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基于延迟反馈的神经群体模型中病理性振荡的抑制。

Delayed Feedback-Based Suppression of Pathological Oscillations in a Neural Mass Model.

出版信息

IEEE Trans Cybern. 2021 Oct;51(10):5046-5056. doi: 10.1109/TCYB.2019.2923317. Epub 2021 Oct 12.

Abstract

Suppression of excessively synchronous beta frequency (12-35 Hz) oscillatory activity in the basal ganglia is believed to correlate with the alleviation of hypokinetic motor symptoms of the Parkinson's disease. Delayed feedback is an effective strategy to interrupt the synchronization and has been used in the design of closed-loop neuromodulation methods computationally. Although tremendous efforts in this are being made by optimizing delayed feedback algorithm and stimulation waveforms, there are still remaining problems in the selection of effective parameters in the delayed feedback control schemes. In most delayed feedback neuromodulation strategies, the stimulation signal is obtained from the local field potential (LFP) of the excitatory subthalamic nucleus (STN) neurons and then is administered back to STN itself only. The inhibitory external globus pallidus (GPe) nucleus in the excitatory-inhibitory STN-GPe reciprocal network has not been involved in the design of the delayed feedback control strategies. Thus, considering the role of GPe, this paper proposes three schemes involving GPe in the design of the delayed feedback strategies and compared their effectiveness to the traditional paradigm using STN only. Based on a neural mass model of STN-GPe network having capability of simulating the LFP directly, the proposed stimulation strategies are tested and compared. Our simulation results show that the four types of delayed feedback control schemes are all effective, even if with a simple linear delayed feedback algorithm. But the three new control strategies we propose here further improve the control performance by enlarging the oscillatory suppression space and reducing the energy expenditure, suggesting that they may be more effective in applications. This paper may guide a new approach to optimize the closed-loop deep brain stimulation treatment to alleviate the Parkinsonian state by retargeting the measurement and stimulation nucleus.

摘要

抑制基底神经节中过度同步的β频率(12-35 Hz)振荡活动被认为与减轻帕金森病的运动迟缓症状有关。延迟反馈是中断同步的有效策略,已在计算中用于闭环神经调节方法的设计。尽管通过优化延迟反馈算法和刺激波形在这方面做出了巨大努力,但在延迟反馈控制方案中选择有效参数仍存在问题。在大多数延迟反馈神经调节策略中,刺激信号来自兴奋性丘脑底核(STN)神经元的局部场电位(LFP),然后仅将其施加回 STN 本身。兴奋性-抑制性 STN-GPe 相互作用网络中的抑制性苍白球外核(GPe)核未参与延迟反馈控制策略的设计。因此,考虑到 GPe 的作用,本文提出了三种涉及 GPe 的延迟反馈策略设计方案,并将其与仅使用 STN 的传统范式进行了比较。基于具有直接模拟 LFP 能力的 STN-GPe 网络的神经质量模型,测试和比较了所提出的刺激策略。我们的仿真结果表明,即使使用简单的线性延迟反馈算法,四种类型的延迟反馈控制方案都是有效的。但是,我们在这里提出的三种新控制策略通过扩大振荡抑制空间和减少能量消耗进一步提高了控制性能,这表明它们在应用中可能更有效。本文可能为通过重新定位测量和刺激核优化闭环深部脑刺激治疗以减轻帕金森状态提供一种新方法。

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