In the last few years, advances in human structural and functional neuroimaging (fMRI, PET, EEG/MEG) have resulted in an explosion of studies investigating the anatomical and functional connectivity between different regions of the brain. More and more studies have employed resting and task-related connectivity analyses to assess functional interactions, and diffusion-weighted tractography to study white matter organization. Many of these studies have addressed normal human function, but recently, a number of investigators have turned their attention to examining brain disorders. The study of brain disorders is a complex endeavor; not only does it require understanding the normal brain, and the regions involved in a particular function, but also it needs a deeper understanding of brain networks and their dynamics. This Research Topic will provide the scientific community with an overview of how to apply connectivity methods to study brain disease, and with perspectives on what are the strength and limitations of each modality. For this Research Topic, we solicit both reviews and original research articles on the use of brain connectivity analysis, with non-human or human models, to explore neurological, psychiatric, developmental and neurodegenerative disorders from a system perspective. Connectivity studies that have focused on one or more of the following will be of particular interest: (1) detection of abnormal functional/structural connectivity; (2) neural plasticity, assessed by changes in connectivity, in patients with brain disorders; (3) assessment of therapy using connectivity measures; (4) relation of connectivity changes to behavioral changes.

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

Connectomic Deep Brain Stimulation (DBS) covers this highly efficacious treatment option for movement disorders such as Parkinson’s Disease, Essential Tremor and Dystonia. The book examines its impact on distributed brain networks that span across the human brain in parallel with modern-day neuroimaging concepts and the connectomics of the brain. It asks several questions, including which cortical areas should DBS electrodes be connected in order to generate the highest possible clinical improvement? Which connections should be avoided? Could these connectomic insights be used to better understand the mechanism of action of DBS? How can they be transferred to individual patients, and more. This book is suitable for neuroscientists, neurologists and functional surgeons studying DBS. It provides practical advice on processing strategies and theoretical background, highlighting and reviewing the current state-of-the-art in connectomic surgery. Written to provide a "hands-on" approach for neuroscience graduate students, as well as medical personnel from the fields of neurology and neurosurgery Includes preprocessing strategies (such as co-registration, normalization, lead localization, VTA estimation and fiber-tracking approaches) Presents references (key articles, books and protocols) for additional detailed study Provides data analysis boxes in each chapter to help with data interpretation

The study and modulation of cortical connections is a rapidly growing area in neuroscience. This unique book by prominent researchers in the field covers recent advances in this area. The first section of the book describes studies of cortical connections, modulation of cortical connectivity and changes in cortical connections with activities such as motor learning and grasping in primates. The second section covers the use of non-invasive brain stimulation to study and modulate cortical connectivity in humans. The last section describes changes in brain connectivity in neurological and psychiatric diseases, and potential new treatments that manipulate brain connectivity. This book provides an up-to-date view of the study of cortical connectivity, and covers its role in both fundamental neuroscience and potential clinical applications.

Connectomics: Applications to Neuroimaging is unique in presenting the frontier of neuro-applications using brain connectomics techniques. The book describes state-of-the-art research that applies brain connectivity analysis techniques to a broad range of neurological and psychiatric disorders (Alzheimer’s, epilepsy, stroke, autism, Parkinson’s, drug or alcohol addiction, depression, bipolar, and schizophrenia), brain fingerprint applications, speech-language assessments, and cognitive assessment. With this book the reader will learn: Basic mathematical principles underlying connectomics How connectomics is applied to a wide range of neuro-applications What is the future direction of connectomics techniques. This book is an ideal reference for researchers and graduate students in computer science, data science, computational neuroscience, computational physics, or mathematics who need to understand how computational models derived from brain connectivity data are being used in clinical applications, as well as neuroscientists and medical researchers wanting an overview of the technical methods. Features: Combines connectomics methods with relevant and interesting neuro-applications Covers most of the hot topics in neuroscience and clinical areas Appeals to researchers in a wide range of disciplines: computer science, engineering, data science, mathematics, computational physics, computational neuroscience, as well as neuroscience, and medical researchers interested in the technical methods of connectomics Combines connectomics methods with relevant and interesting neuro-applications Presents information that will appeal to researchers in a wide range of disciplines, including computer science, engineering, data science, mathematics, computational physics, computational neuroscience, and more Includes a mathematics primer that formulates connectomics from an applied point-of-view, thus avoiding difficult to understand theoretical perspective Lists publicly available neuro-imaging datasets that can be used to construct structural and functional connectomes

Interest in brain connectivity inference has become ubiquitous and is now increasingly adopted in experimental investigations of clinical, behavioral, and experimental neurosciences. Methods in Brain Connectivity Inference through Multivariate Time Series Analysis gathers the contributions of leading international authors who discuss different time

This book focuses on our current understanding of brain dynamics in various brain disorders (e.g. epilepsy, Alzheimer’s and Parkinson’s disease) and how the multi-scale, multi-level tools of computational neuroscience can enhance this understanding. In recent years, there have been significant advances in the study of the dynamics of the disordered brain at both the microscopic and the macroscopic levels. This understanding can be furthered by the application of multi-scale computational models as integrative principles that may link single neuron dynamics and the dynamics of local and distant brain regions observed using human EEG, ERPs, MEG, LFPs and fMRI. Focusing on the computational models that are used to study movement, memory and cognitive disorders as well as epilepsy and consciousness related diseases, the book brings together physiologists and anatomists investigating cortical circuits; cognitive neuroscientists studying brain dynamics and behavior by means of EEG and functional magnetic resonance imaging (fMRI); and computational neuroscientists using neural modeling techniques to explore local and large-scale disordered brain dynamics. Covering topics that have a significant impact on the field of medicine, neuroscience and computer science, the book appeals to a diverse group of investigators.