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Efficient Computation of the Neural Activation during Deep Brain Stimulation for Dispersive Electrical Properties of Brain Tissue

机译:高脑刺激治疗脑组织分散电特性的神经激活的高效计算

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Deep brain stimulation (DBS) is a widely employed neurosurgical method to treat symptoms of neurodegenerative disorders. Computational modeling of DBS can help to gain insight into the mechanisms of its action. Among these models, the estimation of the volume of tissue activated (VTA) comprises a method to predict the extent of beneficial stimulation and unwanted side effects. This method requires the computation of the time-dependent extracellular potential in the proximity of the stimulation electrode, which is, in general, computationally expensive due to the dispersive electrical properties of brain tissue. We present an adaptive scheme based on two interpolation methods, which approximates the transfer function of the extracellular potential distribution in the frequency-domain. The results suggest that the proposed method is able to substantially reduce the computational expense for the computation of the extracellular field distribution and VTA compared to the standard approach.
机译:深脑刺激(DBS)是一种广泛采用的神经外科方法,以治疗神经变性障碍的症状。 DBS的计算建模可以有助于深入了解其行动的机制。在这些模型中,活化(VTA)的组织体积的估计包括预测有益刺激和不需要的副作用的程度的方法。该方法需要计算刺激电极接近的时间依赖性细胞外电位,这通常是由于脑组织的色散电性能而计算地计算地昂贵。我们提出了一种基于两个插值方法的自适应方案,其近似于频域中的细胞外势分布的传递函数。结果表明,与标准方法相比,所提出的方法能够大大降低计算细胞外场分布和VTA的计算费用。

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