title: Cost-efficient FPGA implementation of basal ganglia and their Parkinsonian analysis.
abstract: The basal ganglia (BG) comprise multiple subcortical nuclei, which are responsible for cognition and other functions. Developing a brain-machine interface (BMI) demands a suitable solution for the real-time implementation of a portable BG. In this study, we used a digital hardware implementation of a BG network containing 256 modified Izhikevich neurons and 2048 synapses to reliably reproduce the biological characteristics of BG on a single field programmable gate array (FPGA) core. We also highlighted the role of Parkinsonian analysis by considering neural dynamics in the design of the hardware-based architecture. Thus, we developed a multi-precision architecture based on a precise analysis using the FPGA-based platform with fixed-point arithmetic. The proposed embedding BG network can be applied to intelligent agents and neurorobotics, as well as in BMI projects with clinical applications. Although we only characterized the BG network with Izhikevich models, the proposed approach can also be extended to more complex neuron models and other types of functional networks.
authors: School of Electrical Engineering and Automation, Tianjin University, 300072, PR China.
authors: Shuangming
authors: S
authors: Yang
authors: School of Electrical Engineering and Automation, Tianjin University, 300072, PR China.
authors: Jiang
authors: J
authors: Wang
authors: School of Electrical Engineering and Automation, Tianjin University, 300072, PR China.
authors: Shunan
authors: S
authors: Li
authors: School of Electrical Engineering and Automation, Tianjin University, 300072, PR China. Electronic address: dengbin@tju.edu.cn.
authors: Bin
authors: B
authors: Deng
authors: School of Electrical Engineering and Automation, Tianjin University, 300072, PR China.
authors: Xile
authors: X
authors: Wei
authors: School of Electrical Engineering and Automation, Tianjin University, 300072, PR China.
authors: Haitao
authors: H
authors: Yu
authors: School of Automation and Electrical Engineering, Tianjin University of Technology and Educations, 300222, PR China.
authors: Huiyan
authors: H
authors: Li
mesh_terms: D000465:Algorithms; D001479:Basal Ganglia / Q000503:physiopathology*; D062207:Brain-Computer Interfaces; D003199:Computer Systems; D003201:Computers; D006801:Humans; D015233:Models, Statistical; D016571:Neural Networks, Computer; D009474:Neurons; D010300:Parkinson Disease / Q000503:physiopathology*; D012371:Robotics
keywords: Basal ganglia (BG); Field-programmable gate array (FPGA); Parkinsonian state; Piecewise linear approximation (PLA); Real time