Hardware Implementation of a Bio-plausible Neuron Model for Evolution and Growth of Spiking Neural Networks on FPGA

Authors:
Hooman Shayani;Peter J. Bentley;Andy M. Tyrrell
Affiliations:
-;-;-
Venue:
AHS '08 Proceedings of the 2008 NASA/ESA Conference on Adaptive Hardware and Systems
Year:
2008

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Abstract

We propose a digital neuron model suitable for evolving and growing heterogeneous spiking neural networks on FPGAs by introducing a novel flexible dendrite architecture and the new PLAQIF (Piecewise-Linear Approximation of Quadratic Integrate and Fire) soma model. A network of 161 neurons and 1610 synapses was simulated, implemented, and verified on a Virtex-5 chip with 4210 times real-time speed with 1 ms resolution. The parametric flexibility of the soma model was shown through a set of experiments.