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

Author

Bontorin, G. ; Renaud, S. ; Garenne, A. ; Alvado, L. ; Le Masson, G. ; Tomas, J.

Author_Institution

Univ. of Bordeaux1, Talence

fYear

2007

fDate

22-26 Aug. 2007

Firstpage

3004

Lastpage

3007

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 mus. We detail here the system components and compare its performances to a recent commercial platform.

Keywords

biocontrol; biocybernetics; closed loop systems; neural nets; robots; artificial neural networks; artificial processing unit; biological neural system adaptation; closed loop data processing; cultured neural network; real time closed loop hybrid ANN; robotic interface; Artificial neural networks; Biological materials; Biological neural networks; Biomembranes; Complex networks; Electrodes; Extracellular; Hardware; Neural networks; Neurons; Animals; Biomimetics; Bionics; Cells, Cultured; Computer Systems; Cybernetics; Equipment Design; Equipment Failure Analysis; Feedback; Nerve Net; Neural Networks (Computer); Pattern Recognition, Automated; Rats; Robotics; Signal Processing, Computer-Assisted; Systems Integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE

Conference_Location

Lyon

ISSN

1557-170X

Print_ISBN

978-1-4244-0787-3

Type

conf

DOI

10.1109/IEMBS.2007.4352961

Filename

4352961