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

This Research Topic aims to highlight the latest experimental techniques and methods used to aid in the classification; diagnosis; visualization; prognosis and treatment of neurological and neuropsychiatric disorders using brain imaging methods. Review articles or opinions on methodologies or applications including the advantages and limitations of each are welcome. This Topic includes technologies and up-to-date methods which help advance the science. The contributions to this collection will undergo peer-review. Novelty and the utility of a method or protocol must be evident. We welcome contributions covering all aspects of novel brain imaging methods that aid clinicians in handling neurological and neuropsychiatric disorders as described above. Submissions will be handled by the team of Topic Editors. Frontiers in Neuroscience supports the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management and stewardship (Wilkinson et al., Sci. Data 3:160018, 2016). This Research Topic welcomes: • Methods: Describing new methods that are significantly improved or adapted for specific purposes. These manuscripts may include primary (original) data. • Protocols: Detailed descriptions, including pitfalls and troubleshooting, to benefit those who may evaluate or employ the techniques. The protocols must be proven to work. • Perspective or General Commentaries on brain imaging methods and protocols relevant for aiding in the handling of neurological and neuropsychiatric disorders. • Reviews and mini-reviews of topical methods and protocols highlighting the important future directions of the field.

This text provides students and researchers with a foundation for examining how brain function gives rise to mental activities such as perception, memory and language. It is grouped into sections that cover attention, vision, auditory and somatosensory systems, memory and higher cortical.

A comprehensive survey of best practice in using diagnostic imaging in acute neurologic conditions. The symptom-based approach guides the choice of the available imaging tools for efficient, accurate, and cost-effective diagnosis. Effective examination algorithms integrate neurological and imaging concepts with the practical demands and constraints of emergency care.

This textbook provides a comprehensive overview of the currently used concepts, approaches and technologies in the discovery and development of new treatments for the full spectrum of disorders of the central nervous system. It guides the reader through all essential steps, from finding an innovative idea, to the registration of a new drug. Divided into four sections, the book starts by presenting a broad perspective on current approaches in central nervous system (CNS) drug discovery. The second section addresses the generation of ideas for the identification of targets and novel treatment strategies; covers core functions in early discovery, and provides an example of a novel treatment paradigm: brain stimulation. The third section highlights strategies and technologies in translational CNS drug discovery. In an effort to bridge the gap between discovery and clinical development, it also covers brain imaging, EEG and cognitive testing approaches. The fourth section extensively discusses the clinical phase of drug development, covering the basics of early clinical testing for psychopharmacological drugs. The book’s final chapter addresses the registration for newly developed drugs. Written by experts from academia and industry, the book covers important basics and best practices, as well as recent developments in drug discovery. Offering in-depth insights into the world of drug development, it represents essential reading for early researchers who want to prepare for a career in drug discovery in academia or industry.

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.

New from Oxford Textbooks in Psychiatry, the Oxford Textbook of Neuropsychiatry bridges the gap between general psychiatric textbooks and reference texts in neuropsychiatry. Divided into four sections, it covers core knowledge and skills for practice in all psychiatric disciplines, with key information for training in neuropsychiatry.

Functional Neurologic Disorders, the latest volume in the Handbook of Clinical Neurology series, summarizes state-of-the-art research findings and clinical practice on this class of disorders at the interface between neurology and psychiatry. This 51-chapter volume offers an historical introduction, chapters on epidemiology and pathophysiolology, a large section on the clinical features of different type of functional neurologic symptoms and disorders (including functional movement disorders, non-epileptic seizures, dizziness, vision, hearing, speech and cognitive symptoms), and then concluding with approaches to therapy. This group of internationally acclaimed experts in neurology, psychiatry, and neuroscience represent a broad spectrum of areas of expertise, chosen for their ability to write clearly and concisely with an eye toward a clinical audience. This HCN volume sets a new landmark standard for a comprehensive, multi-authored work dealing with functional neurologic disorders (also described as psychogenic, dissociative or conversion disorders). - Offers a comprehensive interdisciplinary approach for the care of patients with functional disorders seen in neurologic practice, leading to more efficient prevention, management, and treatment - Provides a synthesis of research efforts incorporating clinical, brain imaging and neurophysiological studies - Fills an existing gap between traditional neurology and traditional psychiatry - Contents include coverage of history, epidemiology, clinical presentations, and therapy - Edited work with chapters authored by leaders in the field, the broadest, most expert coverage available

Big Data in Psychiatry and Neurology provides an up-to-date overview of achievements in the field of big data in Psychiatry and Medicine, including applications of big data methods to aging disorders (e.g., Alzheimer's disease and Parkinson's disease), mood disorders (e.g., major depressive disorder), and drug addiction. This book will help researchers, students and clinicians implement new methods for collecting big datasets from various patient populations. Further, it will demonstrate how to use several algorithms and machine learning methods to analyze big datasets, thus providing individualized treatment for psychiatric and neurological patients. As big data analytics is gaining traction in psychiatric research, it is an essential component in providing predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level. - Discusses longitudinal big data and risk factors surrounding the development of psychiatric disorders - Analyzes methods in using big data to treat psychiatric and neurological disorders - Describes the role machine learning can play in the analysis of big data - Demonstrates the various methods of gathering big data in medicine - Reviews how to apply big data to genetics