Synchronization between outputs of neurons and neuron populations with discrete control algorithm basing on least-square method

Chenhui Jia, Jiang Wang, Bin Deng, Xile Wei, Feng Dong, Yanqiu Che

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As a new method on curing mental diseases, Deep Brain Stimulation (DBS) gives great help to patients who do not respond to drug therapies. However, most of the DBS therapies used at present are using high-frequency signals as open-loop stimulating signals, whose mechanism is not sufficiently understood. In this paper, basing on the synchronization mechanism and the close-loop stability theory, we have designed a close-loop method to propose a potential therapy for curing mental diseases with deep brain stimulation. Through reconstruct the input-output dynamics with least square method, we can use a new regressive input-output model to describe the relationship between the input and output of the abnormal neuron population. Using the parameters estimated in the regressive model, we can design a set of DBS signals to make the output of abnormal neuron population accurately track the desired output signal. The method is robust and can be applied even when the abnormal neuron population is disturbed by heavy noise.

Original languageEnglish (US)
Title of host publicationWCICA 2012 - Proceedings of the 10th World Congress on Intelligent Control and Automation
Pages5001-5006
Number of pages6
DOIs
StatePublished - Dec 1 2012
Event10th World Congress on Intelligent Control and Automation, WCICA 2012 - Beijing, China
Duration: Jul 6 2012Jul 8 2012

Publication series

NameProceedings of the World Congress on Intelligent Control and Automation (WCICA)

Other

Other10th World Congress on Intelligent Control and Automation, WCICA 2012
Country/TerritoryChina
CityBeijing
Period7/6/127/8/12

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Computer Science Applications

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