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Supercomputing facilities are becoming increasingly available for simulating activity dynamics in large-scale neuronal networks. On today's most advanced supercomputers, networks with up to a billion of neurons can be readily simulated. However, building biologically realistic, full-scale brain models requires more than just a huge number of neurons. In addition to network size, the detailed local and global anatomy of neuronal connections is of crucial importance. Moreover, anatomical connectivity is not fixed, but can rewire throughout life (structural plasticity)—an aspect that is missing in most current network models, in which plasticity is confined to changes in synaptic strength (synaptic plasticity). The papers in this Ebook, which may broadly be divided into three themes, aim to bring together high-performance computing with recent experimental and computational research in neuroanatomy. In the first theme (fiber connectivity), new methods are described for measuring and data-basing microscopic and macroscopic connectivity. In the second theme (structural plasticity), novel models are introduced that incorporate morphological plasticity and rewiring of anatomical connections. In the third theme (large-scale simulations), simulations of large-scale neuronal networks are presented with an emphasis on anatomical detail and plasticity mechanisms. Together, the articles in this Ebook make the reader aware of the methods and models by which large-scale brain networks running on supercomputers can be extended to include anatomical detail and plasticity.
Computational Psychiatry: Mathematical Modeling of Mental Illness is the first systematic effort to bring together leading scholars in the fields of psychiatry and computational neuroscience who have conducted the most impactful research and scholarship in this area. It includes an introduction outlining the challenges and opportunities facing the field of psychiatry that is followed by a detailed treatment of computational methods used in the service of understanding neuropsychiatric symptoms, improving diagnosis and guiding treatments. This book provides a vital resource for the clinical neuroscience community with an in-depth treatment of various computational neuroscience approaches geared towards understanding psychiatric phenomena. Its most valuable feature is a comprehensive survey of work from leaders in this field. - Offers an in-depth overview of the rapidly evolving field of computational psychiatry - Written for academics, researchers, advanced students and clinicians in the fields of computational neuroscience, clinical neuroscience, psychiatry, clinical psychology, neurology and cognitive neuroscience - Provides a comprehensive survey of work from leaders in this field and a presentation of a range of computational psychiatry methods and approaches geared towards a broad array of psychiatric problems
Experimental and theoretical approaches to global brain dynamics that draw on the latest research in the field. The consideration of time or dynamics is fundamental for all aspects of mental activity—perception, cognition, and emotion—because the main feature of brain activity is the continuous change of the underlying brain states even in a constant environment. The application of nonlinear dynamics to the study of brain activity began to flourish in the 1990s when combined with empirical observations from modern morphological and physiological observations. This book offers perspectives on brain dynamics that draw on the latest advances in research in the field. It includes contributions from both theoreticians and experimentalists, offering an eclectic treatment of fundamental issues. Topics addressed range from experimental and computational approaches to transient brain dynamics to the free-energy principle as a global brain theory. The book concludes with a short but rigorous guide to modern nonlinear dynamics and their application to neural dynamics.
The adult brain is not as hard-wired as traditionally thought. By modifying their small- or large-scale morphology, neurons can make new synaptic connections or break existing ones (structural plasticity). Structural changes accompany memory formation and learning, and are induced by neurogenesis, neurodegeneration and brain injury such as stroke. Exploring the role of structural plasticity in the brain can be greatly assisted by mathematical and computational models, as they enable us to bridge the gap between system-level dynamics and lower level cellular and molecular processes. However, most traditional neural network models have fixed neuronal morphologies and a static connectivity pattern, with plasticity merely arising from changes in the strength of existing synapses (synaptic plasticity). In The Rewiring Brain, the editors bring together for the first time contemporary modeling studies that investigate the implications of structural plasticity for brain function and pathology. Starting with an experimental background on structural plasticity in the adult brain, the book covers computational studies on homeostatic structural plasticity, the impact of structural plasticity on cognition and cortical connectivity, the interaction between synaptic and structural plasticity, neurogenesis-related structural plasticity, and structural plasticity in neurological disorders. Structural plasticity adds a whole new dimension to brain plasticity, and The Rewiring Brain shows how computational approaches may help to gain a better understanding of the full adaptive potential of the adult brain. The book is written for both computational and experimental neuroscientists. - Reviews the current state of knowledge of structural plasticity in the adult brain - Gives a comprehensive overview of computational studies on structural plasticity - Provides insights into the potential driving forces of structural plasticity and the functional implications of structural plasticity for learning and memory - Serves as inspiration for developing novel treatment strategies for stimulating functional repair after brain damage
The brain ... There is no other part of the human anatomy that is so intriguing. How does it develop and function and why does it sometimes, tragically, degenerate? The answers are complex. In Discovering the Brain, science writer Sandra Ackerman cuts through the complexity to bring this vital topic to the public. The 1990s were declared the "Decade of the Brain" by former President Bush, and the neuroscience community responded with a host of new investigations and conferences. Discovering the Brain is based on the Institute of Medicine conference, Decade of the Brain: Frontiers in Neuroscience and Brain Research. Discovering the Brain is a "field guide" to the brainâ€"an easy-to-read discussion of the brain's physical structure and where functions such as language and music appreciation lie. Ackerman examines: How electrical and chemical signals are conveyed in the brain. The mechanisms by which we see, hear, think, and pay attentionâ€"and how a "gut feeling" actually originates in the brain. Learning and memory retention, including parallels to computer memory and what they might tell us about our own mental capacity. Development of the brain throughout the life span, with a look at the aging brain. Ackerman provides an enlightening chapter on the connection between the brain's physical condition and various mental disorders and notes what progress can realistically be made toward the prevention and treatment of stroke and other ailments. Finally, she explores the potential for major advances during the "Decade of the Brain," with a look at medical imaging techniquesâ€"what various technologies can and cannot tell usâ€"and how the public and private sectors can contribute to continued advances in neuroscience. This highly readable volume will provide the public and policymakersâ€"and many scientists as wellâ€"with a helpful guide to understanding the many discoveries that are sure to be announced throughout the "Decade of the Brain."
