An important aspect of neuroscience is to characterize the underlying connectivity patterns of the human brain (i.e., human connectomics). Over the past few years, researchers have demonstrated that by combining a variety of different neuroimaging technologies (e.g., structural MRI, diffusion MRI and functional MRI) with sophisticated analytic strategies such as graph theory, it is possible to noninvasively map the patterns of structural and functional connectivity of human whole-brain networks. With these novel approaches, many studies have shown that human brain networks have nonrandom properties such as modularity, small-worldness and highly connected hubs. Importantly, these quantifiable network properties change with age, learning and disease. Moreover, there is growing evidence for behavioral and genetic correlates. Network analysis of neuroimaging data is opening up a new avenue of research into the understanding of the organizational principles of the brain that will be of interest for all basic scientists and clinical researchers. Such approaches are powerful but there are a number of challenging issues when extracting reliable brain networks from various imaging modalities and analyzing the topological properties, e.g., definitions of network nodes and edges and reproducibility of network analysis. We assembled contributions related to the state-of-the-art methodologies of brain connectivity and the applications involving development, aging and neuropsychiatric disorders such as Alzheimer’s disease, schizophrenia, attention deficit hyperactivity disorder and mood and anxiety disorders. It is anticipated that the articles in this Research Topic will provide a greater range and depth of provision for the field of imaging connectomics.

Brain imaging technology remains at the forefront of advances in both our understanding of the brain and our ability to diagnose and treat brain disease and disorders. Imaging of the Human Brain in Health and Disease examines the localization of neurotransmitter receptors in the nervous system of normal, healthy humans and compares that with humans who are suffering from various neurologic diseases. Opening chapters introduce the basic science of imaging neurotransmitters, including sigma, acetylcholine, opioid, and dopamine receptors. Imaging the healthy and diseased brain includes brain imaging of anger, pain, autism, the release of dopamine, the impact of cannabinoids, and Alzheimer's disease. This book is a valuable companion to a wide range of scholars, students, and researchers in neuroscience, clinical neurology, and psychiatry, and provides a detailed introduction to the application of advanced imaging to the treatment of brain disorders and disease. - A focused introduction to imaging healthy and diseased brains - Focuses on the primary neurotransmitter release - Includes sigma, acetylcholine, opioid, and dopamine receptors - Presents the imaging of healthy and diseased brains via anger, pain, autism, and Alzheimer's disease

The widespread application of brain imaging to the study of psychiatric disorders has led to a revolution in our understanding of the neural basis of psychiatric illness. In particular, the advent of magnetic resonance imaging (MRI) has provided an unprecedented capacity for quantifying diverse aspects of brain structure and function in vivo, and has been used to identify brain changes associated with the full spectrum of psychopathology. With respect to major psychiatric disorders, it is now abundantly clear from this literature that focal brain dysfunction is rare. Rather, most disorders are associated with abnormalities in large-scale networks of spatially distributed and interconnected brain regions; i.e., they are disorders of brain connectivity. Such considerations highlight the need to understand brain dysfunction in psychiatric illness from a network-based perspective. This goal is starting to be realized through recent advances in the use of MRI to map the brain’s complex connectivity architecture. In this special edition, we invite contributions that address brain network dysfunction in psychiatric illnesses. Specifically, the work must be concerned with understanding interactions between brain regions, and how their alterations are affected by psychiatric disease. These interactions can be studied at the level of anatomy using diffusion-MRI or function using functional MRI (fMRI), with the full range of methods available (e.g., tractography, seed-based correlations, independent component analysis, graph analysis, dynamic causal modeling, etc.). Contributions can be either reviews of recent, relevant literature addressing brain network dysfunction in psychiatric disease, or experimental papers describing novel insights into brain network disturbances in such illnesses. Contributions will be invited covering a broad spectrum of psychiatric disease, including mood and anxiety disorders, schizophrenia, autism, attention-deficit hyperactivity disorder and neurodegenerative conditions. It is intended that this volume will provide important insights into how brain networks are perturbed by psychiatric disease, and allow identification of commonalities and differences across diagnostic categories.

