FPGA based pipelined architecture for action potential simulation in biological neural systems

This paper presents a hardware based approach to simulate action potential of large numbers of somas within a biological neural network. At the proposed method multiple processors can work in parallel to increase processing power as required. The high speed pipelined architecture for each processor provides the computation speed of one soma per clock ratio and with multiple processors higher speeds are achievable. The design is highly scalable such that the number of cells in the model is limited only by the available memory size. Compartmental approach and Hodgkin-Huxley methods are used as simulation models in our studies. The approach is verified in MATLAB and is synthesized for Xilinx V5-110t-1 as the target FPGA. While not dependent on particular IP cores, the whole implementation is based on Xilinx IP cores including IEEE-754 64-bit floating-point adder and multiplier cores.