switzerland.
PLoS Comput Biol. 2015 Feb 11;11(2):e1004007. doi: 10.1371/journal.pcbi.1004007. eCollection 2015 Feb.
Neurons in the brain are known to operate under a careful balance of excitation and inhibition, which maintains neural microcircuits within the proper operational range. How this balance is played out at the mesoscopic level of neuronal populations is, however, less clear. In order to address this issue, here we use a coupled neural mass model to study computationally the dynamics of a network of cortical macrocolumns operating in a partially synchronized, irregular regime. The topology of the network is heterogeneous, with a few of the nodes acting as connector hubs while the rest are relatively poorly connected. Our results show that in this type of mesoscopic network excitation and inhibition spontaneously segregate, with some columns acting mainly in an excitatory manner while some others have predominantly an inhibitory effect on their neighbors. We characterize the conditions under which this segregation arises, and relate the character of the different columns with their topological role within the network. In particular, we show that the connector hubs are preferentially inhibitory, the more so the larger the node's connectivity. These results suggest a potential mesoscale organization of the excitation-inhibition balance in brain networks.
大脑中的神经元被认为是在兴奋和抑制的精细平衡下运作的，这种平衡使神经微电路保持在适当的工作范围内。然而，这种平衡在神经元群体的介观水平上是如何发挥作用的还不太清楚。为了解决这个问题，我们在这里使用一个耦合的神经质量模型，从计算上研究在部分同步、不规则状态下工作的皮质大柱网络的动力学。网络的拓扑结构是异构的，其中一些节点充当连接枢纽，而其余节点的连接则相对较差。我们的结果表明，在这种介观网络中，兴奋和抑制会自发地分离，一些柱主要以兴奋的方式作用，而另一些则对其邻居主要产生抑制作用。我们描述了这种分离出现的条件，并将不同柱的特性与其在网络中的拓扑作用联系起来。特别是，我们表明连接枢纽优先抑制，节点连接性越大，抑制作用越强。这些结果表明，大脑网络中的兴奋-抑制平衡可能存在潜在的介观组织。
