Predicting the effects of deep brain stimulation using a reduced coupled oscillator model
Predicting the effects of deep brain stimulation using a reduced coupled oscillator model
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DOI：
10.1101/448290
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发表时间：
2018-10
影响因子：
4.3
通讯作者：
G. Weerasinghe;Benoit Duchet;Hayriye Cagnan;P. Brown;C. Bick;R. Bogacz
中科院分区：
文献类型：
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作者：
G. Weerasinghe;Benoit Duchet;Hayriye Cagnan;P. Brown;C. Bick;R. Bogacz
脑深部电刺激（DBS）被认为是一种有效的治疗各种神经系统疾病，包括帕金森病和原发性震颤（ET）。目前，它涉及通过植入大脑的电极管理一系列恒定频率的脉冲。新的“闭环”方法涉及根据正在进行的症状或大脑活动提供刺激，并有可能在效率，疗效和减少副作用方面提供改进。闭环DBS的成功取决于能够设计一种刺激策略，该策略最大限度地减少与运动障碍症状相关的神经活动的振荡。一个有用的垫脚石是构建一个数学模型，它可以描述当在系统的特定状态下施加刺激时，脑振荡应该如何变化。我们的工作重点是使用耦合振荡器来代表神经元在产生病理性振荡的领域。使用简化形式的仓本模型，我们分析了当神经振荡具有给定的相位和振幅时，患者应该如何对刺激做出反应。我们预测，在满足一定条件的情况下，最好的刺激策略应该是相位特异性的，而且如果在脑振荡的振幅较低时施加刺激，则刺激应该具有更大的效果。我们将这一令人惊讶的预测与ET患者的数据进行了比较。根据我们的预测，我们还提出了一种新的混合策略，有效地结合了文献中发现的两种策略，即锁相和自适应DBS。作者总结脑深部电刺激（DBS）涉及将电脉冲传递到大脑内的目标部位，是一种经验证的治疗各种神经系统疾病的方法。闭环DBS是一种有前途的新方法，根据患者的状态施加刺激。这种方法成功的关键是能够预测患者对刺激的反应。我们的工作重点是DBS应用于特发性震颤（ET）患者。在理论模型的基础上，将神经元描述为对刺激做出反应并具有一定同步趋势的振荡器，我们预测了当刺激以特定相位和持续震颤振荡的振幅施加时，患者应如何反应。以前的闭环DBS的实验研究提供的刺激的基础上正在进行的相位或振幅的病理振荡。我们的研究表明，这两种测量方法都可以用来控制刺激。作为这项工作的一部分，我们还在实验数据中寻找我们理论的证据，并发现我们的预测在一个病人身上得到了满足。从这项工作中获得的见解应导致更好地了解如何优化闭环DBS策略。
Deep brain stimulation (DBS) is known to be an effective treatment for a variety of neurological disorders, including Parkinson’s disease and essential tremor (ET). At present, it involves administering a train of pulses with constant frequency via electrodes implanted into the brain. New ‘closed-loop’ approaches involve delivering stimulation according to the ongoing symptoms or brain activity and have the potential to provide improvements in terms of efficiency, efficacy and reduction of side effects. The success of closed-loop DBS depends on being able to devise a stimulation strategy that minimizes oscillations in neural activity associated with symptoms of motor disorders. A useful stepping stone towards this is to construct a mathematical model, which can describe how the brain oscillations should change when stimulation is applied at a particular state of the system. Our work focuses on the use of coupled oscillators to represent neurons in areas generating pathological oscillations. Using a reduced form of the Kuramoto model, we analyse how a patient should respond to stimulation when neural oscillations have a given phase and amplitude. We predict that, provided certain conditions are satisfied, the best stimulation strategy should be phase specific but also that stimulation should have a greater effect if applied when the amplitude of brain oscillations is lower. We compare this surprising prediction with data obtained from ET patients. In light of our predictions, we also propose a new hybrid strategy which effectively combines two of the strategies found in the literature, namely phase-locked and adaptive DBS. Author summary Deep brain stimulation (DBS) involves delivering electrical impulses to target sites within the brain and is a proven therapy for a variety of neurological disorders. Closed loop DBS is a promising new approach where stimulation is applied according to the state of a patient. Crucial to the success of this approach is being able to predict how a patient should respond to stimulation. Our work focusses on DBS as applied to patients with essential tremor (ET). On the basis of a theoretical model, which describes neurons as oscillators that respond to stimulation and have a certain tendency to synchronize, we provide predictions for how a patient should respond when stimulation is applied at a particular phase and amplitude of the ongoing tremor oscillations. Previous experimental studies of closed loop DBS provided stimulation either on the basis of ongoing phase or amplitude of pathological oscillations. Our study suggests how both of these measurements can be used to control stimulation. As part of this work, we also look for evidence for our theories in experimental data and find our predictions to be satisfied in one patient. The insights obtained from this work should lead to a better understanding of how to optimise closed loop DBS strategies.