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Artificial Life and Robotics

, Volume 23, Issue 1, pp 10–14 | Cite as

Digital implementation of Hodgkin–Huxley neuron model for neurological diseases studies

  • Timothée LeviEmail author
  • Farad Khoyratee
  • Sylvain Saïghi
  • Yoshiho Ikeuchi
Original Article

Abstract

Neurological disorders affect millions of people which influence their cognitive and/or motor capabilities. The realization of a prosthesis must consider the biological activity of the cells and the connection between machine and biological cells. Biomimetic neural network is one solution in front of neurological diseases. The neuron replacement should be processed by reproducing the timing and the shape of the spike. Several mathematical equations which model neural activities exist. The most biologically plausible one is the Hodgkin–Huxley (HH) model. The connection between electrical devices and living cells require a tunable real-time system. The field programmable gate array (FPGA) is a nice component including flexibility, speed and stability. Here, we propose an implementation of HH neurons in FPGA serving as a presage for a modulating network opening a large scale of possibilities such as damage cells replacement and the study of the effect of the cells disease on the neural network.

Keywords

Silicon neuron Hodgkin–Huxley FPGA Neurological diseases 

Notes

Acknowledgements

The research leading to these results has received funding from CNRS PEPS2015 “Neuroprotest”.

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Copyright information

© ISAROB 2017

Authors and Affiliations

  • Timothée Levi
    • 1
    • 2
    Email author
  • Farad Khoyratee
    • 1
  • Sylvain Saïghi
    • 1
  • Yoshiho Ikeuchi
    • 2
  1. 1.IMS LaboratoryUniversity of BordeauxBordeauxFrance
  2. 2.Institute of Industrial ScienceThe University of TokyoTokyoJapan

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