Growth rules for the repair of Asynchronous Irregular neuronal networks after peripheral lesions.
Growth rules for the repair of Asynchronous Irregular neuronal networks after peripheral lesions.
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DOI：
10.1371/journal.pcbi.1008996
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发表时间：
2021-06
影响因子：
4.3
通讯作者：
Steuber V
中科院分区：
文献类型：
--
作者：
Sinha A;Metzner C;Davey N;Adams R;Schmuker M;Steuber V
几种自我平衡机制使大脑能够维持所需的神经元活动水平。其中之一，稳态结构可塑性，已报告恢复活动的网络破坏外周病变，通过改变他们的神经元连接。虽然多个损伤实验已经研究了神经突形态的变化，这些变化是这些网络中突触修饰的基础，但驱动这些变化的潜在机制尚未得到解释。有证据表明，神经元活动调节神经突形态，并可能刺激神经突选择性发芽或回缩，以恢复网络活动水平。我们开发了一个新的尖峰网络模型的外周损伤和准确地再现了网络修复的特点，在实验中报告，以研究活动依赖的生长机制的神经突去传入。为了确保我们的模拟与大脑中的网络行为非常相似，我们在一个生物现实的平衡网络模型中对传入神经阻滞进行建模，该模型表现出在大脑皮层中观察到的低频异步不规则（AI）活动。我们的模拟结果表明，重建活动的神经元内和外的剥夺区域，病变投射区（LPZ），需要相反的活动依赖的兴奋性和抑制性突触后元件的增长规则。对这些生长机制的分析表明，它们也有助于维持单个神经元的活性水平。此外，在我们的模型中，在实验中观察到的突触的定向形成需要突触前兴奋性和抑制性元件也遵循相反的生长规则。最后，我们观察到，我们提出的结构可塑性增长规则和抑制性突触可塑性机制也平衡了我们的AI网络，这两个机制都有助于将网络恢复到去传入神经前的稳定活动水平。越来越多的证据表明，我们的大脑可以通过神经元回路的自适应重新布线来补偿外周损伤。潜在的过程，结构可塑性，可以修改大脑中神经元网络的连接，从而影响它们的功能。为了更好地理解大脑结构可塑性的机制，我们开发了一种新的外周病变模型，并在简化的平衡皮质网络模型中产生了活动依赖性重新布线，该模型表现出生物学上真实的异步不规则（AI）活动。为了准确地再现在外周损伤实验中观察到的损伤后网络重新布线的方向性和过程，我们推导出不同突触元件的活动依赖性生长规则：树突和轴突接触。我们的模拟结果表明，兴奋性和抑制性突触元件必须以相反的方式对神经元活动的变化做出反应。我们表明，这些规则导致个体神经元活动的稳态稳定。在我们的模拟中，突触和结构可塑性机制都有助于网络修复。此外，我们的模拟表明，虽然恢复活动的神经元被剥夺的外周病变，网络的时间放电特性可能不会保留的重新布线过程。
Several homeostatic mechanisms enable the brain to maintain desired levels of neuronal activity. One of these, homeostatic structural plasticity, has been reported to restore activity in networks disrupted by peripheral lesions by altering their neuronal connectivity. While multiple lesion experiments have studied the changes in neurite morphology that underlie modifications of synapses in these networks, the underlying mechanisms that drive these changes are yet to be explained. Evidence suggests that neuronal activity modulates neurite morphology and may stimulate neurites to selective sprout or retract to restore network activity levels. We developed a new spiking network model of peripheral lesioning and accurately reproduced the characteristics of network repair after deafferentation that are reported in experiments to study the activity dependent growth regimes of neurites. To ensure that our simulations closely resemble the behaviour of networks in the brain, we model deafferentation in a biologically realistic balanced network model that exhibits low frequency Asynchronous Irregular (AI) activity as observed in cerebral cortex. Our simulation results indicate that the re-establishment of activity in neurons both within and outside the deprived region, the Lesion Projection Zone (LPZ), requires opposite activity dependent growth rules for excitatory and inhibitory post-synaptic elements. Analysis of these growth regimes indicates that they also contribute to the maintenance of activity levels in individual neurons. Furthermore, in our model, the directional formation of synapses that is observed in experiments requires that pre-synaptic excitatory and inhibitory elements also follow opposite growth rules. Lastly, we observe that our proposed structural plasticity growth rules and the inhibitory synaptic plasticity mechanism that also balances our AI network both contribute to the restoration of the network to pre-deafferentation stable activity levels. An accumulating body of evidence suggests that our brain can compensate for peripheral lesions by adaptive rewiring of its neuronal circuitry. The underlying process, structural plasticity, can modify the connectivity of neuronal networks in the brain, thus affecting their function. To better understand the mechanisms of structural plasticity in the brain, we have developed a novel model of peripheral lesions and the resulting activity-dependent rewiring in a simplified balanced cortical network model that exhibits biologically realistic Asynchronous Irregular (AI) activity. In order to accurately reproduce the directionality and course of network rewiring after injury that is observed in peripheral lesion experiments, we derive activity dependent growth rules for different synaptic elements: dendritic and axonal contacts. Our simulation results suggest that excitatory and inhibitory synaptic elements have to react to changes in neuronal activity in opposite ways. We show that these rules result in a homeostatic stabilisation of activity in individual neurons. In our simulations, both synaptic and structural plasticity mechanisms contribute to network repair. Furthermore, our simulations indicate that while activity is restored in neurons deprived by the peripheral lesion, the temporal firing characteristics of the network may not be retained by the rewiring process.
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