D-BEST Lab, Departments of Computer Science and Engineering and Biomedical Engineering, University of Bridgeport, Bridgeport, CT, United States of America.
Department of Electrical Engineering, University of Bridgeport, Bridgeport, CT, United States of America.
PLoS One. 2018 Nov 20;13(11):e0207761. doi: 10.1371/journal.pone.0207761. eCollection 2018.
The hyperkinetic symptoms of Parkinson's Disease (PD) are associated with the ensembles of interacting oscillators that cause excess or abnormal synchronous behavior within the Basal Ganglia (BG) circuitry. Delayed feedback stimulation is a closed loop technique shown to suppress this synchronous oscillatory activity. Deep Brain Stimulation (DBS) via delayed feedback is known to destabilize the complex intermittent synchronous states. Computational models of the BG network are often introduced to investigate the effect of delayed feedback high frequency stimulation on partially synchronized dynamics. In this study, we develop a reduced order model of four interacting nuclei of the BG as well as considering the Thalamo-Cortical local effects on the oscillatory dynamics. This model is able to capture the emergence of 34 Hz beta band oscillations seen in the Local Field Potential (LFP) recordings of the PD state. Train of high frequency pulses in a delayed feedback stimulation has shown deficiencies such as strengthening the synchronization in case of highly fluctuating neuronal activities, increasing the energy consumed as well as the incapability of activating all neurons in a large-scale network. To overcome these drawbacks, we propose a new feedback control variable based on the filtered and linearly delayed LFP recordings. The proposed control variable is then used to modulate the frequency of the stimulation signal rather than its amplitude. In strongly coupled networks, oscillations reoccur as soon as the amplitude of the stimulus signal declines. Therefore, we show that maintaining a fixed amplitude and modulating the frequency might ameliorate the desynchronization process, increase the battery lifespan and activate substantial regions of the administered DBS electrode. The charge balanced stimulus pulse itself is embedded with a delay period between its charges to grant robust desynchronization with lower amplitudes needed. The efficiency of the proposed Frequency Adjustment Stimulation (FAS) protocol in a delayed feedback method might contribute to further investigation of DBS modulations aspired to address a wide range of abnormal oscillatory behavior observed in neurological disorders.
帕金森病（PD）的多动症状与引起基底神经节（BG）回路中过度或异常同步行为的相互作用振荡器的集合有关。延迟反馈刺激是一种闭环技术，已被证明可抑制这种同步振荡活动。已知通过延迟反馈的深部脑刺激（DBS）会破坏复杂的间歇性同步状态。通常会引入 BG 网络的计算模型来研究延迟反馈高频刺激对部分同步动力学的影响。在这项研究中，我们开发了一个简化模型，该模型由四个相互作用的 BG 核以及考虑丘脑皮质对振荡动力学的局部影响组成。该模型能够捕获 PD 状态下局部场电位（LFP）记录中出现的 34 Hz β波段振荡。延迟反馈刺激中的高频脉冲串已显示出一些缺陷，例如在神经元活动高度波动的情况下增强同步性，增加能量消耗以及无法激活大网络中的所有神经元。为了克服这些缺点，我们提出了一种基于 LFP 滤波和线性延迟记录的新反馈控制变量。然后，使用该控制变量来调制刺激信号的频率，而不是其幅度。在强耦合网络中，只要刺激信号的幅度下降，振荡就会再次出现。因此，我们表明，保持固定幅度并调制频率可能会改善去同步化过程，增加电池寿命并激活所施加的 DBS 电极的大部分区域。带有延迟周期的平衡电荷刺激脉冲本身嵌入在电荷之间，以在需要较低幅度的情况下提供鲁棒去同步化。在延迟反馈方法中，所提出的频率调整刺激（FAS）方案的效率可能有助于进一步研究 DBS 调制，以解决在神经紊乱中观察到的广泛异常振荡行为。