Recent studies show that more people than ever before are reaching old age in better health and enjoying that health for a longer time. This Handbook outlines the latest discoveries in the study of aging from bio-medicine, psychology, and socio-demography. It treats the study of aging as a multidisciplinary scientific subject, since it requires the interplay of broad disciplines, while offering high motivation, positive attitudes, and behaviors for aging well, and lifestyle changes that will help people to stay healthier across life span and in old age. Written by leading scholars from various academic disciplines, the chapters delve into the most topical aspects of aging today - including biological mechanisms of aging, aging with health, active and productive aging, aging with satisfaction, aging with respect, and aging with dignity. Aimed at health professionals as well as general readers, this Cambridge Handbook offers a new, positive approach to later life.
Traumatic brain injury (TBI) remains a significant source of death and permanent disability, contributing to nearly one-third of all injury related deaths in the United States and exacting a profound personal and economic toll. Despite the increased resources that have recently been brought to bear to improve our understanding of TBI, the developme
Consciousness Genesis In Artificial Intelligence" by Professor Ibrahim El Noshokaty, I can provide a preliminary review that outlines the structure and content captured within the initial pages available to me. Below is an overview based on the table of contents and some introductory text: Title: Consciousness Genesis In Artificial Intelligence Author: Professor Ibrahim El Noshokaty Overview: The academic work delves into the complex topic of artificial intelligence and its relation to human-like consciousness. It explores whether AI can be creative, how numerical data and programming languages can emulate human sensory experiences and emotions, and the potential implications of such advances. Chapters and Themes: Introduction and Fuzzy Logic System: Initiates the discussion with fundamental questions about AI creativity and creation, followed by the exposition of fuzzy logic systems. Existential Threat and AI in Hollywood: Examines AI's potential to disrupt industries such as Hollywood, the feasibility of generative AI in original content production, and copyright issues in AI outputs. Hierarchical Fuzzy Deep Learning: Discusses advanced AI techniques to enhance learning and decision making, addressing the concepts of consciousness and fuzzy logic in AI. Algorithms for Modern Fuzzy Logic Systems: Delves into the technical aspects of fuzzy logic systems and algorithms, highlighting methods for system optimization. Development of Conscience in AI: Contemplates the moral aspects and decision-making capabilities of AI systems, along with the incorporation of ethical considerations and human values. Artificial Cognition: Analyzes the notion of machine learning and cognition, transparency within AI mechanisms, and the ethical implications of artificial minds. Artificial Sensations: Explores the development of AI systems capable of mimicking human senses and responses, using advanced materials and devices. Artificial Brain: Concludes with an investigation into mimicking human brain function within AI systems and the potential capacity for AI to evolve with environmental interaction. The work appears to be an exploration of the frontier where technology meets human cognition, emotion, and ethical considerations. The book may offer expertise in several domains, including AI algorithms, deep learning, neuromorphic computing, and the philosophical implications of imbuing AI with aspects of human consciousness. The manuscript's purpose is likely to probe the theoretical boundaries of AI and its future potential, as well as to identify and confront some of the ethical dilemmas that arise as AI systems become increasingly sophisticated. This preliminary review only scratches the surface of what the book contains. For a full review, including critical analysis and conclusions, it would be necessary to read the document in its entirety. If you have any specific areas you'd like me to focus on or if there are particular chapters you want to examine in more detail, please let me know.
Heterogeneity of Function in Numerical Cognition presents the latest updates on ongoing research and discussions regarding numerical cognition. With great individual differences in the development or function of numerical cognition at neuroanatomical, neuropsychological, behavioral, and interactional levels, these issues are important for the achievement of a comprehensive understanding of numerical cognition, hence its brain basis, development, breakdown in brain-injured individuals, and failures to master mathematical skills. These functions are essential for the proper development of numerical cognition. - Provides an innovative reference on the emerging field of numerical cognition and the branches that converge on this diverse cognitive domain - Includes an overview of the multiple disciplines that comprise numerical cognition - Focuses on factors that influence numerical cognition, such as language, executive attention, memory and spatial processing - Features an innovative organization with each section providing a general overview, developmental research, and evidence from neurocognitive studies
An important aspect of neuroscience is to characterize the underlying connectivity patterns of the human brain (i.e., human connectomics). Over the past few years, researchers have demonstrated that by combining a variety of different neuroimaging technologies (e.g., structural MRI, diffusion MRI and functional MRI) with sophisticated analytic strategies such as graph theory, it is possible to noninvasively map the patterns of structural and functional connectivity of human whole-brain networks. With these novel approaches, many studies have shown that human brain networks have nonrandom properties such as modularity, small-worldness and highly connected hubs. Importantly, these quantifiable network properties change with age, learning and disease. Moreover, there is growing evidence for behavioral and genetic correlates. Network analysis of neuroimaging data is opening up a new avenue of research into the understanding of the organizational principles of the brain that will be of interest for all basic scientists and clinical researchers. Such approaches are powerful but there are a number of challenging issues when extracting reliable brain networks from various imaging modalities and analyzing the topological properties, e.g., definitions of network nodes and edges and reproducibility of network analysis. We assembled contributions related to the state-of-the-art methodologies of brain connectivity and the applications involving development, aging and neuropsychiatric disorders such as Alzheimer’s disease, schizophrenia, attention deficit hyperactivity disorder and mood and anxiety disorders. It is anticipated that the articles in this Research Topic will provide a greater range and depth of provision for the field of imaging connectomics.