Mapping Brain Networks Using Multimodal Data

Abstract

AbstractBrains of human, as well as of other species, are all known to be organized into distinct neural networks, which have been found to serve as the basis for various brain functions and behaviors. More importantly, changes in brain networks are widely reported to be associated with almost all neurological and psychiatric disorders. Till now, numerous studies have been conducted to develop novel neuroimaging instruments and computational algorithms for both characterizing brain networks and investigating their behaviors in various populations of participants and patients. In this chapter, we discuss the state-of-the-art of these technologies in studying human brain networks and their applications to address fundamental questions in both basic and clinical neurosciences. We start our discussions on brain network mapping using individual neuroimaging modalities, i.e., functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), electroencephalography, electrocorticography (ECoG), positron emission tomography (PET), and functional near-infrared spectroscopy (fNIRS). We then continue with arguments on the value of multimodal neuroimaging technologies in studying human brain networks, which could achieve a “greater than the sum of its parts” knowledge about human brain networks due to complementary information provided by individual neuroimaging modalities. We discuss in particular on approaches deriving and characterizing intrinsic brain networks and their clinical applications, which are among the most significant findings about human brain networks in the past two decades. At the end, we further present our prospects on future works to address challenges in studying human brain networks, which could pave the way for the broad applications of brain networks in clinical and other real-world applications.KeywordsIntrinsic brain networksMultimodal dataEEGMEGfMRIPETfNIRSBasic neuroscienceClinical neuroscience