Brain Network Dysfunction in Neuropsychiatric Illness


Book Description

Brain network function and dysfunction is the dominant model for understanding how the brain gives rise to normal and abnormal behavior. Moreover, neuropsychiatric illnesses continue to resist attempts to reveal an understanding of their bases. Thus, this timely volume provides a synthesis of the uses of multiple analytic methods as they are applied to neuroimaging data, to seek understanding of the neurobiological bases of psychiatric illnesses, understanding that can subsequently aid in their management and treatment. A principle focus is on the analyses and application of methods to functional magnetic resonance imaging (fMRI) data. fMRI remains the most widely used neuroimaging technique for estimating brain network function, and several of the methods covered can estimate brain network dysfunction in resting and task-active states. Additional chapters provide details on how these methods are (and can be) applied in the understanding of several neuropsychiatric disorders, including schizophrenia, mood disorders, autism, borderline personality disorder, and attention deficit hyperactivity disorder (ADHD). A final complement of chapters provides a collective overview of how this framework continues to provoke theoretical advances in our conception of the brain in psychiatry. This unique volume is designed to be a comprehensive resource for imaging researchers interested in psychiatry, and for psychiatrists interested in advanced imaging applications.




Brain Network Dysfunction in Neuropsychiatric Illness


Book Description

Brain network function and dysfunction is the dominant model for understanding how the brain gives rise to normal and abnormal behavior. Moreover, neuropsychiatric illnesses continue to resist attempts to reveal an understanding of their bases. Thus, this timely volume provides a synthesis of the uses of multiple analytic methods as they are applied to neuroimaging data, to seek understanding of the neurobiological bases of psychiatric illnesses, understanding that can subsequently aid in their management and treatment. A principle focus is on the analyses and application of methods to functional magnetic resonance imaging (fMRI) data. fMRI remains the most widely used neuroimaging technique for estimating brain network function, and several of the methods covered can estimate brain network dysfunction in resting and task-active states. Additional chapters provide details on how these methods are (and can be) applied in the understanding of several neuropsychiatric disorders, including schizophrenia, mood disorders, autism, borderline personality disorder, and attention deficit hyperactivity disorder (ADHD). A final complement of chapters provides a collective overview of how this framework continues to provoke theoretical advances in our conception of the brain in psychiatry. This unique volume is designed to be a comprehensive resource for imaging researchers interested in psychiatry, and for psychiatrists interested in advanced imaging applications.




Understanding Neuropsychiatric Disorders


Book Description

An informative and comprehensive review from the leading researchers in the field, this book provides a complete one-stop guide to neuroimaging techniques and their application to a wide range of neuropsychiatric disorders. For each disorder or group of disorders, separate chapters review the most up-to-date findings from structural imaging, functional imaging and/or molecular imaging. Each section ends with an overview from a internationally-renowned luminary in the field, addressing the question of 'What do we know and where are we going?' Richly illustrated throughout, each chapter includes a 'summary box', providing readers with explicit take-home messages. This is an essential resource for clinicians, researchers and trainees who want to learn how neuroimaging tools lead to new discoveries about brain and behaviour associations in neuropsychiatric disorders.




Imaging of the Human Brain in Health and Disease


Book Description

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




Cognitive deficits in schizophrenia and other neuropsychiatric disorders: Convergence of preclinical and clinical evidence


Book Description

Neuropsychiatric diseases, such as schizophrenia, Alzheimer's disease, and etc., represent a serious medical and socioeconomic problems. These diseases are often accompanied by impairments of cognitive function, e.g., abstract thinking, decision-making, attention, and several types of memory. Such deficits significantly disrupt quality of life and daily functioning of patients. Cognitive deficits in neuropsychiatric diseases are associated with alterations of brain morphology and function, and are often resistant to therapeutic interventions. In schizophrenia and related disorders, cognitive deficits are also defined as endophenotypes, i.e. measurable phenotypes linking these disaeses with discrete heritable and reproducible traits. This points to the importance of elucidating these endophenotypes in translational studies. Animal models may not mimic the full spectrum of clinical symptoms, but may act as analogies of particular behaviors or other pathological outcomes. They are useful to search for the etiology of particular psychiatric illnesses and novel therapeutics. Moreover, several behavioral tests to measure cognitive performance in rodents and other species have been implemented. The primary focus of the present topic is to provide up-to-date information on cognitive deficits of neuropsychiatric disorders, such as schizophrenia. This Research Topic also delineates future directions for translational studies aimed at developing novel treatments/interventions of cognitive disturbances.




