Duchet Benoit, Weerasinghe Gihan, Cagnan Hayriye, Brown Peter, Bick Christian, Bogacz Rafal
Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK.
MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
J Math Neurosci. 2020 Mar 30;10(1):4. doi: 10.1186/s13408-020-00081-0.
Essential tremor manifests predominantly as a tremor of the upper limbs. One therapy option is high-frequency deep brain stimulation, which continuously delivers electrical stimulation to the ventral intermediate nucleus of the thalamus at about 130 Hz. Constant stimulation can lead to side effects, it is therefore desirable to find ways to stimulate less while maintaining clinical efficacy. One strategy, phase-locked deep brain stimulation, consists of stimulating according to the phase of the tremor. To advance methods to optimise deep brain stimulation while providing insights into tremor circuits, we ask the question: can the effects of phase-locked stimulation be accounted for by a canonical Wilson-Cowan model? We first analyse patient data, and identify in half of the datasets significant dependence of the effects of stimulation on the phase at which stimulation is provided. The full nonlinear Wilson-Cowan model is fitted to datasets identified as statistically significant, and we show that in each case the model can fit to the dynamics of patient tremor as well as to the phase response curve. The vast majority of top fits are stable foci. The model provides satisfactory prediction of how patient tremor will react to phase-locked stimulation by predicting patient amplitude response curves although they were not explicitly fitted. We also approximate response curves of the significant datasets by providing analytical results for the linearisation of a stable focus model, a simplification of the Wilson-Cowan model in the stable focus regime. We report that the nonlinear Wilson-Cowan model is able to describe response to stimulation more precisely than the linearisation.
特发性震颤主要表现为上肢震颤。一种治疗选择是高频深部脑刺激,它以约130Hz的频率持续向丘脑腹中间核传递电刺激。持续刺激会导致副作用,因此需要找到在保持临床疗效的同时减少刺激的方法。一种策略是锁相深部脑刺激,即根据震颤的相位进行刺激。为了推进优化深部脑刺激的方法并深入了解震颤回路,我们提出一个问题:锁相刺激的效果能否用经典的威尔逊 - 考恩模型来解释?我们首先分析患者数据,发现在一半的数据集中,刺激效果对刺激所施加的相位存在显著依赖性。将完整的非线性威尔逊 - 考恩模型拟合到被确定为具有统计学显著性的数据集上,我们表明在每种情况下,该模型都能拟合患者震颤的动态以及相位响应曲线。绝大多数最佳拟合是稳定焦点。该模型通过预测患者振幅响应曲线,对患者震颤如何对锁相刺激做出反应提供了令人满意的预测,尽管这些曲线并非明确拟合得到。我们还通过给出稳定焦点模型线性化的分析结果来近似显著数据集的响应曲线,稳定焦点模型是威尔逊 - 考恩模型在稳定焦点区域的简化形式。我们报告称,非线性威尔逊 - 考恩模型比线性化模型能够更精确地描述对刺激的反应。