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Construction of comprehensive and detailed brain regions neuroanatomical connections matrices (macro-connectomes) is necessary to understand how the nervous system is organized and to elucidate how its different parts interact. Macro-connectomes also are the structural foundation of any finer granularity approaches at the neuron classes and types (meso-connectomes) or individual neuron (micro-connectomes) levels. The advent of novel neuroanatomical methods, as well as combinations of classic techniques, form the basis of several large scale projects with the ultimate goal of producing publicly available connectomes at different levels. A parallel approach, that of systematic and comprehensive collation of connectivity data from the published literature and from publicly accessible neuroinformatics platforms, has produced macro-connectomes of different parts of the central nervous system (CNS) in several mammalian species. The emergence of these public platforms that allow for the manipulation of rich connectivity data sets and enable the construction of CNS macro-connectomes in different species may have significant and long lasting implications. Moreover, when these efforts are leveraged by novel statistical methods, they may influence our way of thinking about the brain. Hence, the present brain region-centric paradigm may be challenged by a network-centric one. Ultimately, these projects will provide the information and knowledge for understanding how different neuronal parts communicate and function, developing novel approaches to diseases and disorders, and facilitating translational efforts in neurosciences. With this Research Topic we bring together the current state of macro-connectome related projects including the large scale production of thousands of publicly available neuronatomical experiments, databases with tens of thousands of connectivity records collated from the published literature, and the newest methods for displaying and analyzing this information. This topic also includes a wide range of challenges and how they are addressed - from platforms designed to integrate connectivity data across different sources, species and CNS levels of organization, to languages specifically designed to use these data in models at different scales of resolution, to efforts of 3D reconstruction and data integration, and to approaches for extraction and representation of this knowledge. Finally, we address the present state of different efforts of meso-connectomes construction, and of computational modeling in the context of the information provided by macro-connectomes.
This book has brought together leading investigators who work in the new arena of brain connectomics. This includes ‘macro-connectome’ efforts to comprehensively chart long-distance pathways and functional networks; ‘micro-connectome’ efforts to identify every neuron, axon, dendrite, synapse, and glial process within restricted brain regions; and ‘meso-connectome’ efforts to systematically map both local and long-distance connections using anatomical tracers. This book highlights cutting-edge methods that can accelerate progress in elucidating static ‘hard-wired’ circuits of the brain as well as dynamic interactions that are vital for brain function. The power of connectomic approaches in characterizing abnormal circuits in the many brain disorders that afflict humankind is considered. Experts in computational neuroscience and network theory provide perspectives needed for synthesizing across different scales in space and time. Altogether, this book provides an integrated view of the challenges and opportunities in deciphering brain circuits in health and disease.
Connectome Analysis: Characterization, Methods, and Analysis is a comprehensive companion for the analysis of brain networks, or connectomes. The book provides sources of constituent structural and functional MRI signals, network construction and practices for analysis, cutting-edge methods that address the latest challenges in neuroscience, and the fundamentals of network theory in the context of giving practical methods for building connectomes for analysis. Emphasis is placed on quality control of the individual analysis steps. Subsequent chapters discuss networks in neuroscience in clinical and general populations, including how findings are related to underlying neurophysiology and neuropsychology. This book is aimed at students and early-career researchers in brain connectomics and neuroimaging who have a background in computer science, mathematics and physics, as well as more broadly to neuroscientists and psychologists who want to start incorporating connectomics into their research. - Provides practical recommendations on how to construct, assess and analyze brain networks - Gives an understanding of all the technical methods for connectome analysis - Presents the basic network theoretical principles typically used in neuroscience - Covers the latest tools and data repositories that are freely available for the reader to carry out connectomic analyses
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
The brain's ability to process information crucially relies on connectivity. Understanding how the brain processes complex information and how such abilities are disrupted in individuals with neuropsychological disorders will require an improved understanding of brain connectivity. Autism is an intriguingly complex neurodevelopmental disorder with multidimensional symptoms and cognitive characteristics. A biological origin for autism spectrum disorders (ASD) had been proposed even in the earliest published accounts (Kanner, 1943; Asperger, 1944). Despite decades of research, a focal neurobiological marker for autism has been elusive. Nevertheless, disruptions in interregional and functional and anatomical connectivity have been a hallmark of neural functioning in ASD. Theoretical accounts of connectivity perceive ASD as a cognitive and neurobiological disorder associated with altered functioning of integrative circuitry. Neuroimaging studies have reported disruptions in functional connectivity (synchronization of activated brain areas) during cognitive tasks and during task-free resting states. While these insights are valuable, they do not address the time-lagged causality and directionality of such correlations. Despite the general promise of the connectivity account of ASD, inconsistencies and methodological differences among studies call for more thorough investigations. A comprehensive neurological account of ASD should incorporate functional, effective, and anatomical connectivity measures and test the diagnostic utility of such measures. In addition, questions pertaining to how cognitive and behavioral intervention can target connection abnormalities in ASD should be addressed. This research topic of the Frontiers in Human Neuroscience addresses “Brain Connectivity in Autism” primarily from cognitive neuroscience and neuroimaging perspectives.
