Individual-cell-based electrophysiological measurement of a topographically controlled neuronal network pattern using agarose architecture with a multi-electrode array
Individual-cell-based electrophysiological measurement of a topographically controlled neuronal network pattern using agarose architecture with a multi-electrode array
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DOI：
10.1143/jjap.43.l403
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发表时间：
2004-03-15
期刊：
影响因子：
--
通讯作者：
Yasuda, K
中科院分区：
文献类型：
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作者：
Suzuki, I;Sugio, Y;Yasuda, K
我们开发了一种新型的基于单个细胞的电生理测量方法，使用带有琼脂糖微室(AMC)阵列的芯片上多电极阵列(MEA)细胞培养系统来对活的神经元网络的网络模式进行地形图控制。这种方法的优点是，它允许使用MEA记录几周内同时激发多个细胞而不受污染，并且它允许控制细胞的位置和数量，以及它们的连接，使用通过光热蚀刻制造的具有微通道的AMC进行培养，其中琼脂糖层的一部分用1480 nm红外激光熔化。利用这种方法，我们形成了一个基于单个细胞的大鼠神经网络模式，AMC阵列中的海马细胞在培养13天时没有细胞从微室的电极位置逃逸，并可以通过电极记录排列好的海马细胞对20-A，5 kHz刺激的反应。这证明了我们的芯片上AMC/MEA细胞培养方法的潜力，用于长期基于单细胞的神经网络系统的电生理测量，以了解神经网络模式的拓扑学意义。
We have developed a new type of individual-cell-based electrophysiological measurement method using an on-chip multielectrode array (MEA) cell-cultivation system with an agarose microchamber (AMC) array for topographical control of the network patterns of a living neuronal network. The advantages of this method are that it allows the recording of the firing of multiple cells simultaneously for weeks without contamination using the MEA, and that it allows control of the cell positions and numbers, and their connections for cultivation using AMCs with microchannels fabricated by photothermal etching where a portion of the agarose layer is melted with a 1480 nm infrared laser beam. Using this method, we formed an individual-cellbased neural network pattern of Rat,hippocampal cells within the AMC array without cells escaping from the electrode positions in the microchamber during a thirteen-day cultivation, and could record the cell firing of lined-up hippocampal cells in response to 20muA, 5 kHz stimulation via an electrode. This demonstrated the potential of our on-chip AMC/MEA cell cultivation method for long-term single-cell-based electrophysiological measurement of a neural network system for understanding the topographical meaning of neuronal network patterns.