Multilayer Networks in Neuroimaging

Recent advances in network science, applied to in vivo brain recordings, have significantly improved our understanding of brain structure and function. However, despite its obvious usefulness in neuroscience, traditional network science lacks the tools needed for – so important – the simultaneous investigation of the inter-relationship between the two domains. This chapter focuses on the growing role of multilayer networks in developing generative models of the brain and their potential to capture the complex spatiotemporal interactions that extend across multiple scales and modalities. I begin by outlining the theoretical foundations of brain networks, including a brief overview of traditional network models and their relevance for constructing multilayer frameworks. I then focus on applications of multilayer networks in neuroimaging, with particular emphasis on uncovering structure–function relationships, modelling disease and integrating multiscale and multimodal data. Finally, I show how adopting a multilayer perspective has revealed previously hidden features of brain organisation and discuss how this approach provides new insights into the structure and function of the brain.