Biological Neural Networks Hierarchical Concept Of Brain Function

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Biological Neural Networks Hierarchical Concept Of Brain Function

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Author : Konstantin V. Baev
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Biological Neural Networks Hierarchical Concept Of Brain Function written by Konstantin V. Baev and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.

This book is devoted to a novel conceptual theoretical framework of neuro science and is an attempt to show that we can postulate a very small number of assumptions and utilize their heuristics to explain a very large spectrum of brain phenomena. The major assumption made in this book is that inborn and acquired neural automatisms are generated according to the same func tional principles. Accordingly, the principles that have been revealed experi mentally to govern inborn motor automatisms, such as locomotion and scratching, are used to elucidate the nature of acquired or learned automat isms. This approach allowed me to apply the language of control theory to describe functions of biological neural networks. You, the reader, can judge the logic of the conclusions regarding brain phenomena that the book derives from these assumptions. If you find the argument flawless, one can call it common sense and consider that to be the best praise for a chain of logical conclusions. For the sake of clarity, I have attempted to make this monograph as readable as possible. Special attention has been given to describing some of the concepts of optimal control theory in such a way that it will be under standable to a biologist or physician. I have also included plenty of illustra tive examples and references designed to demonstrate the appropriateness and applicability of these conceptual theoretical notions for the neurosciences.

Biological Neural Networks

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Author : Konstantin Vasilʹevich Baev
language : en
Publisher:
Release Date : 1998

Biological Neural Networks written by Konstantin Vasilʹevich Baev and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Neural networks (Neurobiology) categories.

Collective Consciousness And Gender

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Author : Alexandra Walker
language : en
Publisher: Springer
Release Date : 2018-08-22

Collective Consciousness And Gender written by Alexandra Walker and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-22 with Psychology categories.

This book explores collective consciousness and how it is applied to the pursuit of gender justice in international law. It discusses how the collective mode of behaviour and identity can lead to unconscious role-playing based on the social norms, expectations or archetypes of a group. Alexandra Walker contends that throughout history, men have been constructed as archetypal dominators and women as victims. In casting women in this way, we have downplayed their pre-existing, innate capacities for strength, leadership and power. In casting men as archetypal dominators, we have downplayed their capacities for nurturing, care and empathy. The author investigates the widespread implications of this unconscious role-playing, arguing that even in countries in which women have many of the same legal rights as men, gender justice and equality have been too simplistically framed as ‘feminism’ and ‘women’s rights’ and that giving women the rights of men has not created gender balance. This book highlights the masculine and feminine traits belonging to all individuals and calls on international law to reflect this gender continuum.

Deep Learning

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Author : Manish Soni
language : en
Publisher:
Release Date : 2024-11-13

Deep Learning written by Manish Soni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-13 with Computers categories.

Welcome to "Deep Learning: A Comprehensive Guide," a book meticulously designed to cater to the needs of learners at various stages of their journey into the fascinating world of deep learning. Whether you are a beginner embarking on your first exploration into artificial intelligence or a seasoned professional looking to deepen your expertise, this book aims to be your trusted companion. Deep learning, a subset of machine learning, has revolutionized the field of artificial intelligence, enabling advancements that were once thought to be the stuff of science fiction. From autonomous vehicles to sophisticated natural language processing systems, deep learning has become the backbone of many cutting-edge technologies. Understanding and mastering deep learning is not just a desirable skill but a necessity for anyone looking to thrive in the modern tech landscape. What This Book Offers This book is not just a theoretical exposition but a practical guide designed to provide you with a holistic learning experience. Here's a glimpse of what you can expect: Structured Content: Starts with neural network basics and advances to topics like convolutional, recurrent, and generative adversarial networks. Each chapter builds on the previous, ensuring a comprehensive learning journey. Online Practice Questions: Each chapter includes practice questions from basic to advanced levels to test and reinforce your understanding. Videos: Instructional videos complement the book's content, offering step-by-step explanations and real-life applications. Exercises and Projects: Includes exercises and hands-on projects that simulate real-world problems, providing practical experience. Lab Activities: Features lab activities using frameworks like TensorFlow and PyTorch for hands-on experimentation with deep learning models. Case Studies: Illustrates the application of deep learning in industries such as healthcare, finance, and entertainment, highlighting its transformative potential. Comprehensive Coverage: Covers a broad spectrum of topics, from theoretical foundations to practical implementations, latest advancements, ethical considerations, and future trends. Who Should Use This Book? This book is designed for: Students and Academics: Pursuing studies in computer science, data science, or related fields. Industry Professionals: Enhancing skills or transitioning into roles involving deep learning. Embarking on the journey to master deep learning is both challenging and rewarding. This book is designed to make that journey as smooth and enlightening as possible. We hope that the combination of theoretical knowledge, practical exercises, projects, and real-world applications will equip you with the skills and confidence needed to excel in the field of deep learning.

