Authors:
Safa Yaghini Bonabi
1
;
Hassan Asgharian
2
;
Reyhaneh Bakhtiari
3
;
Saeed Safari
1
and
Majid Nili Ahmadabadi
3
Affiliations:
1
University of Tehran, Iran, Islamic Republic of
;
2
IUST, Iran, Islamic Republic of
;
3
University of Tehran and Institute for Research in Fundamental Sciences (IPM), Iran, Islamic Republic of
Keyword(s):
Hodgkin-Huxley, FPGA, VHDL, MATLAB.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Computational Neuroscience
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neural Network Hardware Implementation and Applications
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
Abstract:
In this paper an implementation of Hodgkin-Huxley single neuron is provided. Unlike almost all of the existing implementations, the arithmetic logics are implemented with computation techniques (i.e. CORDIC) and look-up-tables (LUTs) are used only in few modules. This makes our design more robust and flexible to simulate the functionality of a large network of neurons. Most of the previous works are based on the software implementations which overshadow the parallel nature of the neural system or using LUTs for hardware implementation which needs more space and also limited flexibility. In this paper, an FPGA is selected as our hardware implementation platform to provide an appropriate reconfigurable platform for simulating the functionality of a network of neurons. We validated our design based on our high level implementation of Hodgkin-Huxley neuron in MATLAB and report our implementation results based on Xilinx SPARTAN 3 FPGA in Xilinx ISE Design Suite.