Efficient Implementation of Cerebellar Purkinje Cell With the CORDIC Algorithm on LaCSNN - Hao, Xinyu; Yang, Shuangming; Wang, Jiang; Deng, Bin; Wei, Xile; Yi, Guosheng (Frontiers in Neuroscience, 2019)
Purkinje cell is an important neuron for the cerebellar information processing. In this work, we present an efficient implementation of a cerebellar Purkinje model using Coordinate Rotation Digital Computer (CORDIC) algorithm and implement it on Large-Scale Conductance-Based Spiking Neural Networks (LaCSNN) system with cost-efficient multiplier-less methods, which are more suitable for large-scale neural networks. The CORDIC-based Purkinje model has been compared with the original model in terms of the voltage activities, dynamic mechanisms, precision and hardware resource utilization. The results show that the CORDIC-based Purkinje model can reproduce the same biological activities and dynamical mechanisms as the original model with slight deviation. In the aspect of the hardware implementation, it can use only logic resources so it provides an efficient way for maximizing the FPGA resource utilization, thereby expanding the scale of neural networks which can be implemented on FPGAs.