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Application of polymer microstructures with controlled surface chemistries as a platform for creating and interfacing with synthetic neural networks

Par Conseil national de recherches du Canada

DOITrouver le DOI : https://doi.org/10.1109/IJCNN.2005.1556425
AuteurRechercher : 1; Rechercher : 1; Rechercher : 1; Rechercher : 1; Rechercher : 1; Rechercher : 2; Rechercher : 2; Rechercher : 2; Rechercher : 2
Affiliation
  1. Conseil national de recherches du Canada. Institut des sciences biologiques du CNRC
  2. Conseil national de recherches du Canada. Institut des sciences des microstructures du CNRC
FormatTexte, Article
ConférenceInternational Joint Conference on Neural Networks, Special Session: Neural Prostheses and the Neuron-Silicon Interface, July 31 - August 4, 2005, Montreal, Canada
Résumé
Hybrid silicon-polymer chips with microscale topography and contrasting surface chemistries were created using a novel combination of soft lithography techniques, and evaluated for their suitability as a platform to guide cell attachment, growth and differentiation. These capabilities are all necessary to synthesize organized neural networks in vitro. Neurons developed on these chips exhibit patterned growth and functional communication, evidenced by spontaneous and stimulated action potentials and intracellular calcium oscillations. Integration of planar patch-clamp technology into this platform to create a novel long-term interface is presented, with the formation of a high resistance (giga-ohm) electrical seal between the cultured cell membrane and the perimeter of a micron-sized orifice integrated into the substrate. This platform has potential as a tool to investigate mechanisms underlying neuro-genesis, synaptic transmission, and neuro-degeneration. It may also lead to the development of more sophisticated and functionally relevant bioassays and high throughput electrophysiological screening, thus speeding the drug discovery process.
Date de publication
Dans
  • Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on Neural Networks 5 (2005).
Langueanglais
Numéro NPARC12346365
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Identificateur de l’enregistrement27fd88ea-3815-4731-a1e2-8e677f01d73e
Enregistrement créé2009-09-17
Enregistrement modifié2020-04-07
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