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

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 FPGA (Field Programmable Gate Array) 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 like damage cells replacement and the study of the effect of the cells disease on the neural network.
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Contributor : Timothée Levi <>
Submitted on : Tuesday, July 25, 2017 - 2:07:51 AM
Last modification on : Tuesday, March 17, 2020 - 11:16:02 AM


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  • HAL Id : hal-01567496, version 1


Timothée Levi, Farad Khoyratee, Sylvain Saïghi, Yoshiho Ikeuchi. Digital implementation of Hodgkin-Huxley neuron model for neurological diseases studies. 22th International Symposium on Artificial Life and Robotics, Jan 2017, Beppu, Japan. ⟨hal-01567496⟩



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