Biologically Inspired Spiking Neurons: Piecewise Linear Models and Digital Implementation

Abstract

Abstract-there has been a strong push recently to examine biological scale simulations of neuromorphic algorithms to achieve stronger inference capabilities. This paper presents a set of piecewise linear spiking neuron models, which can reproduce different behaviors, similar to the biological neuron, both for a single neuron as well as a network of neurons. The proposed models are investigated, in terms of digital implementation feasibility and costs, targeting large scale hardware implementation.Hardware synthesis and physical implementations on FPGA show that the proposed models can produce precise neural behaviors with higher performance and considerably lower implementation costs compared with the original model. Accordingly, a compact structure of the models which can be trained with supervised and unsupervised learning algorithms has been developed. Using this structure and based on a spike rate coding, a character recognition case study has been implemented and tested.Index Terms-Spiking Neural networks, Piecewise Linear Model, Field Programmable Gate Array (FPGA), Spike Rate Learning.

A digital implementation of neuron–astrocyte interaction for neuromorphic applications

“…(v-nullcline) Considering, Fig.3 (b), the piecewise linear model can be obtained as follows (Soleimani et al, 2012):…”

Neural dynamics and bifurcation analysis of piecewise linear neuron models

“…The difficulty of implementation arises from the quadratic part of the model so to improve computational efficiency of this model, three piecewise linear approximations have been proposed [7]. The piecewise linear models (PWL) models are described in the following.…”

“…Implementation of these models, targeting different applications, has been subject of studies in terms of efficiency and large scale simulations [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19].…”

“…Recently, a new piecewise linear (PWL) modification of the Izhikevich model, which can reproduce different dynamic behaviors of cortical neurons have been presented [7]. Due to the simple structure of these models using standard analog and digital implementations, they have the capability to be realized as application specific reconfigurable analog or digital devices, targeting neural networks.…”

Systematic Computation of Nonlinear Bilateral Dynamical Systems With a Novel Low-Power Log-Domain Circuit

“…Exceptional examples can be found in neuromorphic electronics where brain's neural dynamical systems are mimicked by the use of very-large-scale integration (VLSI) systems containing electronic analog/digital circuits [3][4][5][6][7][8][9][10][11][12]. On the other hand, other research efforts have focused on the synthesis and study of intra/extracellular chemical dynamics demonstrating a bold shift of emphasis from the neural system.…”