标题： 多层网络在神经成像中的应用 显示英文标题

标题： Multilayer Networks in Neuroimaging

摘要： 近年来，网络科学的进展被应用于\textit{体内}脑记录，为更好地理解大脑的结构和功能铺平了道路。 然而，尽管它在神经科学中显然有用，传统的网络科学缺乏对这两个领域之间相互关系进行——如此重要——同时研究的工具。 在本章中，我探讨多层网络在构建大脑生成模型中的日益重要的作用，以及这些模型揭示跨越多个尺度和模态的大脑复杂时空交互的全部信息的能力。 首先，我从大脑网络的理论基础开始，并简要概述传统网络及其在构建多层网络模型中的作用。 然后，我深入探讨多层网络在神经科学中的应用，特别是在解码结构-功能关系、建模疾病和整合多尺度和多模态数据方面。 最后，我展示了将多层框架引入网络神经科学如何揭示了大脑网络之前隐藏的特征，以及多层网络如何能提供新的见解并描述大脑的结构和功能。 显示英文摘要

摘要： Recent advances in network science, applied to \textit{in vivo} brain recordings, have paved the way for better understanding of the structure and function of the brain. However, despite its obvious usefulness in neuroscience, traditional network science lacks tools for -- so important -- simultaneous investigation of the inter-relationship between the two domains. In this chapter, I explore the increasing role of multilayer networks in building brain generative models and abilities of such models to uncover the full information about the brain complex spatiotemporal interactions that span across multiple scales and modalities. First, I begin with the theoretical foundation of brain networks accompanied by a brief overview of traditional networks and their role in constructing multilayer network models. Then, I delve into the applications of multilayer networks in neuroscience, particularly in deciphering structure-function relationship, modelling diseases, and integrating multi-scale and multi-modal data. Finally, I demonstrate how incorporating the multilayer framework into network neuroscience has brought to light previously hidden features of brain networks and, how multilayer networks can provide new insights and a description of the structure and function of the brain.