Neuron Model Database for Arm-Based Multi-Core Neuromorphic Computing

The development of neuromorphic computing provides new approaches for research in neuroscience. However, the network construction phase occupies most of development cycle. Therefore, this paper builds a multi-scale neuron model database for the developed ARM-based multi-core neuromorphic computing system, which is perfect matched to the embedded system from ion channel and neuron scales. By optimizing the calculation process of neuron models, it can support the real-time simulation of various models in the database, which provides strong support for the simulation of the system in large-scale brain networks and spiking neural networks (SNNs). The Leaky Integrate and Fire (LIF), Izhikevich, and Hodgkin-Huxley (HH) neurons are simulated in the system within 0.5s, 0.1s, and 0.5s, respectively, which verified the great potential of the neuron model database in SNN modeling, large-scale brain network simulation and neurodynamic analysis. The neuron model database serves as the foundation for network construction, and study upon this will provide a normalized method for embedded neuromorphic computation.