Hierarchy And Dynamics In Neural Networks

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Author : Rolf Kötter
language : en
Publisher: Frontiers E-books
Release Date : 2012-01-01

Hierarchy And Dynamics In Neural Networks written by Rolf Kötter and has been published by Frontiers E-books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-01 with categories.

Hierarchy is a central feature in the organisation of complex biological systems and particularly the structure and function of neural networks. While other aspects of brain connectivity such as regionalisation, modularity or motif composition have been discussed elsewhere, no detailed analysis has been presented so far on the role of hierarchy and its connection to brain dynamics. Recent discussions among many of our colleagues have shown an increasing interest in hierarchy (of spatial, temporal and dynamic features), and this is an emerging key question in neuroscience as well as generally in the field of network science, due to its links with concepts of control, efficiency and development across scales (e.g. Hilgetag et al. Science, 1996; Ravasz et al. Science, 2002; Bassett et al. PNAS, 2006; Mueller-Linow et al. PLoS Comp. Biol., in press). The proposed Research Topic will address recent findings from a theoretical as well as experimental perspective including contributions under the following four headings: 1) Topology: Detecting and characterizing network hierarchy; 2) Experiments: Neural dynamics across hierarchical scales; 3) Dynamics: Activity spread, oscillations, and synchronization in hierarchical networks; 4) Dynamics: Stable functioning and information processing in hierarchical networks.

Intelligent Medicine On Prediction Of Pelvic Lymph Node Metastasis

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Author : Haixian Zhang
language : en
Publisher: Elsevier
Release Date : 2024-10-23

Intelligent Medicine On Prediction Of Pelvic Lymph Node Metastasis written by Haixian Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-23 with Science categories.

Intelligent Medicine on Prediction of Pelvic Lymph Node Metastasis focuses on leveraging intelligent medical techniques to predict lymph node metastasis, using pelvic cancer as a primary case study. Combined with the actual clinical application scenarios, this book introduces deep neural network models, application systems, and carries out method concentrated on the four major links of lymph node location, partition, segmentation and metastasis prediction, aiming to provide theoretical and experimental reference for researchers in this field. In 8 chapters this title introduces the reader to intelligent medicine and deep neural networks, summarises the intelligent biological neural network and the classical artificial neural network, introduces several commonly used network architectures and a new neural network model, and introduces the deep learning based algorithms on lymph nodes metastasis prediction, summarising the method and experimental results. This book is a friendly learning tool, providing beginners and researchers with an in-depth knowledge of deep learning and how to develop intelligent medicine methods in lymph node metastasis prediction. - Provides readers with the recent deep learning findings and possible future directions on lesion monitoring - Introduces intelligent medicine development and the artificial intelligence basis, including a new generation of neural network - Keeps the reader up-to-date with the latest research progress of deep learning architectures for lymph node metastasis prediction - Gives systematical insights into the deep learning algorithms for lymph node metastasis prediction, experiments and results, and potential research direction

System And Circuit Design For Biologically Inspired Intelligent Learning

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Author : Temel, Turgay
language : en
Publisher: IGI Global
Release Date : 2010-10-31

System And Circuit Design For Biologically Inspired Intelligent Learning written by Temel, Turgay and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-31 with Medical categories.

"The objective of the book is to introduce and bring together well-known circuit design aspects, as well as to cover up-to-date outcomes of theoretical studies in decision-making, biologically-inspired, and artificial intelligent learning techniques"--Provided by publisher.

Biophysical Neural Networks

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Author : Roman R. Poznanski
language : en
Publisher:
Release Date : 2001

Biophysical Neural Networks written by Roman R. Poznanski and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Medical categories.

