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Significant progress has been made in recent years in studying the dynamics of the diseased brain at both microscopic and macroscopic levels. Electrical recordings of the diseased brain activity show (in)-coherent dynamic phenomena at scales ranging from local networks (thousands of neurons) to entire brain regions (millions of neurons). Our understanding of these spatial and temporal scales and resolutions continues to increase as evidence suggests close relationships between local field potentials recorded in the cortex (with electroencephalography or multi-unit recordings) and blood flow signals (measured with fMRI). Application of multi-scale computational models as integrative principles that bridge the single neuron dynamics (monitored with intracellular recordings) with the dynamics of local and distant brain regions observed using human EEG, ERPs, MEG, LFPs and fMRI can further enhance our understanding of the diseased brain dynamics. The goal of this book is to provide a focused series of papers on computational models of brain disorders combining multiple levels and types of computation with multiple types of data in an effort to improve understanding, prediction and treatment of brain and mental illness. The volume aims to bring together physiologists and anatomists studying cortical circuits, cognitive neuroscientists studying brain dynamics and behaviour via EEG and functional magnetic resonance imaging (fMRI), and computational neuroscientists using neural modelling techniques to explore local and large-scale disordered brain dynamics. The thematic focus is expected to be appealing to a diverse group of investigators and have a high impact on the medical, neuroscience and computer science fields.

Brain --- Diseases. --- Neurosciences. --- Neural sciences --- Neurological sciences --- Neuroscience --- Medical sciences --- Nervous system --- Brain diseases --- Psychology, Pathological

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The perception-action cycle is the circular flow of information that takes place between the organism and its environment in the course of a sensory-guided sequence of behavior towards a goal. Each action causes changes in the environment that are analyzed bottom-up through the perceptual hierarchy and lead to the processing of further action, and top-down through the executive hierarchy toward motor effectors. These actions cause new changes that are analyzed and lead to new action, and so the cycle continues. The Perception-Action cycle: Models, Architectures and Hardware book provides focused and easily accessible reviews of various aspects of the perception-action cycle. It is an unparalleled resource of information that will be an invaluable companion to anyone in constructing and developing models, algorithms, and hardware implementations of autonomous machines empowered with cognitive capabilities. The book is divided into three main parts. In the first part, leading computational neuroscientists present brain-inspired models of perception, attention, cognitive control, decision making, conflict resolution and monitoring, knowledge representation and reasoning, learning and memory, planning and action, and consciousness grounded in experimental data. In the second part, architectures, algorithms, and systems with cognitive capabilities and minimal guidance from the brain are discussed. These architectures, algorithms, and systems are inspired by cognitive science, computer vision, robotics, information theory, machine learning, computer agents, and artificial intelligence. In the third part, the analysis, design, and implementation of hardware systems with robust cognitive abilities from the areas of mechatronics, sensing technology, sensor fusion, smart sensor networks, control rules, controllability, stability, model/knowledge representation, and reasoning are discussed. About the Editors: Vassilis Cutsuridis is a Senior Research Scientist at the Center for Memory and Brain at Boston University, Boston, USA. Amir Hussain is a Reader in Computing Science in the Department of Computing Science and Mathematics at the University of Stirling, UK. John G. Taylor is an Emeritus Distinguished Professor of Mathematics in the Department of Mathematics at King’s College, London, UK.

Cognition in children. --- Education -- Effect of technological innovations on. --- Educational technology -- Psychological aspects. --- Learning, Psychology of. --- Neural networks (Computer science) --- Perceptual-motor processes --- Pattern Recognition, Automated --- Mathematical Concepts --- Psychological Phenomena and Processes --- Models, Biological --- Artificial Intelligence --- Phenomena and Processes --- Models, Theoretical --- Computing Methodologies --- Information Science --- Psychiatry and Psychology --- Investigative Techniques --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Neural Networks (Computer) --- Models, Neurological --- Mental Processes --- Medicine --- Engineering & Applied Sciences --- Health & Biological Sciences --- Computer Science --- Neurology --- Computer algorithms. --- Information resources management. --- Corporations --- Information resource management --- Information systems management --- IRM (Information resources management) --- Information resources management --- Medicine. --- Neurosciences. --- Computers. --- Neurobiology. --- Biomedicine. --- Computation by Abstract Devices. --- Signal, Image and Speech Processing. --- Management --- Management information systems --- Algorithms --- Computer science. --- Neurosciences --- Informatics --- Science --- Neural sciences --- Neurological sciences --- Neuroscience --- Medical sciences --- Nervous system --- Signal processing. --- Image processing. --- Speech processing systems. --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace

