کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
759041 896461 2014 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Model-based iterative learning control of Parkinsonian state in thalamic relay neuron
ترجمه فارسی عنوان
کنترل یادگیری تکراری بر پایه مدل پارکینسونی در نورون رله تالاموم
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی مکانیک
چکیده انگلیسی


• Iterative learning control (ILC) is applied to improve the Parkinsonian conditions.
• ILC is independent of accurate model and can achieve the perfect tracking.
• ILC can reduce the difficulty of the selection of the controller’ parameters.
• Changing the model parameter can verify that ILC’s model-independence.

Although the beneficial effects of chronic deep brain stimulation on Parkinson’s disease motor symptoms are now largely confirmed, the underlying mechanisms behind deep brain stimulation remain unclear and under debate. Hence, the selection of stimulation parameters is full of challenges. Additionally, due to the complexity of neural system, together with omnipresent noises, the accurate model of thalamic relay neuron is unknown. Thus, the iterative learning control of the thalamic relay neuron’s Parkinsonian state based on various variables is presented. Combining the iterative learning control with typical proportional–integral control algorithm, a novel and efficient control strategy is proposed, which does not require any particular knowledge on the detailed physiological characteristics of cortico-basal ganglia-thalamocortical loop and can automatically adjust the stimulation parameters. Simulation results demonstrate the feasibility of the proposed control strategy to restore the fidelity of thalamic relay in the Parkinsonian condition. Furthermore, through changing the important parameter—the maximum ionic conductance densities of low-threshold calcium current, the dominant characteristic of the proposed method which is independent of the accurate model can be further verified.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Communications in Nonlinear Science and Numerical Simulation - Volume 19, Issue 9, September 2014, Pages 3255–3266
نویسندگان
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