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A Real-Time Closed-Loop Setup for Hybrid Neural Networks

Abstract : Hybrid living-artificial neural networks are an efficient and adaptable experimental support to explore the dynamics and the adaptation process of biological neural systems. We present in this paper an innovative platform performing a real-time closed-loop between a cultured neural network and an artificial processing unit like a robotic interface. The system gathers bioware, hardware, and software components and ensures the closed-loop data processing in less than 50 µs. We detail here the system components and compare its performances to a recent commercial platform.
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https://hal.archives-ouvertes.fr/hal-00181426
Contributor : Sylvain Saighi <>
Submitted on : Wednesday, October 24, 2007 - 4:34:47 PM
Last modification on : Thursday, January 11, 2018 - 6:21:07 AM
Document(s) archivé(s) le : Sunday, April 11, 2010 - 11:57:06 PM

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2007_EMBC_Bontorin.pdf
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  • HAL Id : hal-00181426, version 1

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G. Bontorin, S. Renaud, A. Garenne, L. Alvado, G. Le Masson, et al.. A Real-Time Closed-Loop Setup for Hybrid Neural Networks. Proc. of the 29th Annaul Int. Conference of the IEEE EMBS, Aug 2007, Lyon, France. pp.3004-3007. ⟨hal-00181426⟩

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