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This is the 2nd edition of a very well received and popular book that reflects the current state-of-the-art of the ongoing research avenues concerning the hippocampus and processing units bridging the gap between single cell activity, network activity and global brain function. It aims to provide a methodology to anyone interested in developing microcircuit level models of the hippocampus. The book is divided into two thematic areas: (I) Experimental background and (II) Computational analysis. In part I, leading experimental neuroscientists discuss the morphological, physiological and molecular characteristics as well as the connectivity and synaptic properties of the various cell types found in the hippocampus. Behaviour-related ensemble activity patterns of morphologically identified neurons in anesthetized and freely moving animals provide insights on the function of the hippocampal areas. In part II, computational neuroscientists present models of the hippocampal microcircuits at various levels of detail (e.g. single cell level, network level, etc.). Synaptomics and connectomics models of hippocampal structures are initially discussed. Then, network models of memory, rhythm generation and spatial navigation are presented, followed by abstract and biophysical models of synaptic plasticity. Network models of hippocampal implicated disorders (epilepsy and schizophrenia) are then detailed and how their network topologies, connectivities and activities change in these diseases. Finally, two chapters are dedicated to describing simulator environments of single neurons and networks currently used by computational neuroscientists in developing their models and modelling tools to parametrically constrain them. This engaging volume is invaluable to experimental and computational neuroscientists, electrical engineers, physicists, mathematicians and others interested in developing microcircuit models of the hippocampus. Graduate level students and trainees in all of these fields can find this book a significant source of information.

Neurosciences. --- Neurobiology. --- Biology --- Computer Appl. in Life Sciences. --- Data processing. --- Hippocampus (Brain) --- Computer simulation. --- Ammon's horn --- Cornu ammonis --- Cerebral cortex --- Limbic system --- Neurosciences --- Neural sciences --- Neurological sciences --- Neuroscience --- Medical sciences --- Nervous system --- Bioinformatics . --- Computational biology . --- Bioinformatics --- Bio-informatics --- Biological informatics --- Information science --- Computational biology --- Systems biology --- Data processing

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This is the 2nd edition of a very well received and popular book that reflects the current state-of-the-art of the ongoing research avenues concerning the hippocampus and processing units bridging the gap between single cell activity, network activity and global brain function. It aims to provide a methodology to anyone interested in developing microcircuit level models of the hippocampus. The book is divided into two thematic areas: (I) Experimental background and (II) Computational analysis. In part I, leading experimental neuroscientists discuss the morphological, physiological and molecular characteristics as well as the connectivity and synaptic properties of the various cell types found in the hippocampus. Behaviour-related ensemble activity patterns of morphologically identified neurons in anesthetized and freely moving animals provide insights on the function of the hippocampal areas. In part II, computational neuroscientists present models of the hippocampal microcircuits at various levels of detail (e.g. single cell level, network level, etc.). Synaptomics and connectomics models of hippocampal structures are initially discussed. Then, network models of memory, rhythm generation and spatial navigation are presented, followed by abstract and biophysical models of synaptic plasticity. Network models of hippocampal implicated disorders (epilepsy and schizophrenia) are then detailed and how their network topologies, connectivities and activities change in these diseases. Finally, two chapters are dedicated to describing simulator environments of single neurons and networks currently used by computational neuroscientists in developing their models and modelling tools to parametrically constrain them. This engaging volume is invaluable to experimental and computational neuroscientists, electrical engineers, physicists, mathematicians and others interested in developing microcircuit models of the hippocampus. Graduate level students and trainees in all of these fields can find this book a significant source of information.

Biology --- Physiology of nerves and sense organs --- Neuropathology --- Computer. Automation --- neurologie --- biologie --- informatica --- wiskunde --- ingenieurswetenschappen --- neurobiologie --- moleculaire biologie

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The hippocampus plays an indispensible role in the formation of new memories in the mammalian brain. It is the focus of intense research and our understanding of its physiology, anatomy, and molecular structure has rapidly expanded in recent years. Yet, still much needs to be done to decipher how hippocampal microcircuits are built and function. Here, we present an overview of our current knowledge and a snapshot of ongoing research into these microcircuits. Rich in detail, Hippocampal Microcircuits: A Computational Modeler's Resource Book provides focused and easily accessible reviews on various aspects of the theme. It is an unparalleled resource of information, including both data and techniques that will be an invaluable companion to all those wishing to develop computational models of hippocampal neurons and neuronal networks. The book is divided into two main parts. In the first part, leading experimental neuroscientists discuss data on the electrophysiological, neuroanatomical, and molecular characteristics of hippocampal circuits. The various types of excitatory and inhibitory neurons are reviewed along with their connectivity and synaptic properties. Single cell and ensemble activity patterns are presented from in vitro models, as well as anesthetized and freely moving animals. In the second part, computational neuroscientists describe models of hippocampal microcircuits at various levels of complexity, from single neurons to large-scale networks. Additionally, a chapter is devoted to simulation environments currently used by computational neuroscientists in developing their models. In addition to providing concise reviews and a wealth of data, the chapters also identify central questions and unexplored areas that will define future research in computational neuroscience. About the Editors: Dr. Vassilis Cutsuridis is a Research Fellow in the Department of Computing Science and Mathematics at the University of Stirling, Scotland, UK. Dr. Bruce P. Graham is a Reader in Computing Science in the Department of Computing Science and Mathematics at the University of Stirling. Dr. Stuart Cobb and Dr. Imre Vida are Senior Lecturers in the Neuroscience and Molecular Pharmacology Department at the University of Glasgow, Scotland, UK.

Biomathematics. Biometry. Biostatistics --- Biological techniques --- Biology --- Physiology of nerves and sense organs --- Neuropathology --- Computer. Automation --- neurologie --- bio-informatica --- biologie --- informatica --- neurobiologie