Modeling of neural networks has been in the past mostly associated with the computer analogy. All this is to change in a volume dedicated to provinding a clear exposition of the biophysical and biochemical processes that underpin the functioning of single neurons in networks. The contents serve as an invaluable reference to the subject of biologically more plausible neural networks. This book will provide a thorough understanding of quantitative modeling with each chapter containing abundant references and a set of problems to challenge the inspiring post graduate student or researcher.

Insights In Systems Biology Research

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Author : Gary An
language : en
Publisher: Frontiers Media SA
Release Date : 2025-06-10

Insights In Systems Biology Research written by Gary An and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-10 with Science categories.

Summary of Topic: This collection represents an interdisciplinary exploration of systems biology and systems medicine, integrating advanced methodologies from computational modeling, deep neural networks, and multiomics to improve understanding and treatment of human diseases and biological mechanisms. Emphasis is placed on cutting-edge technologies, including deep learning for statistical inference from gene expression data and noncoding genetic variants, quantitative systems pharmacology for virtual patient generation, and semi-mechanistic modeling applied to novel therapies such as CAR T-cell interventions. The articles further highlight disease modeling across various scales, exemplified through multi-scale simulation frameworks applied to complex conditions such as COVID-19 long-term sequelae, rheumatoid arthritis, epilepsy, and tuberculosis. Additionally, the importance of modularity in biological networks, developments in functional annotation of microbial transporters, and new approaches towards bioengineered bacterial consortia through molecular communication are discussed. This collection informs us of the ongoing efforts to harness computational power and biological insights to advance personalized medicine, improve therapeutic strategies, and deepen our understanding of complex biological phenomena. ----- Systems Biology has undergone significant transformations due to the pioneering efforts of researchers worldwide. The discipline now spans several subfields, such as Neuroscience, Genetics and Genomics, Medicine, among others, each advancing the field in unique ways through innovative technologies and insightful discoveries. This evolution is celebrated in a curated collection by Frontiers in Systems Biology, which aims to highlight the state-of-the-art developments and set the stage for future inquiries and applications in the field. This collection actively showcases the overlap of technology with theoretical advancements, creating a broad framework from which new methodologies and strategies are born. This Research Topic aims to provide an overview of the most recent progress in Systems Biology. It seeks to outline the impacts that the integration of disparate biological research areas can have in solving complex biological problems and advancing human health. Without losing sight of the past achievements, the goal is to explore the potential of future advancements, addressing the challenges that remain at the forefront of this vibrant field. The scope of this Research Topic is broadly defined yet focused on areas where significant innovative strides have been made. We welcome contributions that emphasize: - Integrative approaches in Systems Neuroscience - Contemporary breakthroughs in Genetics and Genomics - The use of Multiscale Mechanistic Modelling to represent biological interfaces - Bridging gaps between experimental and computational biology in Translational Systems Biology - Enhancing methodologies in Data and Model Integration This collection welcomes contributions from Editorial Board Members or those referred by a board member, reflecting on current developments and plotting pathways for upcoming research endeavors. Authors are encouraged to engage critically with their fields, identifying current challenges and proposing novel solutions to advance the understanding of complex systems within biology.

Theoretical Mechanics Of Biological Neural Networks

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Author : Ronald J. MacGregor
language : en
Publisher: Elsevier
Release Date : 2012-12-02

Theoretical Mechanics Of Biological Neural Networks written by Ronald J. MacGregor and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-02 with Science categories.

Theoretical Mechanics of Biological Neural Networks presents an extensive and coherent discusson and formulation of the generation and integration of neuroelectric signals in single neurons. The approach relates computer simulation programs for neurons of arbitrary complexity to fundamental gating processes of transmembrance ionic fluxes of synapses of excitable membranes. Listings of representative computer programs simulating arbitrary neurons, and local and composite neural networks are included. - Develops a theory of dynamic similarity for characterising the firing rate sensitivites of neurons in terms of their characteristic anatomical and physiological parameters - Presents the sequential configuration theory - a theoretical presentation of coordinated firing patterns in entire neural population - Presents the outlines of mechanics for multiple interacting networks in composite systems