A multiplier-less digital design of a bio-inspired stimulator to suppress synchronized regime in a large-scale, sparsely connected neural network

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• 作者：Soheila Nazari ; Karim Faez ; Mahmood Amiri
• 关键词：DBS ; Synchronization ; Digital implementation ; Bio ; inspired Stimulator
• 刊名：Neural Computing and Applications
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：28
• 期：2
• 页码：375-390
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence (incl. Robotics); Data Mining and Knowledge Discovery; Probability and Statistics in Computer Science; Computational Science and Engineering; Image Processing and Computer Visi
• 出版者：Springer London
• ISSN：1433-3058
• 卷排序：28

文摘

Excessive synchronous firing of neurons is the sign of several neurological disorders such as Parkinson and epilepsy. In addition, growing evidence suggests that astrocytes have significant roles in neural synchronization. Drawing on these concepts and based on the latest studies, a bio-inspired stimulator which essentially is a dynamical model of the astrocyte biophysical model is proposed. The performance of the proposed bio-inspired stimulator is investigated on a large-scale, sparsely connected neural network which models a local cortical population. Next, a multiplier-less digital circuit for the bio-inspired stimulator is designed, and finally, the complete digital circuit of the closed-loop system is implemented in hardware on the ZedBoard development kit. Considering software simulations and hardware FPGA implementation, the proposed bio-inspired stimulator is able to prevent the hyper-synchronous neural firing in a network of excitatory and inhibitory neurons. Based on the obtained results, it is demonstrated that the proposed stimulator has a demand-controlled characteristic and can be a good candidate as a new deep brain stimulation (DBS) technique to effectively suppress the hyper-synchronous neural oscillations.