Miner Daniel C, Triesch Jochen
Department of Neuroscience, Frankfurt Institute for Advanced Studies Frankfurt am Main, Germany.
Front Neuroanat. 2014 Nov 5;8:125. doi: 10.3389/fnana.2014.00125. eCollection 2014.
The neuroanatomical connectivity of cortical circuits is believed to follow certain rules, the exact origins of which are still poorly understood. In particular, numerous nonrandom features, such as common neighbor clustering, overrepresentation of reciprocal connectivity, and overrepresentation of certain triadic graph motifs have been experimentally observed in cortical slice data. Some of these data, particularly regarding bidirectional connectivity are seemingly contradictory, and the reasons for this are unclear. Here we present a simple static geometric network model with distance-dependent connectivity on a realistic scale that naturally gives rise to certain elements of these observed behaviors, and may provide plausible explanations for some of the conflicting findings. Specifically, investigation of the model shows that experimentally measured nonrandom effects, especially bidirectional connectivity, may depend sensitively on experimental parameters such as slice thickness and sampling area, suggesting potential explanations for the seemingly conflicting experimental results.
人们认为皮质回路的神经解剖学连接遵循某些规则，但其确切起源仍知之甚少。特别是，在皮质切片数据中通过实验观察到了许多非随机特征，如共同邻居聚类、相互连接的过度呈现以及某些三元图模式的过度呈现。其中一些数据，特别是关于双向连接的数据，似乎相互矛盾，其原因尚不清楚。在这里，我们提出了一个简单的静态几何网络模型，该模型在实际尺度上具有距离依赖性连接，自然地产生了这些观察到的行为的某些元素，并可能为一些相互矛盾的发现提供合理的解释。具体而言，对该模型的研究表明，实验测量的非随机效应，尤其是双向连接，可能敏感地取决于诸如切片厚度和采样面积等实验参数，这为看似相互矛盾的实验结果提供了潜在的解释。
