Functional Mechanisms of Recovery after Chronic Stroke: Modeling with the Virtual Brain.
Functional Mechanisms of Recovery after Chronic Stroke: Modeling with the Virtual Brain.
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DOI：
10.1523/eneuro.0158-15.2016
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发表时间：
2016-03
期刊：
影响因子：
3.4
通讯作者：
Solodkin A
中科院分区：
文献类型：
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作者：
Falcon MI;Riley JD;Jirsa V;McIntosh AR;Chen EE;Solodkin A
我们在了解中风康复的机制方面取得了重要进展，但基础科学和应用科学之间以及从大数据到个性化疗法之间的有效转化联系，才能真正开发中风的治疗方法。我们提出了这样一种方法，使用虚拟大脑（TVB），神经信息学平台，使用经验神经成像数据来创建一个人的人脑的动态模型，具体来说，我们模拟功能磁共振成像信号建模参数与脑卒中后的动态。在20名中风患者和11名对照者中，我们获得了静息fMRI、T1 w和弥散张量成像（DTI）数据。在治疗前、治疗后和治疗后6-12个月评估运动表现。基于DTI得到的单个结构连接体，在TVB平台上完成了以下步骤：（1）局部和全局参数的优化（2）使用优化的参数值模拟BOLD信号;（3）通过将模拟信号的频率、幅度和相位与经验时间序列进行比较来验证模拟时间序列;（4）模型参数与临床表型的多元线性回归。与对照组相比，中风患者表现出一致的传导速度降低，局部动力学增加，局部抑制耦合减少。局部兴奋与运动恢复呈负相关，局部动力与运动恢复呈正相关。TVB揭示了一个破坏的中风后系统，有利于兴奋-抑制和局部-全局动力学，与现有的哺乳动物中风机制的文献一致。我们的研究结果表明TVB有潜力确定中风恢复的个体化生物标志物。
We have seen important strides in our understanding of mechanisms underlying stroke recovery, yet effective translational links between basic and applied sciences, as well as from big data to individualized therapies, are needed to truly develop a cure for stroke. We present such an approach using The Virtual Brain (TVB), a neuroinformatics platform that uses empirical neuroimaging data to create dynamic models of an individual’s human brain; specifically, we simulate fMRI signals by modeling parameters associated with brain dynamics after stroke. In 20 individuals with stroke and 11 controls, we obtained rest fMRI, T1w, and diffusion tensor imaging (DTI) data. Motor performance was assessed pre-therapy, post-therapy, and 6–12 months post-therapy. Based on individual structural connectomes derived from DTI, the following steps were performed in the TVB platform: (1) optimization of local and global parameters (conduction velocity, global coupling); (2) simulation of BOLD signal using optimized parameter values; (3) validation of simulated time series by comparing frequency, amplitude, and phase of the simulated signal with empirical time series; and (4) multivariate linear regression of model parameters with clinical phenotype. Compared with controls, individuals with stroke demonstrated a consistent reduction in conduction velocity, increased local dynamics, and reduced local inhibitory coupling. A negative relationship between local excitation and motor recovery, and a positive correlation between local dynamics and motor recovery were seen. TVB reveals a disrupted post-stroke system favoring excitation-over-inhibition and local-over-global dynamics, consistent with existing mammal literature on stroke mechanisms. Our results point to the potential of TVB to determine individualized biomarkers of stroke recovery.