The brain is the most complex computational device we know, consisting of highly interacting and redundant networks of areas, supporting specific brain functions. The rules by which these areas organize themselves to perform specific computations have only now started to be uncovered. Advances in non-invasive neuroimaging technologies have revolutionized our understanding of the functional anatomy of cortical circuits in health and disease states, which is the focus of this book. The first section of this book focuses on methodological issues, such as combining functional MRI technology with other brain imaging modalities. The second section examines the application of brain neuroimaging to understand cognitive, visual, auditory, motor and decision-making networks, as well as neurological diseases. The use of non-invasive neuroimaging technologies will continue to stimulate an exponential growth in understanding basic brain processes, largely as a result of sustained advances in neuroimaging methods and applications.

Notable experts in the field of neuroimaging provide comprehensive overviews of advances in functional and structural aspects of both common and uncommon brain disorders. Functional imaging is evolving quickly but researchers and clinicians do not always have a strong understanding of the fundamental basis of the imaging techniques that they use. By focusing on both structure and function this book will provide a strong foundation for emerging developments in the field.

Advances in Resting-State Functional MRI: Methods, Interpretation, and Applications gives readers with basic neuroimaging experience an up-to-date and in-depth understanding of the methods, opportunities, and challenges in rs-fMRI. The book covers current knowledge gaps in rs-fMRI, including "what are biologically plausible brain networks," "how to tell what part is noise," "how to perform quality assurance on the data," "what are the spatial and temporal limits of our ability to resolve FC," and "how to best identify network features related to individual differences or disease state". This book is an ideal reference for neuroscientists, computational neuroscientists, psychologists, biomedical engineers, physicists and medical physicists. Both new and more advanced researchers alike will be able to discover new information distilled from the past decade of research to become well-versed in rs-fMRI-related topics. - Presents the first book to explain the latest methods, opportunities and challenges of Resting-state Functional MRI - Edited and authored by leading researchers in fMRI - Includes neuroscientific and clinical applications

In the last thirty years, Magnetic Resonance has generated a wide revolution in biomedical research and in medical imaging in general. More recently, the "in vivo" studies of the human brain were extended by new original ways to the dynamic study of function and metabolism of the human brain. The enormous interest in expanding the investigation of the brain is emphasizing the search for new NMR methods capable of extracting information of so-far obscure aspects of the brain function. In fact, many quantitative approaches have been proposed in order to complement the information obtained by functional MRI, and several multimodal and multiparametric approaches have been developed to exploit the information, either functional or structural, made available by the flexible contrast generation typical of MRI, and to combine it with complementary information. The XII workshop of the International School on Magnetic Resonanceand Brain Function, held in Erice between 17 April and 6 May, 2016, was specially devoted to novel approaches aimed at better structural characterization of brain diseases, and at investigating frontiers MRI approaches to better understand the brain function. The papers included in this eBook offer a broad overview of the subjects covered during the Workshop, including applications of multiparametric MRI to neurological diseases, multimodal combination of MRI with electrophysiology, advanced methods for the investigation of brain networks and of brain physiology, and perspectives towards brain state reading.

This issue of Neuroimaging Clinics of North America focuses on Functional Connectivity, and is edited by Dr. Jay Pillai. Articles will include: Applications of rs-fMRI to presurgical mapping: sensorimotor mapping; Dynamic functional connectivity methods; Machine learning applications to rs-fMRI analysis; Frequency domain analysis of rs-fMRI; Applications of rs-fMRI to epilepsy; Data-driven analysis methods for rs-fMRI; Applications of rs-fMRI to presurgical mapping: language mapping; Limitations of rs-fMRI in the setting of focal brain lesions; Applications of rs-fMRI to neuropsychiatric disease; Applications of rs-fMRI to Traumatic Brain Injury; Applications of rs-fMRI to neurodegenerative disease; Graph theoretic analysis of rs-fMRI; and more!

Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. - Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology - Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems - Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience - Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain