First published in 1992, AY's Neuroanatomy of C. elegans for Computation provides the neural circuitry database of the nematode Caenorhabditis elegans, both in printed form and in ASCII files on 5.25-inch diskettes (for use on IBM® and compatible personal computers, Macintosh® computers, and higher level machines). Tables of connections among neuron classes, synapses among individual neurons, gap junctions among neurons, worm cells and their embryonic origin, and synthetically derived neuromuscular connections are presented together with the references from which the data were compiled and edited. Sample data files and source codes of FORTRAN and BASIC programs are provided to illustrate the use of mathematical tools for any researcher or student interested in examining a natural neural network and discovering what makes it tick.
AY's Neuroanatomy of C. elegans for Computation provides the neural circuitry database of the nematode Caenorhabditis elegans, both in printed form and in ASCII files on 5.25-inch diskettes (for use on IBM® and compatible personal computers, Macintosh® computers, and higher level machines). Tables of connections among neuron classes, synapses among individual neurons, gap junctions among neurons, worm cells and their embryonic origin, and synthetically derived neuromuscular connections are presented together with the references from which the data were compiled and edited. Sample data files and source codes of FORTRAN and BASIC programs are provided to illustrate the use of mathematical tools for any researcher or student interested in examining a natural neural network and discovering what makes it tick.
Comprehensive Overview of Advances in OlfactionThe common belief is that human smell perception is much reduced compared with other mammals, so that whatever abilities are uncovered and investigated in animal research would have little significance for humans. However, new evidence from a variety of sources indicates this traditional view is likely
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.
Invertebrates have proven to be extremely useful model systems for gaining insights into the neural and molecular mechanisms of sensory processing, motor control and higher functions such as feeding behavior, learning and memory, navigation, and social behavior. A major factor in their enormous contributions to neuroscience is the relative simplicity of invertebrate nervous systems. In addition, some invertebrates, primarily the molluscs, have large cells, which allow analyses to take place at the level of individually identified neurons. Individual neurons can be surgically removed and assayed for expression of membrane channels, levels of second messengers, protein phosphorylation, and RNA and protein synthesis. Moreover, peptides and nucleotides can be injected into individual neurons. Other invertebrate model systems such as Drosophila and Caenorhabditis elegans offer tremendous advantages for obtaining insights into the neuronal bases of behavior through the application of genetic approaches. The Oxford Handbook of Invertebrate Neurobiology reviews the many neurobiological principles that have emerged from invertebrate analyses, such as motor pattern generation, mechanisms of synaptic transmission, and learning and memory. It also covers general features of the neurobiology of invertebrate circadian rhythms, development, and regeneration and reproduction. Some neurobiological phenomena are species-specific and diverse, especially in the domain of the neuronal control of locomotion and camouflage. Thus, separate chapters are provided on the control of swimming in annelids, crustaea and molluscs, locomotion in hexapods, and camouflage in cephalopods. Unique features of the handbook include chapters that review social behavior and intentionality in invertebrates. A chapter is devoted to summarizing past contributions of invertebrates to the understanding of nervous systems and identifying areas for future studies that will continue to advance that understanding.
This book covers novel approaches using networks and oscillations and it will serve as a catalyst for translating these exciting advancements into the clinical arena. This collection of articles aims to accelerate the widespread clinical translation of network approaches by providing practical information accessible to clinicians in neurology and psychiatry - fields that are uniquely poised to implement these developments in clinical treatment of brain diseases. It should be a useful resource for researchers and clinicians in neurology and psychiatry.
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.
Molecular biology has driven a powerful reductionist, or “molecule-c- tric,” approach to biological research in the last half of the 20th century. Red- tionism is the attempt to explain complex phenomena by defining the functional properties of the individual components of the system. Bloom (1) has referred to the post-genome sequencing era as the end of “naïve reductionism. ” Red- tionist methods will continue to be an essential element of all biological research efforts, but “naïve reductionism,” the belief that reductionism alone can lead to a complete understanding of living organisms, is not tenable. Organisms are clearly much more than the sum of their parts, and the behavior of complex physiological processes cannot be understood simply by knowing how the parts work in isolation. Systems biology has emerged in the wake of genome sequencing as the s- cessor to reductionism (2–5). The “systems” of systems biology are defined over a wide span of complexity ranging from two macromolecules that interact to carry out a specific task to whole organisms. Systems biology is integrative and seeks to understand and predict the behavior or “emergent” properties of complex, multicomponent biological processes. A systems-level characteri- tion of a biological process addresses the following three main questions: (1) What are the parts of the system (i. e.
A thought-provoking argument that consciousness—more widespread than previously assumed—is the feeling of being alive, not a type of computation or a clever hack In The Feeling of Life Itself, Christof Koch offers a straightforward definition of consciousness as any subjective experience, from the most mundane to the most exalted—the feeling of being alive. Psychologists study which cognitive operations underpin a given conscious perception. Neuroscientists track the neural correlates of consciousness in the brain, the organ of the mind. But why the brain and not, say, the liver? How can the brain—three pounds of highly excitable matter, a piece of furniture in the universe, subject to the same laws of physics as any other piece—give rise to subjective experience? Koch argues that what is needed to answer these questions is a quantitative theory that starts with experience and proceeds to the brain. In The Feeling of Life Itself, Koch outlines such a theory, based on integrated information. Koch describes how the theory explains many facts about the neurology of consciousness and how it has been used to build a clinically useful consciousness meter. The theory predicts that many, and perhaps all, animals experience the sights and sounds of life; consciousness is much more widespread than conventionally assumed. Contrary to received wisdom, however, Koch argues that programmable computers will not have consciousness. Even a perfect software model of the brain is not conscious. Its simulation is fake consciousness. Consciousness is not a special type of computation—it is not a clever hack. Consciousness is about being.
Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. - Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology - Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems - Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience - Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain
