FPGA implementation of a cortical network based on the hodgkin-huxley neuron model

Authors:
Safa Yaghini Bonabi;Hassan Asgharian;Reyhaneh Bakhtiari;Saeed Safari;Majid Nili Ahmadabadi
Affiliations:
School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran;Department of Computer Engineering, IUST, Tehran, Iran;School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran,School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran;School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran;School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran,School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part I
Year:
2012

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Abstract

In this paper a biological neural network based on the Hodgkin-Huxley neuron model is implemented using Xilinx Field Programmable Gate Array (FPGA). By employing appropriate computational techniques, such as CORDIC, and step-by-step time integration of the respective equations, an exact response of the neuron is calculated. Neurons are simple units that exhibit high level behaviors during interaction in a network. The Parallel processing feature of FPGA makes this platform an ideal candidate to model these networks. We implemented a network with 16 neurons and the result of this implementation is validated using MATLAB simulation.