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
This was the first conference organized by the school of Computer Science Engineering in VIT-AP University campus with the cumulative efforts of all the faculty members. The proceedings discusses recent advancements and novel ideas in areas of interest. It covers topics such as advances in computer based systems, processes and applications
A pioneer in the field outlines new empirical and computational approaches to mapping the neural connections of the human brain. Crucial to understanding how the brain works is connectivity, and the centerpiece of brain connectivity is the connectome, a comprehensive description of how neurons and brain regions are connected. In this book, Olaf Sporns surveys current efforts to chart these connections—to map the human connectome. He argues that the nascent field of connectomics has already begun to influence the way many neuroscientists collect, analyze, and think about their data. Moreover, the idea of mapping the connections of the human brain in their entirety has captured the imaginations of researchers across several disciplines including human cognition, brain and mental disorders, and complex systems and networks. Discovering the Human Connectome offers the first comprehensive overview of current empirical and computational approaches in this rapidly developing field.
This volume deals with some of the association areas of the cerebral cortex and with the auditory cortex. In the first chapter, by Deepak Pandya and Edward Yeterian, the general architectural features and connections of cortical associ ation areas are considered; as these authors point out, in primates the association areas take up a considerable portion of the total cortical surface. Indeed, it is the development of the association areas that accounts for the greatest differ ences between the brains of primate and non primate species, and these areas have long been viewed as crucial in the formation of higher cognitive and be havioral functions. In the following chapter, Irving Diamond, David Fitzpatrick, and James Sprague consider the question of whether the functions of the as sociation areas depend on projections from the sensory areas of the cortex. They use the visual cortex to examine this question and show that there is a great deal of difference between species in the amount of dependence, the differences being paralleled by variations in the manner in which the geniculate and pulvinar nuclei of the thalamus project to the striate and extra striate cortical areas. One of the more interesting and perhaps least understood of the association areas is the cingulate cortex, discussed by Brent Vogt. Cingulate cortex has been linked with emotion and with affective responses to pain, and in his chapter Vogt gives an account of its cytoarchitecture, connections, and functions.
Spontaneous 'resting-state' fluctuations in neuronal activity offer insights into the inherent organisation of the human brain, and may provide markers for diagnosis and treatment of mental disorders. Resting state functional magnetic resonance imaging (fMRI) can be used to investigate intrinsic functional connectivity networks, which are identified based on similarities in the signal measured from different regions. From data acquisition to results interpretation, An Introduction to Resting State fMRI Functional Connectivity discusses a wide range of approaches without expecting previous knowledge of the reader, making it truly accessible to readers from a broad range of backgrounds. Supplemented with online examples to enable the reader to obtain hands-on experience working with data, the text also provides details to enhance learning for those already experienced in the field. The Oxford Neuroimaging Primers are written for new researchers or advanced undergraduates in neuroimaging to provide a thorough understanding of the ways in which neuroimaging data can be analysed and interpreted. Aimed at students without a background in mathematics or physics, this book is also important reading for those familiar with task fMRI but new to the field of resting state fMRI.