ABSTRACT

The increasing adoption of brain imaging methods has greatly augmented our understanding of the neural underpinnings of communication processes. Enabled by recent advancements in mathematics and computational infrastructure, researchers have begun to move beyond traditional univariate analytic techniques in favor of methods that consider the brain in terms of evolving networks of interactions between brain regions. This network neuroscience approach is a potential boon to communication and media psychology research but also requires a careful look at the complications inherent in adopting a novel (and complex) methodological tool. In this manuscript, we provide an overview of network neuroscience in view of the needs of communication neuroscientists, discussing considerations that must be taken into account when constructing networks from neuroimaging data and conducting statistical tests on these networks. Throughout the manuscript, we highlight research domains in which network neuroscience is likely to be particularly useful for increasing theoretical clarity in communication and media psychology research.

抽象的

脑成像方法的日益普及极大地增进了我们对交流过程的神经基础的理解。由于数学和计算基础设施的最新发展，研究人员已开始超越传统的单变量分析技术，转而考虑根据大脑区域之间相互作用网络的演化来考虑大脑的方法。这个网络神经科学这种方法是传播和媒体心理学研究的潜在收益，但也需要仔细研究采用一种新颖（复杂）的方法论工具所固有的复杂性。在此手稿中，我们根据交流神经科学家的需求提供了网络神经科学的概述，讨论了从神经影像数据构建网络并在这些网络上进行统计测试时必须考虑的考虑因素。在整个手稿中，我们重点介绍了研究领域，其中网络神经科学可能对于提高传播和媒体心理学研究的理论清晰度特别有用。