A review of CMOS, memristive, superconducting, and optical hardware for spiking neural networks, concluding that hybrid approaches are the most promising direction.
Bio-realistic Neural Network Implementation on Loihi 2 with Izhikevich Neurons
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In this paper, we presented a bio-realistic basal ganglia neural network and its integration into Intel's Loihi neuromorphic processor to perform simple Go/No-Go task. To incorporate more bio-realistic and diverse set of neuron dynamics, we used Izhikevich neuron model, implemented as microcode, instead of Leaky-Integrate and Fire (LIF) neuron model that has built-in support on Loihi. This work aims to demonstrate the feasibility of implementing computationally efficient custom neuron models on Loihi for building spiking neural networks (SNNs) that features these custom neurons to realize bio-realistic neural networks.
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Contemporary implementations of spiking bio-inspired neural networks
A review of CMOS, memristive, superconducting, and optical hardware for spiking neural networks, concluding that hybrid approaches are the most promising direction.