This book shows how information systems (IS) scholars can effectively apply neuroscience expertise in ways that do not require neuroscience tools. However, the approach described here is intended to complement neuroscience tools, not to supplant them. Written by leading scholars in the field, it presents a review of the empirical literature on NeuroIS and provides a conceptual description of basic brain function from a cognitive neuroscience perspective. Drawing upon the cognitive neuroscience knowledge developed in non-IS contexts, the book enables IS scholars to reinterpret existing behavioral findings, develop new hypotheses and eventually test the hypotheses with non-neuroscience tools. At its core, the book conveys how neuroscience knowledge makes a deeper understanding of IS phenomena possible by connecting the behavioral and neural levels of analysis.

This book presents the proceedings of the virtual conference NeuroIS Retreat 2020, June 2–4, hosted in Austria, reporting on topics at the intersection of information systems (IS) research, neurophysiology and the brain sciences. Readers will discover the latest findings from top scholars in the field of NeuroIS, which offer detailed insights on the neurobiology underlying IS behavior, essential methods and tools and their applications for IS, as well as the application of neuroscience and neurophysiological theories to advance IS theory.

This book presents the proceedings of the Gmunden Retreat on NeuroIS 2016, reporting on topics at the intersection of Information Systems (IS) research, neurophysiology and the brain sciences. Readers will discover the latest findings from top scholars in the field of NeuroIS, which offer detailed insights on the neurobiology underlying IS behavior, essential methods and tools and their applications for IS, as well as the application of neuroscience and neurophysiological theories to advance IS theory.

This book presents the proceedings of the NeuroIS Retreat 2021, June 1-3, virtual conference, reporting on topics at the intersection of information systems (IS) research, neurophysiology and the brain sciences. Readers will discover the latest findings from top scholars in the field of NeuroIS, which offer detailed insights on the neurobiology underlying IS behavior, essential methods and tools and their applications for IS, as well as the application of neuroscience and neurophysiological theories to advance IS theory.

This edition of Advances in Neurobiology brings together experts in the emerging field of Systems Neuroscience to present an overview of this area of research. Topics covered include: how different neural circuits analyze sensory information, form perceptions of the external world, make decisions, and execute movements; how nerve cells behave when connected together to form neural networks; the relationship between molecular and cellular approaches to understanding brain structure and function; the study of high-level mental functions; and studying brain pathologies and diseases with Systems Neuroscience. A hierarchy of biological complexity arises from the genome, transcriptome, proteome, organelles, cells, synapses, circuits, brain regions, the whole brain, and behaviour. The best way to study the brain, the most complex organ in the body composed of 100 billion cells with trillions of interconnections, is with a Systems Biology approach. Systems biology is an inter-disciplinary field that focuses on complex interactions within biological systems to reveal 'emergent properties' - properties of cells and groups of cells functioning as a system whose actual and theoretical description is only possible using Systems Biology techniques.

Explains the relationship of electrophysiology, nonlinear dynamics, and the computational properties of neurons, with each concept presented in terms of both neuroscience and mathematics and illustrated using geometrical intuition. In order to model neuronal behavior or to interpret the results of modeling studies, neuroscientists must call upon methods of nonlinear dynamics. This book offers an introduction to nonlinear dynamical systems theory for researchers and graduate students in neuroscience. It also provides an overview of neuroscience for mathematicians who want to learn the basic facts of electrophysiology. Dynamical Systems in Neuroscience presents a systematic study of the relationship of electrophysiology, nonlinear dynamics, and computational properties of neurons. It emphasizes that information processing in the brain depends not only on the electrophysiological properties of neurons but also on their dynamical properties. The book introduces dynamical systems, starting with one- and two-dimensional Hodgkin-Huxley-type models and continuing to a description of bursting systems. Each chapter proceeds from the simple to the complex, and provides sample problems at the end. The book explains all necessary mathematical concepts using geometrical intuition; it includes many figures and few equations, making it especially suitable for non-mathematicians. Each concept is presented in terms of both neuroscience and mathematics, providing a link between the two disciplines. Nonlinear dynamical systems theory is at the core of computational neuroscience research, but it is not a standard part of the graduate neuroscience curriculum—or taught by math or physics department in a way that is suitable for students of biology. This book offers neuroscience students and researchers a comprehensive account of concepts and methods increasingly used in computational neuroscience. An additional chapter on synchronization, with more advanced material, can be found at the author's website, www.izhikevich.com.

