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物理障碍对神经元回路结构和有效连接性的影响

Impact of Physical Obstacles on the Structural and Effective Connectivity of Neuronal Circuits.

作者信息

Ludl Adriaan-Alexander, Soriano Jordi

机构信息

Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway.

Departament de Física de la Matèria Condensada, Universitat de Barcelona, Barcelona, Spain.

出版信息

Front Comput Neurosci. 2020 Aug 31;14:77. doi: 10.3389/fncom.2020.00077. eCollection 2020.

Abstract

Scaffolds and patterned substrates are among the most successful strategies to dictate the connectivity between neurons in culture. Here, we used numerical simulations to investigate the capacity of physical obstacles placed on a flat substrate to shape structural connectivity, and in turn collective dynamics and effective connectivity, in biologically-realistic neuronal networks. We considered μ-sized obstacles placed in mm-sized networks. Three main obstacle shapes were explored, namely crosses, circles and triangles of isosceles profile. They occupied either a small area fraction of the substrate or populated it entirely in a periodic manner. From the point of view of structure, all obstacles promoted short length-scale connections, shifted the in- and out-degree distributions toward lower values, and increased the modularity of the networks. The capacity of obstacles to shape distinct structural traits depended on their density and the ratio between axonal length and substrate diameter. For high densities, different features were triggered depending on obstacle shape, with crosses trapping axons in their vicinity and triangles funneling axons along the reverse direction of their tip. From the point of view of dynamics, obstacles reduced the capacity of networks to spontaneously activate, with triangles in turn strongly dictating the direction of activity propagation. Effective connectivity networks, inferred using transfer entropy, exhibited distinct modular traits, indicating that the presence of obstacles facilitated the formation of local effective microcircuits. Our study illustrates the potential of physical constraints to shape structural blueprints and remodel collective activity, and may guide investigations aimed at mimicking organizational traits of biological neuronal circuits.

摘要

支架和图案化基质是在培养中控制神经元之间连接性的最成功策略之一。在这里,我们使用数值模拟来研究放置在平坦基质上的物理障碍物在生物现实神经元网络中塑造结构连接性的能力,进而塑造集体动力学和有效连接性。我们考虑了放置在毫米级网络中的微米级障碍物。探索了三种主要的障碍物形状,即十字形、圆形和等腰三角形。它们要么占据基质的一小部分面积,要么以周期性方式完全填充基质。从结构的角度来看,所有障碍物都促进了短长度尺度的连接,将入度和出度分布向较低值移动,并增加了网络的模块化程度。障碍物塑造不同结构特征的能力取决于它们的密度以及轴突长度与基质直径之间的比率。对于高密度情况,根据障碍物形状会触发不同的特征,十字形会将轴突捕获在其附近,而三角形会使轴突沿着其尖端的相反方向汇聚。从动力学的角度来看,障碍物降低了网络自发激活的能力,三角形则强烈地决定了活动传播的方向。使用转移熵推断的有效连接性网络表现出不同的模块化特征,表明障碍物的存在促进了局部有效微电路的形成。我们的研究说明了物理约束在塑造结构蓝图和重塑集体活动方面的潜力,并可能指导旨在模拟生物神经元回路组织特征的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/98ce/7488194/8741cf6c4321/fncom-14-00077-g0001.jpg

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