Okujeni Samora, Kandler Steffen, Egert Ulrich
Bernstein Center Freiburg and
Biomicrotechnology, IMTEK-Department of Microsystems Engineering, University of Freiburg, 79110 Freiburg, Germany.
J Neurosci. 2017 Apr 5;37(14):3972-3987. doi: 10.1523/JNEUROSCI.2552-16.2017. Epub 2017 Mar 14.
Spontaneous activity in the absence of external input, including propagating waves of activity, is a robust feature of neuronal networks and The neurophysiological and anatomical requirements for initiation and persistence of such activity, however, are poorly understood, as is their role in the function of neuronal networks. Computational network studies indicate that clustered connectivity may foster the generation, maintenance, and richness of spontaneous activity. Since this mesoscale architecture cannot be systematically modified in intact tissue, testing these predictions is impracticable Here, we investigate how the mesoscale structure shapes spontaneous activity in generic networks of rat cortical neurons In these networks, neurons spontaneously arrange into local clusters with high neurite density and form fasciculating long-range axons. We modified this structure by modulation of protein kinase C, an enzyme regulating neurite growth and cell migration. Inhibition of protein kinase C reduced neuronal aggregation and fasciculation of axons, i.e., promoted uniform architecture. Conversely, activation of protein kinase C promoted aggregation of neurons into clusters, local connectivity, and bundling of long-range axons. Supporting predictions from theory, clustered networks were more spontaneously active and generated diverse activity patterns. Neurons within clusters received stronger synaptic inputs and displayed increased membrane potential fluctuations. Intensified clustering promoted the initiation of synchronous bursting events but entailed incomplete network recruitment. Moderately clustered networks appear optimal for initiation and propagation of diverse patterns of activity. Our findings support a crucial role of the mesoscale architectures in the regulation of spontaneous activity dynamics. Computational studies predict richer and persisting spatiotemporal patterns of spontaneous activity in neuronal networks with neuron clustering. To test this, we created networks of varying architecture Supporting these predictions, the generation and spatiotemporal patterns of propagation were most variable in networks with intermediate clustering and lowest in uniform networks. Grid-like clustering, on the other hand, facilitated spontaneous activity but led to degenerating patterns of propagation. Neurons outside clusters had weaker synaptic input than neurons within clusters, in which increased membrane potential fluctuations facilitated the initiation of synchronized spike activity. Our results thus show that the intermediate level organization of neuronal networks strongly influences the dynamics of their activity.
在没有外部输入的情况下的自发活动，包括活动的传播波，是神经网络的一个显著特征。然而，对于这种活动的起始和持续存在的神经生理学和解剖学要求，以及它们在神经网络功能中的作用，人们了解得还很少。计算网络研究表明，集群连接性可能促进自发活动的产生、维持和丰富性。由于这种中尺度结构在完整组织中无法系统地改变，因此测试这些预测是不切实际的。在这里，我们研究中尺度结构如何塑造大鼠皮层神经元通用网络中的自发活动。在这些网络中，神经元自发地排列成具有高神经突密度的局部集群，并形成成束的长距离轴突。我们通过调节蛋白激酶C来改变这种结构，蛋白激酶C是一种调节神经突生长和细胞迁移的酶。抑制蛋白激酶C可减少神经元聚集和轴突成束，即促进均匀结构。相反，激活蛋白激酶C可促进神经元聚集成簇、局部连接以及长距离轴突的束化。支持理论预测的是，集群网络更具自发活性，并产生多样的活动模式。集群内的神经元接受更强的突触输入，并表现出膜电位波动增加。强化集群促进了同步爆发事件的起始，但导致网络募集不完全。适度集群的网络似乎最适合多种活动模式的起始和传播。我们的研究结果支持中尺度结构在调节自发活动动态方面的关键作用。计算研究预测，具有神经元集群的神经网络中自发活动的时空模式更丰富且持续存在。为了验证这一点，我们创建了不同结构的网络。支持这些预测的是，传播的产生和时空模式在具有中等集群的网络中变化最大，而在均匀网络中最低。另一方面，网格状集群促进了自发活动，但导致传播模式退化。集群外的神经元比集群内的神经元具有较弱的突触输入，其中膜电位波动增加促进了同步尖峰活动的起始。因此，我们的结果表明，神经网络的中间层次组织强烈影响其活动的动态。
