Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model.
Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model.
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将 3D 工程神经元培养物与微电极阵列连接：一种创新的体外实验模型。
DOI：
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发表时间：
2015
期刊：
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通讯作者：
P. Massobrio
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作者：
M. Tedesco;M. Frega;S. Martinoia;M. Pesce;P. Massobrio
目前，在细胞外微传感器装置上分离的神经元在体外生长和发育的大规模网络是研究神经元细胞组合形成和维持的基本神经生理机制的金标准实验模型。然而，体外研究仅限于记录由二维（2D）神经网络产生的电生理活动。然而，考虑到结构和动力学之间的复杂关系，研究三维（3D）网络的形成和发展动力学是必要的。在这项工作中，提出了一个新的实验平台，其中3D海马或皮层网络耦合到平面微电极阵列（MEAs）。3D网络是通过将神经元植入由玻璃微珠（直径30-40µm）组成的支架中来实现的，神经元能够在支架上生长并形成复杂的相互连接的3D组件。通过这种方式，可以设计出由5-8层组成的工程3D网络，并具有预期的最终细胞密度。在三维组装的形态组织的复杂性增加诱导了这种类型的网络所显示的电生理模式的增强。与标准的2D网络相比，3D结构改变了爆炸活动的持续时间和频率，并且可以观察到更多随机的尖峰活动。从这个意义上说，开发的3D模型更接近于体内神经网络。
Currently, large-scale networks derived from dissociated neurons growing and developing in vitro on extracellular micro-transducer devices are the gold-standard experimental model to study basic neurophysiological mechanisms involved in the formation and maintenance of neuronal cell assemblies. However, in vitro studies have been limited to the recording of the electrophysiological activity generated by bi-dimensional (2D) neural networks. Nonetheless, given the intricate relationship between structure and dynamics, a significant improvement is necessary to investigate the formation and the developing dynamics of three-dimensional (3D) networks. In this work, a novel experimental platform in which 3D hippocampal or cortical networks are coupled to planar Micro-Electrode Arrays (MEAs) is presented. 3D networks are realized by seeding neurons in a scaffold constituted of glass microbeads (30-40 µm in diameter) on which neurons are able to grow and form complex interconnected 3D assemblies. In this way, it is possible to design engineered 3D networks made up of 5-8 layers with an expected final cell density. The increasing complexity in the morphological organization of the 3D assembly induces an enhancement of the electrophysiological patterns displayed by this type of networks. Compared with the standard 2D networks, where highly stereotyped bursting activity emerges, the 3D structure alters the bursting activity in terms of duration and frequency, as well as it allows observation of more random spiking activity. In this sense, the developed 3D model more closely resembles in vivo neural networks.