Marinaro Giovanni, La Rocca Rosanna, Toma Andrea, Barberio Marianna, Cancedda Laura, Di Fabrizio Enzo, Decuzzi Paolo, Gentile Francesco
Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy.
Integr Biol (Camb). 2015 Feb;7(2):184-97. doi: 10.1039/c4ib00216d.
The human brain is a tightly interweaving network of neural cells where the complexity of the network is given by the large number of its constituents and its architecture. The topological structure of neurons in the brain translates into its increased computational capabilities, low energy consumption, and nondeterministic functions, which differentiate human behavior from artificial computational schemes. In this manuscript, we fabricated porous silicon chips with a small pore size ranging from 8 to 75 nm and large fractal dimensions up to Df ∼ 2.8. In culturing neuroblastoma N2A cells on the described substrates, we found that those cells adhere more firmly to and proliferate on the porous surfaces compared to the conventional nominally flat silicon substrates, which were used as controls. More importantly, we observed that N2A cells on the porous substrates create highly clustered, small world topology patterns. We conjecture that neurons with a similar architecture may elaborate information more efficiently than in random or regular grids. Moreover, we hypothesize that systems of neurons on nano-scale geometry evolve in time to form networks in which the propagation of information is maximized.
人类大脑是一个由神经细胞紧密交织而成的网络，其网络的复杂性由大量的组成部分及其结构决定。大脑中神经元的拓扑结构转化为其增强的计算能力、低能耗和非确定性功能，这些功能将人类行为与人工计算方案区分开来。在本论文中，我们制造了孔径范围为8至75纳米且分形维数高达Df ∼ 2.8的多孔硅芯片。在用所述底物培养神经母细胞瘤N2A细胞时，我们发现与用作对照的传统名义上平坦的硅底物相比，这些细胞在多孔表面上更牢固地附着并增殖。更重要的是，我们观察到多孔底物上的N2A细胞形成了高度聚集的小世界拓扑模式。我们推测具有类似结构的神经元可能比在随机或规则网格中更有效地处理信息。此外，我们假设纳米尺度几何结构上的神经元系统会随时间演化形成信息传播最大化的网络。
