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Generation of Granule Cell Dendritic Morphologies by Estimating the Spatial Heterogeneity of Dendritic Branching
Frontiers in Computational Neuroscience ( IF 3.2 ) Pub Date : 2020-04-09 , DOI: 10.3389/fncom.2020.00023
Zane Z Chou 1 , Gene J Yu 1 , Theodore W Berger 1
Affiliation  

Biological realism of dendritic morphologies is important for simulating electrical stimulation of brain tissue. By adding point process modeling and conditional sampling to existing generation strategies, we provide a novel means of reproducing the nuanced branching behavior that occurs in different layers of granule cell dendritic morphologies. In this study, a heterogeneous Poisson point process was used to simulate branching events. Conditional distributions were then used to select branch angles depending on the orthogonal distance to the somatic plane. The proposed method was compared to an existing generation tool and a control version of the proposed method that used a homogeneous Poisson point process. Morphologies were generated with each method and then compared to a set of digitally reconstructed neurons. The introduction of a conditionally dependent branching rate resulted in the generation of morphologies that more accurately reproduced the emergent properties of dendritic material per layer, Sholl intersections, and proximal passive current flow. Conditional dependence was critically important for the generation of realistic granule cell dendritic morphologies.

中文翻译:

通过估计树突分支的空间异质性产生颗粒细胞树突形态

树突形态的生物学真实性对于模拟脑组织的电刺激很重要。通过将点过程建模和条件采样添加到现有的生成策略中,我们提供了一种新的方法来重现在不同层的颗粒细胞树突形态中发生的细微分支行为。在这项研究中,异构泊松点过程用于模拟分支事件。然后使用条件分布根据到体细胞平面的正交距离选择分支角度。将所提出的方法与使用齐次泊松点过程的现有生成工具和所提出方法的控制版本进行比较。每种方法都会生成形态,然后与一组数字重建的神经元进行比较。条件依赖分支率的引入导致更准确地再现每层树枝状材料、Sholl 交叉点和近端无源电流的涌现特性的形态的生成。条件依赖性对于生成逼真的颗粒细胞树突形态至关重要。
更新日期:2020-04-09
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