Seo Hyeon, Jun Sung C
School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea.
Front Hum Neurosci. 2017 Oct 26;11:515. doi: 10.3389/fnhum.2017.00515. eCollection 2017.
Electrical brain stimulation (EBS) is an appealing method to treat neurological disorders. To achieve optimal stimulation effects and a better understanding of the underlying brain mechanisms, neuroscientists have proposed computational modeling studies for a decade. Recently, multi-scale models that combine a volume conductor head model and multi-compartmental models of cortical neurons have been developed to predict stimulation effects on the macroscopic and microscopic levels more precisely. As the need for better computational models continues to increase, we overview here recent multi-scale modeling studies; we focused on approaches that coupled a simplified or high-resolution volume conductor head model and multi-compartmental models of cortical neurons, and constructed realistic fiber models using diffusion tensor imaging (DTI). Further implications for achieving better precision in estimating cellular responses are discussed.
脑电刺激（EBS）是一种治疗神经系统疾病的有吸引力的方法。为了实现最佳刺激效果并更好地理解潜在的脑机制，神经科学家已经提出了十年的计算建模研究。最近，结合了容积导体头部模型和皮质神经元多室模型的多尺度模型已经被开发出来，以更精确地预测宏观和微观层面的刺激效果。随着对更好的计算模型的需求持续增加，我们在此概述最近的多尺度建模研究；我们关注的方法是将简化或高分辨率的容积导体头部模型与皮质神经元的多室模型相结合，并使用扩散张量成像（DTI）构建逼真的纤维模型。还讨论了在估计细胞反应方面实现更高精度的进一步意义。
