Tahedl Marlene, Levine Seth M, Greenlee Mark W, Weissert Robert, Schwarzbach Jens V
Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany.
Institute for Experimental Psychology, University of Regensburg, Regensburg, Germany.
Front Neurol. 2018 Oct 11;9:828. doi: 10.3389/fneur.2018.00828. eCollection 2018.
Multiple sclerosis is a debilitating disorder resulting from scattered lesions in the central nervous system. Because of the high variability of the lesion patterns between patients, it is difficult to relate existing biomarkers to symptoms and their progression. The scattered nature of lesions in multiple sclerosis offers itself to be studied through the lens of network analyses. Recent research into multiple sclerosis has taken such a network approach by making use of functional connectivity. In this review, we briefly introduce measures of functional connectivity and how to compute them. We then identify several common observations resulting from this approach: (a) high likelihood of altered connectivity in deep-gray matter regions, (b) decrease of brain modularity, (c) hemispheric asymmetries in connectivity alterations, and (d) correspondence of behavioral symptoms with task-related and task-unrelated networks. We propose incorporating such connectivity analyses into longitudinal studies in order to improve our understanding of the underlying mechanisms affected by multiple sclerosis, which can consequently offer a promising route to individualizing imaging-related biomarkers for multiple sclerosis.
多发性硬化症是一种由中枢神经系统中散在病变引起的致残性疾病。由于患者之间病变模式的高度变异性，很难将现有的生物标志物与症状及其进展联系起来。多发性硬化症中病变的散在性质适合通过网络分析的视角进行研究。最近对多发性硬化症的研究通过利用功能连接性采用了这种网络方法。在本综述中，我们简要介绍功能连接性的测量方法及其计算方式。然后，我们确定了这种方法产生的几个常见观察结果：(a) 深部灰质区域连接性改变的高可能性，(b) 脑模块化的降低，(c) 连接性改变中的半球不对称性，以及 (d) 行为症状与任务相关和任务无关网络的对应关系。我们建议将这种连接性分析纳入纵向研究，以增进我们对受多发性硬化症影响的潜在机制的理解，从而为多发性硬化症的个体化影像相关生物标志物提供一条有前景的途径。