Significant advances in brain research have been made, but investigators who face the resulting explosion of data need new methods to integrate the pieces of the "brain puzzle." Based on the expertise of more than 100 neuroscientists and computer specialists, this new volume examines how computer technology can meet that need. Featuring outstanding color photography, the book presents an overview of the complexity of brain research, which covers the spectrum from human behavior to genetic mechanisms. Advances in vision, substance abuse, pain, and schizophrenia are highlighted. The committee explores the potential benefits of computer graphics, database systems, and communications networks in neuroscience and reviews the available technology. Recommendations center on a proposed Brain Mapping Initiative, with an agenda for implementation and a look at issues such as privacy and accessibility.

Modern neuroscience research is inherently multidisciplinary, with a wide variety of cutting edge new techniques to explore multiple levels of investigation. This Third Edition of Guide to Research Techniques in Neuroscience provides a comprehensive overview of classical and cutting edge methods including their utility, limitations, and how data are presented in the literature. This book can be used as an introduction to neuroscience techniques for anyone new to the field or as a reference for any neuroscientist while reading papers or attending talks. - Nearly 200 updated full-color illustrations to clearly convey the theory and practice of neuroscience methods - Expands on techniques from previous editions and covers many new techniques including in vivo calcium imaging, fiber photometry, RNA-Seq, brain spheroids, CRISPR-Cas9 genome editing, and more - Clear, straightforward explanations of each technique for anyone new to the field - A broad scope of methods, from noninvasive brain imaging in human subjects, to electrophysiology in animal models, to recombinant DNA technology in test tubes, to transfection of neurons in cell culture - Detailed recommendations on where to find protocols and other resources for specific techniques - "Walk-through" boxes that guide readers through experiments step-by-step

"This book is a comprehensive reference source for the latest scholarly material on trends, techniques, and various uses of neuroscience and examines the benefits and challenges of these developments. Highlighting a range of pertinent topics such as cognitive processes, neuroeconomics, and neural signal processing"--Provided by publisher.

In security science, efficient operation depends typically on the interaction between technology, human and machine detection and human and machine decision making. A perfect example of this interplay is ‘gatekeeping’, which is aimed to prevent the passage of people and objects that represent known threats from one end to the other end of an access point. Gatekeeping is most often achieved via visual inspections, mass screening, random sample probing and/or more targeted controls on attempted passages at points of entry. Points of entry may be physical (e.g. national borders) or virtual (e.g. connection log-ons). Who and what are defined as security threats and the resources available to gatekeepers determine the type of checks and technologies that are put in place to ensure appropriate access control. More often than not, the net performance of technology-aided screening and authentication systems ultimately depends on the characteristics of human operators. Assessing cognitive, affective, behavioural, perceptual and brain processes that may affect gatekeepers while undertaking this task is fundamental. On the other hand, assessing the same processes in those individuals who try to breach access to secure systems (e.g. hackers), and try to cheat controls (e.g. smugglers) is equally fundamental and challenging. From a security standpoint it is vital to be able to anticipate, focus on and correctly interpret the signals connected with such attempts to breach access and/or elude controls, in order to be proactive and to enact appropriate responses. Knowing cognitive, behavioral, social and neural constraints that may affect the security enterprise will undoubtedly result in a more effective deployment of existing human and technological resources. Studying how inter-observer variability, human factors and biology may affect the security agenda, and the usability of existing security technologies, is of great economic and policy interest. In addition, brain sciences may suggest the possibility of novel methods of surveillance and intelligence gathering. This is just one example of a typical security issue that may be fruitfully tackled from a neuroscientific and interdisciplinary perspective. The objective of our Research Topic was to document across relevant disciplines some of the most recent developments, ideas, methods and empirical findings that have the potential to expand our knowledge of the human factors involved in the security process. To this end we welcomed empirical contributions using different methodologies such as those applied in human cognitive neuroscience, biometrics and ethology. We also accepted original theoretical contributions, in the form of review articles, perspectives or opinion papers on this topic. The submissions brought together researchers from different backgrounds to discuss topics which have scientific, applicative and social relevance.