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Our contemporary understanding of brain function is deeply rooted in the ideas of the nonlinear dynamics of distributed networks. Cognition and motor coordination seem to arise from the interactions of local neuronal networks, which themselves are connected in large scales across the entire brain. The spatial architectures between various scales inevitably influence the dynamics of the brain and thereby its function. But how can we integrate brain connectivity amongst these structural and functional domains? Our Handbook provides an account of the current knowledge on the measurement, analysis and theory of the anatomical and functional connectivity of the brain. All contributors are leading...
This volume includes papers presented at the Third Annual Computation and Neural Systems meeting (CNS*94) held in Monterey California, July 21 - July 26, 1994. This collection includes 71 of the more than 100 papers presented at this year's meeting. Acceptance for meeting presentation was based on the peer review of preliminary papers by at least two referees. The papers in this volume were submitted in final form after the meeting. As represented by this volume, CNS meetings continue to expand in quality, size and breadth of focus as increasing numbers of neuroscientists are taking a computational approach to understanding nervous system function. The CNS meetings are intended to showcase t...
Biological Network Analysis: Trends, Approaches, Graph Theory, and Algorithms considers three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN), and Human Brain Connectomes. The book's authors discuss various graph theoretic and data analytics approaches used to analyze these networks with respect to available tools, technologies, standards, algorithms and databases for generating, representing and analyzing graphical data. As a wide variety of algorithms have been developed to analyze and compare networks, this book is a timely resource.
An integrative overview of network approaches to neuroscience explores the origins of brain complexity and the link between brain structure and function. Over the last decade, the study of complex networks has expanded across diverse scientific fields. Increasingly, science is concerned with the structure, behavior, and evolution of complex systems ranging from cells to ecosystems. In Networks of the Brain, Olaf Sporns describes how the integrative nature of brain function can be illuminated from a complex network perspective. Highlighting the many emerging points of contact between neuroscience and network science, the book serves to introduce network theory to neuroscientists and neuroscience to those working on theoretical network models. Sporns emphasizes how networks connect levels of organization in the brain and how they link structure to function, offering an informal and nonmathematical treatment of the subject. Networks of the Brain provides a synthesis of the sciences of complex networks and the brain that will be an essential foundation for future research.
In Computational Neuroanatomy: Principles and Methods, the path-breaking investigators who founded the field review the principles and key techniques available to begin the creation of anatomically accurate and complete models of the brain. Combining the vast, data-rich field of anatomy with the computational power of novel hardware, software, and computer graphics, these pioneering investigators lead the reader from the subcellular details of dendritic branching and firing to system-level assemblies and models.
Brain imaging has revolutionised the field of Psychology, yet it can be a minefield whichever discipline you approach it from. This book shows how brain imaging can advance a true neuroscience of human cognition. It is accessible for those starting out in imaging, whilst also informative for those who have already acquired some expertise
We live in an age of surveillance. In this book, the moral importance of this is explained through an examination of virtual identities.
Artificial Psychology (AP) is a highly multidisciplinary field of study in psychology. AP tries to solve problems which occur when psychologists do research and need a robust analysis method. Conventional statistical approaches have deep rooted limitations. These approaches are excellent on paper but often fail to model the real world. Mind researchers have been trying to overcome this by simplifying the models being studied. This stance has not received much practical attention recently. Promoting and improving artificial intelligence helps mind researchers to find a holistic model of mental models. This development achieves this goal by using multiple perspectives and multiple data sets to...
This book constitutes the refereed proceedings of the 15th International Symposium on Algorithms and Computation, ISAAC 2004, held in Hong Kong, China in December 2004. The 76 revised full papers presented were carefully reviewed and selected from 226 submissions. Among the topics addressed are computational geometry, graph computations, computational combinatorics, combinatorial optimization, computational complexity, scheduling, distributed algorithms, parallel algorithms, data structures, network optimization, randomized algorithms, and computational mathematics more generally.