Theory and Method in the Neurosciences surveys the nature and structure of theories in contemporary neuroscience, exploring many of its methodological techniques and problems. The essays in this volume from the Pittsburgh -Konstanz series explore basic questions about how to relate theories of neuroscience and cognition, the multilevel character of such theories, and their experimental bases. Philosophers and scientists (and some who are both) examine the topics of explanation and mechanisms, simulation and computation, imaging and animal models that raise questions about the forefront of research in cognitive neuroscience. Their work will stimulate new thinking in anyone interested in the mind or brain and in recent theories of their connections.

The fifth edition of a work that defines the field of cognitive neuroscience, with entirely new material that reflects recent advances in the field. Each edition of this classic reference has proved to be a benchmark in the developing field of cognitive neuroscience. The fifth edition of The Cognitive Neurosciences continues to chart new directions in the study of the biological underpinnings of complex cognition—the relationship between the structural and physiological mechanisms of the nervous system and the psychological reality of the mind. It offers entirely new material, reflecting recent advances in the field. Many of the developments in cognitive neuroscience have been shaped by the introduction of novel tools and methodologies, and a new section is devoted to methods that promise to guide the field into the future—from sophisticated models of causality in brain function to the application of network theory to massive data sets. Another new section treats neuroscience and society, considering some of the moral and political quandaries posed by current neuroscientific methods. Other sections describe, among other things, new research that draws on developmental imaging to study the changing structure and function of the brain over the lifespan; progress in establishing increasingly precise models of memory; research that confirms the study of emotion and social cognition as a core area in cognitive neuroscience; and new findings that cast doubt on the so-called neural correlates of consciousness.

Unique in its coverage of such an extensive range of methods, Neuroscience Methods: A Guide for Advanced Students provides easy-to-understand descriptions of the many different techniques that are currently being used to study the brain at the molecular and cellular levels. This valuable reference text will help rescue undergraduate and postgraduate students from continuing bewilderment at the methods sections of current neuroscience publications. Topics covered include in vivo and in vitro preparations, electrophysiological, histochemical, hybridization and genetic techniques, measurement of cellular ion concentrations, methods of drug application, production of antibodies, expression systems, and neural grafting.

As the ultimate information processing device, the brain naturally lends itself to being studied with information theory. The application of information theory to neuroscience has spurred the development of principled theories of brain function, and has led to advances in the study of consciousness, as well as to the development of analytical techniques to crack the neural code—that is, to unveil the language used by neurons to encode and process information. In particular, advances in experimental techniques enabling the precise recording and manipulation of neural activity on a large scale now enable for the first time the precise formulation and the quantitative testing of hypotheses about how the brain encodes and transmits the information used for specific functions across areas. This Special Issue presents twelve original contributions on novel approaches in neuroscience using information theory, and on the development of new information theoretic results inspired by problems in neuroscience.

Neuroscience Databases: A Practical Guide is the first book providing a comprehensive overview of these increasingly important databases. This volume makes the results of the Human Genome Project and other recent large-scale initiatives in the neurosciences available to a wider community. It extends the scope of bioinformatics from the molecular to the cellular, microcircuitry and systems levels, dealing for the first time with complex neuroscientific issues and leading the way to a new culture of data sharing and data mining necessary to successfully tackle neuroscience questions. Aimed at the novice user who wants to access the data, it provides clear and concise instructions on how to download the available data sets and how to use the software with a minimum of technical detail with most chapters written by the database creators themselves.

V. Methodology: E. J. Wagenmakers (Volume Editor) Topics covered include methods and models in categorization; cultural consensus theory; network models for clinical psychology; response time modeling; analyzing neural time series data; models and methods for reinforcement learning; convergent methods of memory research; theories for discriminating signal from noise; bayesian cognitive modeling; mathematical modeling in cognition and cognitive neuroscience; the stop-signal paradigm; hypothesis testing and statistical inference; model comparison in psychology; fmri; neural recordings; open science; neural networks and neurocomputational modeling; serial versus parallel processing; methods in psychophysics.

This book bridges the gap between data scientists and clinicians by introducing all relevant aspects of machine learning in an accessible way, and will certainly foster new and serendipitous applications of machine learning in the clinical neurosciences. Building from the ground up by communicating the foundational knowledge and intuitions first before progressing to more advanced and specific topics, the book is well-suited even for clinicians without prior machine learning experience. Authored by a wide array of experienced global machine learning groups, the book is aimed at clinicians who are interested in mastering the basics of machine learning and who wish to get started with their own machine learning research. The volume is structured in two major parts: The first uniquely introduces all major concepts in clinical machine learning from the ground up, and includes step-by-step instructions on how to correctly develop and validate clinical prediction models. It also includes methodological and conceptual foundations of other applications of machine learning in clinical neuroscience, such as applications of machine learning to neuroimaging, natural language processing, and time series analysis. The second part provides an overview of some state-of-the-art applications of these methodologies. The Machine Intelligence in Clinical Neuroscience (MICN) Laboratory at the Department of Neurosurgery of the University Hospital Zurich studies clinical applications of machine intelligence to improve patient care in clinical neuroscience. The group focuses on diagnostic, prognostic and predictive analytics that aid in decision-making by increasing objectivity and transparency to patients. Other major interests of our group members are in medical imaging, and intraoperative applications of machine vision.

The first comprehensive guide to research methods and technologies in psycholinguistics and the neurobiology of language Bringing together contributions from a distinguished group of researchers and practitioners, editors Annette M. B. de Groot and Peter Hagoort explore the methods and technologies used by researchers of language acquisition, language processing, and communication, including: traditional observational and behavioral methods; computational modelling; corpus linguistics; and virtual reality. The book also examines neurobiological methods, including functional and structural neuroimaging and molecular genetics. Ideal for students engaged in the field, Research Methods in Psycholinguistics and the Neurobiology of Language examines the relative strengths and weaknesses of various methods in relation to competing approaches. It describes the apparatus involved, the nature of the stimuli and data used, and the data collection and analysis techniques for each method. Featuring numerous example studies, along with many full-color illustrations, this indispensable text will help readers gain a clear picture of the practices and tools described. Brings together contributions from distinguished researchers across an array of related disciplines who explain the underlying assumptions and rationales of their research methods Describes the apparatus involved, the nature of the stimuli and data used, and the data collection and analysis techniques for each method Explores the relative strengths and weaknesses of various methods in relation to competing approaches Features numerous real-world examples, along with many full-color illustrations, to help readers gain a clear picture of the practices and tools described

Each day, novel neuroscientific findings show that researchers are focusing on developing advanced smart hardware designs and intelligent computational models to imitate the human brain’s computational abilities. The advancements in smart materials provide a significant role in inventing intelligent bioelectronic device designs with smart features such as accuracy, low power consumption, and more. These advanced and intelligent computing models through machine and smart deep learning algorithms help to understand the information processing capabilities of the human brain with optimum accuracy. Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering highlights advanced computational models and hardware designs in neurology and integration of mathematical physical, biological, chemical, and engineering models to mimic brain functions; discovers new technological diagnosis techniques; and achieves high accuracy in learning models to better understand the functioning of the human brain. Providing rich information on brain-computer interfacing, gamification in children, and vestibular rehabilitation, this text acts as an essential resource for experts in electrophysiological studies, neurologists, neuro-physiotherapists, neuro-radiologists, intelligent system developers, bio-software and hardware developers, neuro database collectors, electro-physiologists, professors associated with neurology, psychiatrists, engineers, scientists, and students from academia and industry involved in interdisciplinary approaches to neurology.