FPGA implementation of motifs-based neuronal network and synchronization analysis

Bin Deng, Zechen Zhu, Shuangming Yang, Xile Wei, Jiang Wang and Haitao Yu

Physica A: Statistical Mechanics and its Applications, 2016, vol. 451, issue C, 388-402

Abstract: Motifs in complex networks play a crucial role in determining the brain functions. In this paper, 13 kinds of motifs are implemented with Field Programmable Gate Array (FPGA) to investigate the relationships between the networks properties and motifs properties. We use discretization method and pipelined architecture to construct various motifs with Hindmarsh–Rose (HR) neuron as the node model. We also build a small-world network based on these motifs and conduct the synchronization analysis of motifs as well as the constructed network. We find that the synchronization properties of motif determine that of motif-based small-world network, which demonstrates effectiveness of our proposed hardware simulation platform. By imitation of some vital nuclei in the brain to generate normal discharges, our proposed FPGA-based artificial neuronal networks have the potential to replace the injured nuclei to complete the brain function in the treatment of Parkinson’s disease and epilepsy.

Keywords: Motif; Synchronization; FPGA; Small-world network (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:451:y:2016:i:c:p:388-402

DOI: 10.1016/j.physa.2016.01.052

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