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闭环深脑刺激控制:一项模拟研究。

Closed-loop control of deep brain stimulation: a simulation study.

机构信息

Department of Engineering, Università del Sannio, Benevento, Italy.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2011 Feb;19(1):15-24. doi: 10.1109/TNSRE.2010.2081377. Epub 2010 Sep 30.

Abstract

Deep brain stimulation (DBS) is an effective therapy to treat movement disorders including essential tremor, dystonia, and Parkinson's disease. Despite over a decade of clinical experience the mechanisms of DBS are still unclear, and this lack of understanding makes the selection of stimulation parameters quite challenging. The objective of this work was to develop a closed-loop control system that automatically adjusted the stimulation amplitude to reduce oscillatory neuronal activity, based on feedback of electrical signals recorded from the brain using the same electrode as implanted for stimulation. We simulated a population of 100 intrinsically active model neurons in the Vim thalamus, and the local field potentials (LFPs) generated by the population were used as the feedback (control) variable for closed loop control of DBS amplitude. Based on the correlation between the spectral content of the thalamic activity and tremor (Hua , 1998), (Lenz , 1988), we implemented an adaptive minimum variance controller to regulate the power spectrum of the simulated LFPs and restore the LFP power spectrum present under tremor conditions to a reference profile derived under tremor free conditions. The controller was based on a recursively identified autoregressive model (ARX) of the relationship between stimulation input and LFP output, and showed excellent performances in tracking the reference spectral features through selective changes in the theta (2-7 Hz), alpha (7-13 Hz), and beta (13-35 Hz) frequency ranges. Such changes reflected modifications in the firing patterns of the model neuronal population, and, differently from open-loop DBS, replaced the tremor-related pathological patterns with patterns similar to those simulated in tremor-free conditions. The closed-loop controller generated a LFP spectrum that approximated more closely the spectrum present in the tremor-free condition than did open loop fixed intensity stimulation and adapted to match the spectrum after a change in the neuronal oscillation frequency. This computational study suggests the feasibility of closed-loop control of DBS amplitude to regulate the spectrum of the local field potentials and thereby normalize the aberrant pattern of neuronal activity present in tremor.

摘要

脑深部电刺激(DBS)是一种有效的治疗运动障碍的方法,包括原发性震颤、肌张力障碍和帕金森病。尽管有十多年的临床经验,但 DBS 的机制仍不清楚,这种缺乏理解使得刺激参数的选择极具挑战性。本工作的目的是开发一种闭环控制系统,该系统根据使用与植入刺激相同的电极从大脑记录的电信号的反馈,自动调整刺激幅度以减少振荡神经元活动。我们模拟了 100 个活跃的 Vim 丘脑模型神经元群体,群体产生的局部场电位(LFP)被用作 DBS 幅度闭环控制的反馈(控制)变量。基于丘脑活动与震颤之间的谱内容的相关性(Hua,1998 年),(Lenz,1988 年),我们实施了一个自适应最小方差控制器来调节模拟 LFPs 的功率谱,并将震颤条件下的 LFP 功率谱恢复到无震颤条件下的参考谱。控制器基于刺激输入和 LFP 输出之间关系的递归识别自回归模型(ARX),并通过在 theta(2-7Hz)、alpha(7-13Hz)和 beta(13-35Hz)频带中选择性地改变来出色地跟踪参考谱特征。这些变化反映了模型神经元群体的放电模式的修改,并且与开环 DBS 不同,用类似于无震颤条件下模拟的模式代替与震颤相关的病理模式。闭环控制器产生的 LFP 谱比开环固定强度刺激更接近无震颤条件下的谱,并适应于神经元振荡频率变化后的谱。这项计算研究表明,DBS 幅度闭环控制调节局部场电位谱并使震颤时存在的异常神经元活动模式正常化是可行的。

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