Yousif Nada, Mace Michael, Pavese Nicola, Borisyuk Roman, Nandi Dipankar, Bain Peter
Division of Brain Sciences, Imperial College London, London, United Kingdom.
School of Engineering and Technology, University of Hertfordshire, Hatfield, United Kingdom.
PLoS Comput Biol. 2017 Jan 9;13(1):e1005326. doi: 10.1371/journal.pcbi.1005326. eCollection 2017 Jan.
Essential tremor (ET), a movement disorder characterised by an uncontrollable shaking of the affected body part, is often professed to be the most common movement disorder, affecting up to one percent of adults over 40 years of age. The precise cause of ET is unknown, however pathological oscillations of a network of a number of brain regions are implicated in leading to the disorder. Deep brain stimulation (DBS) is a clinical therapy used to alleviate the symptoms of a number of movement disorders. DBS involves the surgical implantation of electrodes into specific nuclei in the brain. For ET the targeted region is the ventralis intermedius (Vim) nucleus of the thalamus. Though DBS is effective for treating ET, the mechanism through which the therapeutic effect is obtained is not understood. To elucidate the mechanism underlying the pathological network activity and the effect of DBS on such activity, we take a computational modelling approach combined with electrophysiological data. The pathological brain activity was recorded intra-operatively via implanted DBS electrodes, whilst simultaneously recording muscle activity of the affected limbs. We modelled the network hypothesised to underlie ET using the Wilson-Cowan approach. The modelled network exhibited oscillatory behaviour within the tremor frequency range, as did our electrophysiological data. By applying a DBS-like input we suppressed these oscillations. This study shows that the dynamics of the ET network support oscillations at the tremor frequency and the application of a DBS-like input disrupts this activity, which could be one mechanism underlying the therapeutic benefit.
特发性震颤（ET）是一种运动障碍，其特征是受影响身体部位出现无法控制的抖动，常被认为是最常见的运动障碍，影响着高达1%的40岁以上成年人。ET的确切病因尚不清楚，然而，多个脑区网络的病理性振荡被认为与该疾病的发生有关。深部脑刺激（DBS）是一种用于缓解多种运动障碍症状的临床治疗方法。DBS包括将电极手术植入大脑的特定核团。对于ET，目标区域是丘脑的腹中间核（Vim）。虽然DBS对治疗ET有效，但其获得治疗效果的机制尚不清楚。为了阐明病理性网络活动的潜在机制以及DBS对这种活动的影响，我们采用了结合电生理数据的计算建模方法。术中通过植入的DBS电极记录病理性脑活动，同时记录受影响肢体的肌肉活动。我们使用Wilson-Cowan方法对假设为ET基础的网络进行建模。建模网络在震颤频率范围内表现出振荡行为，我们的电生理数据也是如此。通过应用类似DBS的输入，我们抑制了这些振荡。这项研究表明，ET网络的动力学支持震颤频率下的振荡，而类似DBS的输入应用会破坏这种活动，这可能是治疗益处的一种潜在机制。
