A Resource-Efficient and High-Accuracy CORDIC-Based Digital Implementation of the Hodgkin–Huxley Neuron
Alexander J. Leigh, Moslem Heidarpur, Mitra Mirhassani
Abstract
A new and efficient Hodgkin–Huxley (HH) neuron has been implemented on field-programmable gate array (FPGA). Multiplication, division, and exponential terms were implemented using the COordinate Rotation DIgital Computer (CORDIC) algorithm with carefully selected iteration numbers for each operation to greatly reduce the hardware resource requirements while simultaneously maintaining system throughput and a maximum clock frequency of over 275 MHz. The proposed design achieves higher modeling accuracy than previously proposed designs and an accuracy-resource trade-off that represents dramatic improvements. Additionally, all the neuron’s physiological parameters are variable as inputs to the proposed design postimplementation for a high degree of freedom in neuroscientific simulations. The implemented neuron is presented with results, and the behavior of the implemented system is evaluated to verify its close behavioral matching to the target neuron model.