Precision Medicine for Investigators, Practitioners and Providers


Book Description

Precision Medicine for Investigators, Practitioners and Providers addresses the needs of investigators by covering the topic as an umbrella concept, from new drug trials to wearable diagnostic devices, and from pediatrics to psychiatry in a manner that is up-to-date and authoritative. Sections include broad coverage of concerning disease groups and ancillary information about techniques, resources and consequences. Moreover, each chapter follows a structured blueprint, so that multiple, essential items are not overlooked. Instead of simply concentrating on a limited number of extensive and pedantic coverages, scholarly diagrams are also included. - Provides a three-pronged approach to precision medicine that is focused on investigators, practitioners and healthcare providers - Covers disease groups and ancillary information about techniques, resources and consequences - Follows a structured blueprint, ensuring essential chapters items are not overlooked




Neuropsychiatry and Behavioral Neuroscience


Book Description

This is the long-awaited successor to Jeffrey Cummings' classic work, Clinical Neuropsychiatry, published in 1985. That book represented an integration of behavioral neurology and biological psychiatry into a single volume devoted to explicating brain-behavior relationships. It was clinically oriented and intended for practitioners caring for patients with neuropsychiatric disorders. The new title reflects the authors' effort to link the recent explosion of new information from neurochemistry, neuroanatomy, genetics, neuropharmacology, neuropathology, and neuroimaging to the clinical descriptions. Yet the clinical emphasis of its predecessor has been maintained. Each chapter has a consistent approach and the book as whole provides a practical, easy-to-use synthesis of clinical advice and basic science. The volume is enhanced by 4-color images throughout. It is intended for students, residents, fellows, and practitioners of neurology, psychiatry, neuropsychology, and cognitive neuroscience. It will also be of interest to individuals in neuroimaging.




Pattern Analysis of the Human Connectome


Book Description

This book presents recent advances in pattern analysis of the human connectome. The human connectome, measured by magnetic resonance imaging at the macroscale, provides a comprehensive description of how brain regions are connected. Based on machine learning methods, multiviarate pattern analysis can directly decode psychological or cognitive states from brain connectivity patterns. Although there are a number of works with chapters on conventional human connectome encoding (brain-mapping), there are few resources on human connectome decoding (brain-reading). Focusing mainly on advances made over the past decade in the field of manifold learning, sparse coding, multi-task learning, and deep learning of the human connectome and applications, this book helps students and researchers gain an overall picture of pattern analysis of the human connectome. It also offers valuable insights for clinicians involved in the clinical diagnosis and treatment evaluation of neuropsychiatric disorders.




Fundamentals of Neural Network Modeling


Book Description

Provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. Over the past few years, computer modeling has become more prevalent in the clinical sciences as an alternative to traditional symbol-processing models. This book provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. It is intended to make the neural network approach accessible to practicing neuropsychologists, psychologists, neurologists, and psychiatrists. It will also be a useful resource for computer scientists, mathematicians, and interdisciplinary cognitive neuroscientists. The editors (in their introduction) and contributors explain the basic concepts behind modeling and avoid the use of high-level mathematics. The book is divided into four parts. Part I provides an extensive but basic overview of neural network modeling, including its history, present, and future trends. It also includes chapters on attention, memory, and primate studies. Part II discusses neural network models of behavioral states such as alcohol dependence, learned helplessness, depression, and waking and sleeping. Part III presents neural network models of neuropsychological tests such as the Wisconsin Card Sorting Task, the Tower of Hanoi, and the Stroop Test. Finally, part IV describes the application of neural network models to dementia: models of acetycholine and memory, verbal fluency, Parkinsons disease, and Alzheimer's disease. Contributors J. Wesson Ashford, Rajendra D. Badgaiyan, Jean P. Banquet, Yves Burnod, Nelson Butters, John Cardoso, Agnes S. Chan, Jean-Pierre Changeux, Kerry L. Coburn, Jonathan D. Cohen, Laurent Cohen, Jose L. Contreras-Vidal, Antonio R. Damasio, Hanna Damasio, Stanislas Dehaene, Martha J. Farah, Joaquin M. Fuster, Philippe Gaussier, Angelika Gissler, Dylan G. Harwood, Michael E. Hasselmo, J, Allan Hobson, Sam Leven, Daniel S. Levine, Debra L. Long, Roderick K. Mahurin, Raymond L. Ownby, Randolph W. Parks, Michael I. Posner, David P. Salmon, David Servan-Schreiber, Chantal E. Stern, Jeffrey P. Sutton, Lynette J. Tippett, Daniel Tranel, Bradley Wyble