Paper-based patterned 3D neural cultures as a tool to study network activity on multielectrode arrays
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2017
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Journal Article
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Abstract
Cells in vitro behave differently if cultured in a 2D or 3D environment. In spite of the continuous progress over the recent years, methods available for realizing 3D cultures of primary neurons are still fairly complex, limited in throughput and especially limited in compatibility with other techniques like multielectrode arrays (MEAs) for recording and stimulating the network activity with high temporal precision. In this manuscript, a paper-based approach is presented using cellulose filter paper as a mobile substrate for 3D cultures of primary rat hippocampal and cortical neurons. Acting as 3D scaffolds for network development, filter membranes with different surface treatments were prepared to control network homogeneity and laser cut to change the network topology through spatial confinement. The viability of the prepared cultures was comparable to that of reference 2D cultures for over 4 weeks, and the mechanical stability of the paper substrates made it possible to transfer the cultures to MEA chips in an on-demand manner. Once the cultures were successfully transduced with a gene-encoded calcium indicator and transferred to a MEA chip, the optical and electrical signals of neuronal activity were simultaneously recorded and combined to study the different activity patterns with high spatiotemporal resolution. The high-throughput nature of the presented approach makes it a valuable tool for investigating the intimate relationship between topology and function, by studying the intrinsic parameters influencing network synchronization and signal propagation through the different activity patterns of 3D neural cultures with arbitrary topology. The developed platform provides a robust and simple alternative to existing 3D culturing technologies for neurons.
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7 (62)
Pages / Article No.
39359 - 39371
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Royal Society of Chemistry
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296590 - Biomimiking the brain - towards 3D neuronal network dynamics (EC)