Artificial Brain And Simulation
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Artificial Brain And Simulation
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Author : S. R. Jena
language : en
Publisher: SRJX RESEARCH AND INNOVATION LAB LLP
Release Date : 2025-06-28
Artificial Brain And Simulation written by S. R. Jena and has been published by SRJX RESEARCH AND INNOVATION LAB LLP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-28 with Computers categories.
The human brain remains the most explosive enigmatic and powerful computing system ever known. Its unmatched ability to learn, adapt, reason, and generate creativity continues to inspire scientists, engineers, and philosophers across generations. With the rise of Artificial Intelligence (AI), Neuroscience, and Neuromorphic Engineering, the question once relegated to the realm of science fiction — Can we build an artificial brain? — is now a legitimate and actively explored scientific frontier. This book, Artificial Brain and Simulation, is an earnest attempt to synthesize the diverse yet interrelated domains of cognitive science, machine learning, brain simulation, neuromorphic computing, and robotics into a cohesive academic framework. This work is not merely a speculative exploration of artificial cognition. Rather, it is grounded in current scientific developments, technological breakthroughs, and practical systems already demonstrating nascent forms of synthetic intelligence. From IBM Watson’s symbolic reasoning to the digital neurons firing inside Intel’s Loihi neuromorphic chip, from brain-computer interfaces used in prosthetics to AI-driven diagnosis of neurological disorders, the world is witnessing an unprecedented convergence of human cognition and machine computation. This convergence is shaping what we refer to as Artificial Brain Simulation. Why This Book? The goal of this book is to serve as a comprehensive guide and reference text for students, researchers, academicians, technologists, and policy makers. It captures the evolving narrative of brain-inspired computing, simulative cognition, and intelligent neural interfaces. Despite the proliferation of literature on AI and neuroscience individually, there exists a noticeable void where both disciplines intersect with engineering design — particularly in the design and simulation of artificial brains. This book addresses that void. It dives deep into the biological fundamentals of the human brain while simultaneously translating those concepts into machine-executable systems, neural network models, and cognitive architectures. It traces the history, evaluates the present, and speculates on the future of artificially simulating human thought, perception, memory, decision-making, emotion, and even consciousness. Target Audience This book is written with multiple tiers of readers in mind: Undergraduate and graduate students studying computer science, neuroscience, AI, robotics, cognitive science, or biomedical engineering. Researchers and Ph.D. candidates seeking deep insights into brain-inspired AI, computational neuroscience, and machine consciousness. Faculty and educators looking for a structured reference to design multidisciplinary courses involving AI and biological cognition. Industry professionals and startups working on neural interfaces, robotics, AR/VR, BCI, IoT, and intelligent automation. Futurists and philosophers of technology interested in the ethical, social, and psychological dimensions of synthetic minds. Book Structure and Flow The book is divided into 14 meticulously crafted chapters, each building upon the foundation laid by its predecessors: Chapter 1: Introduction To Artificial Brain This chapter defines what constitutes an artificial brain, outlines the motivation behind its development, and distinguishes it from general-purpose AI. It provides historical insights and visual representations comparing human brains with machine-based intelligence. Chapter 2: Neuroscience Overview To simulate the brain, one must first understand it. This chapter explains the structure, components, and processes of the human brain — including neurons, synapses, learning, memory, and cognition — all explained in computational terms. Chapter 3: Foundations of Artificial Intelligence This chapter transitions to core AI principles, introducing learning paradigms (supervised, unsupervised, reinforcement), deep learning, neural networks, and cognitive architectures like ACT-R and SOAR. Chapter 4: Neuromorphic Computing Neuromorphic systems mimic the behavior of neurons in silicon. This chapter details spiking neural networks, memristors, neuromorphic chips like Loihi and TrueNorth, and the integration of hardware with software. Chapter 5: Brain-Inspired Algorithms Here we discuss Hebbian learning, reinforcement learning loops, bio-inspired optimization methods (GA, PSO, ACO, BFO), and deep cognitive networks as scalable learning systems. Chapter 6: Brain Simulation Projects This chapter dives into real-world simulations like the Blue Brain Project, the Human Brain Project (HBP), OpenWorm, and Nengo — highlighting architectural details and outcomes. Chapter 7: Architecture of Artificial Brain Covering layer-wise simulation of perception, cognition, decision-making, and motor control, this chapter also introduces architectural block diagrams of artificial brains in modular format. Chapter 8: Cognitive Computing and Reasoning Explores AI capabilities in symbolic reasoning, language understanding, planning, perception, and the philosophical notion of self-awareness in synthetic systems. Chapter 9: Memory and Learning Systems It delves into memory models (short-term vs long-term), neural memory frameworks, lifelong learning, and transfer learning. Visual diagrams illustrate how memory evolves in artificial systems. Chapter 10: AI in Healthcare and Brain-Computer Interfaces (BCIs) The intersection of AI and neuroscience is most visible in neural prosthetics, AI for neurological disorders, and BCI-based medical interventions. This chapter includes real-time BCI system design. Chapter 11: Robotics and Autonomous Systems This chapter introduces cognitive robots, emotion-enabled machines, artificial empathy, and humanoid assistants that simulate real social interaction and decision-making. Chapter 12: Smart Systems and Embedded AI Explores deployment of cognitive systems in mobile chips, IoT platforms, smart surveillance, and AR/VR environments. It underscores the importance of real-time, low-power neural architectures. Chapter 13: Ethical, Philosophical Issues and Technological Challenges As artificial brains grow closer to consciousness, this chapter discusses machine rights, existential risks, interpretability, and the control mechanisms necessary to safeguard humanity. A speculative yet evidence-based chapter exploring machine consciousness, AI-human symbiosis, and the implications of uploading human minds into machines (mind uploading). Chapter 14: The Future of Artificial Brain A forward-looking chapter forecasting technological, cognitive, societal, and regulatory trends shaping the future of artificial brain systems. Unique Features of the Book Interdisciplinary Approach: Merges neuroscience, AI, robotics, cognitive science, ethics, and embedded computing. Detailed Diagrams: Over 100 hand-drawn and digitally illustrated diagrams explain complex systems in accessible formats. Comparison Tables: Comparative evaluations of architectures (e.g., ACT-R vs SOAR), chip designs (Loihi vs TrueNorth), and learning models. Recent Research Citations: Each chapter ends with a list of 30 IEEE-style references covering the most recent developments. Case Studies & Applications: Includes Neuralink, BrainGate, OpenWorm, HBP, and real-world BCI-enabled prosthetics. Ethical & Philosophical Lens: Goes beyond technology to address societal impact, machine rights, and AI regulation. The journey toward building an artificial brain is not merely technological—it is deeply philosophical, neuropsychological, and even spiritual. The idea that machines could one day think, feel, or possess some form of synthetic awareness requires us to redefine intelligence, personhood, and even life itself. This book encourages readers to question conventional boundaries and embrace a future that may include minds made of code, thoughts running through silicon, and humanity coexisting with a new cognitive species. We believe Artificial Brain and Simulation will serve as a bridge — connecting the brilliance of natural intelligence with the promise of artificial cognition. Whether you are a student, researcher, or simply a curious mind, we invite you to embark on this voyage where biology meets computation, neurons inspire algorithms, and thought itself is reimagined. We thank you for picking up this book — and we hope it will both inform and inspire you to shape the intelligent systems of tomorrow.
Human Brain And Artificial Intelligence
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Author : An Zeng
language : en
Publisher: Springer Nature
Release Date : 2019-11-09
Human Brain And Artificial Intelligence written by An Zeng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-09 with Computers categories.
This book constitutes the refereed proceedings of the workshop held in conjunction with the 28th International Conference on Artificial Intelligence, IJCAI 2019, held in Macao, China, in August 2019: the First International Workshop on Human Brain and Artificial Intelligence, HBAI 2019. The 24 full papers presented were carefully reviewed and selected from 62 submissions. The papers are organized according to the following topical headings: computational brain science and its applications; brain-inspired artificial intelligence and its applications.
Philosophy And Theory Of Artificial Intelligence
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Author : Vincent C. Müller
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-08-23
Philosophy And Theory Of Artificial Intelligence written by Vincent C. Müller 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 2012-08-23 with Technology & Engineering categories.
Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here.
