The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke.
The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke.
复制标题
DOI：
10.3389/fneur.2015.00228
复制
发表时间：
2015
影响因子：
3.4
通讯作者：
Solodkin A
中科院分区：
文献类型：
--
作者：
Falcon MI;Riley JD;Jirsa V;McIntosh AR;Shereen AD;Chen EE;Solodkin A
目前，中风幸存者的恢复仍有相当大的可变性。为解决这一问题，开展个体化治疗已成为脑卒中治疗的重要目标。作为第一步，有必要确定与中风和恢复相关的脑动力学。虽然最近的方法在这个方向上取得了长足的进步，但我们仍然缺乏生理生物标志物。虚拟脑（TVB）是一种新颖的脑动力学建模应用，它通过将个体自身的神经成像数据与局部生物物理模型相结合来模拟个体的大脑活动。在这里，我们详细描述了TVB建模过程，并探讨了与笔画相关的模型参数。为了在这种新型建模和目前使用的建模之间建立平行关系，在这项工作中，我们建立了一个特定的TVB参数（远程耦合）之间的关联，该参数在笔画后与图形分析得出的指标之间增加。我们使用TVB模拟20例脑卒中患者和10例健康对照者的个体BOLD信号。我们对它们的结构连通性矩阵进行图分析，计算度中心性、中间中心性和全局效率。线性回归分析表明，远程耦合与整体效率呈负相关（P = 0.038），但与度中心性和中间中心性无关。我们的研究结果表明，通过远程耦合参数看到的局部动力学的较大影响与系统效率的降低密切相关。因此，我们提出，TVB中远程参数的增加（表明局部动力学比全局动力学更倾向于局部动力学）是有害的，因为它减少了通信，正如效率降低所表明的那样。因此，新的模型平台TVB为理解脑卒中后全球脑动力学的生物物理参数提供了一个新的视角，允许设计集中的治疗干预措施。
There currently remains considerable variability in stroke survivor recovery. To address this, developing individualized treatment has become an important goal in stroke treatment. As a first step, it is necessary to determine brain dynamics associated with stroke and recovery. While recent methods have made strides in this direction, we still lack physiological biomarkers. The Virtual Brain (TVB) is a novel application for modeling brain dynamics that simulates an individual’s brain activity by integrating their own neuroimaging data with local biophysical models. Here, we give a detailed description of the TVB modeling process and explore model parameters associated with stroke. In order to establish a parallel between this new type of modeling and those currently in use, in this work we establish an association between a specific TVB parameter (long-range coupling) that increases after stroke with metrics derived from graph analysis. We used TVB to simulate the individual BOLD signals for 20 patients with stroke and 10 healthy controls. We performed graph analysis on their structural connectivity matrices calculating degree centrality, betweenness centrality, and global efficiency. Linear regression analysis demonstrated that long-range coupling is negatively correlated with global efficiency (P = 0.038), but is not correlated with degree centrality or betweenness centrality. Our results suggest that the larger influence of local dynamics seen through the long-range coupling parameter is closely associated with a decreased efficiency of the system. We thus propose that the increase in the long-range parameter in TVB (indicating a bias toward local over global dynamics) is deleterious because it reduces communication as suggested by the decrease in efficiency. The new model platform TVB hence provides a novel perspective to understanding biophysical parameters responsible for global brain dynamics after stroke, allowing the design of focused therapeutic interventions.