The Neural Simulation Language
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Author : Alfredo Weitzenfeld
language : en
Publisher: MIT Press
Release Date : 2002
The Neural Simulation Language written by Alfredo Weitzenfeld and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
Simulation in NSL - Modeling in NSL - Schematic Capture System - User Interface and Graphical Windows - The Modeling Language NSLM - The Scripting Language NSLS - Adaptive Resonance Theory - Depth Perception - Retina - Receptive Fields - The Associative Search Network: Landmark Learning and Hill Climbing - A Model of Primate Visual-Motor Conditional Learning - The Modular Design of the Oculomotor System in Monkeys - Crowley-Arbib Saccade Model - A Cerebellar Model of Sensorimotor Adaptation - Learning to Detour - Face Recognition by Dynamic Link Matching - Appendix I : NSLM Methods - NSLJ Extensions - NSLC Extensions - NSLJ and NSLC Differences - NSLJ and NSLC Installation Instructions.
Nanobrain
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Author : Anirban Bandyopadhyay
language : en
Publisher:
Release Date : 2019
Nanobrain written by Anirban Bandyopadhyay and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Artificial Brain
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Author : Fouad Sabry
language : en
Publisher: One Billion Knowledgeable
Release Date : 2022-07-10
Artificial Brain written by Fouad Sabry and has been published by One Billion Knowledgeable this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-10 with Technology & Engineering categories.
What Is Artificial Brain An artificial brain is a combination of computer software and hardware that has cognitive capacities that are analogous to those of a human or animal brain. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Artificial brain Chapter 2: Artificial intelligence Chapter 3: Chinese room Chapter 4: Technological singularity Chapter 5: The Age of Spiritual Machines Chapter 6: Mind uploading Chapter 7: Bio-inspired computing Chapter 8: Neuromorphic engineering Chapter 9: Artificial general intelligence Chapter 10: The Singularity Is Near Chapter 11: Neural network Chapter 12: Physical symbol system Chapter 13: Philosophy of artificial intelligence Chapter 14: Neuroinformatics Chapter 15: Outline of artificial intelligence Chapter 16: Hubert Dreyfus's views on artificial intelligence Chapter 17: Brain simulation Chapter 18: How to Create a Mind Chapter 19: Cognitive computer Chapter 20: Hypothetical technology Chapter 21: Turing's Wager (II) Answering the public top questions about artificial brain. (III) Real world examples for the usage of artificial brain in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of artificial brain' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of artificial brain.
Health Technology Sourcebook 2nd Ed
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Author : James Chambers
language : en
Publisher: Infobase Holdings, Inc
Release Date : 2021-07-01
Health Technology Sourcebook 2nd Ed written by James Chambers and has been published by Infobase Holdings, Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-01 with Health & Fitness categories.
Consumer health information about the application of science to develop solutions to health problems or issues such as the prevention or delay of onset of diseases or the promotion and monitoring of good health. Includes index, glossary of related terms, and other resources.
How To Build A Brain
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Author : Chris Eliasmith
language : en
Publisher: Oxford University Press
Release Date : 2013-04-16
How To Build A Brain written by Chris Eliasmith and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-16 with Psychology categories.
How to Build a Brain provides a detailed exploration of a new cognitive architecture - the Semantic Pointer Architecture - that takes biological detail seriously, while addressing cognitive phenomena. Topics ranging from semantics and syntax, to neural coding and spike-timing-dependent plasticity are integrated to develop the world's largest functional brain model.
Biomimetic And Biohybrid Systems
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Author : Nicholas S. Szczecinski
language : en
Publisher: Springer Nature
Release Date : 2024-12-12
Biomimetic And Biohybrid Systems written by Nicholas S. Szczecinski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-12 with Computers categories.
This proceeding constitutes the 13th International Conference on Biomimetic and Biohybrid Systems, held in Chicago, IL, USA, during July 8–11, 2024. The 27 full papers and 4 short papers were carefully reviewed and selected from 35 submissions. They were categorized under the following topics: Brain Network Modeling; Tools for Studying Behaviors; Sensors and Sensing, Navigational Systems; Control and Mechanics of Soft and Continuum Systems; System Design; Neural Networks for Computation; Bio Inspired Neural Networks for Control; Biohybrid Systems; and Biomechanics.
Artificial Intelligence Based Brain Computer Interface
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Author : Varun Bajaj
language : en
Publisher: Academic Press
Release Date : 2022-02-04
Artificial Intelligence Based Brain Computer Interface written by Varun Bajaj and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-04 with Science categories.
Artificial Intelligence-Based Brain Computer Interface provides concepts of AI for the modeling of non-invasive modalities of medical signals such as EEG, MRI and FMRI. These modalities and their AI-based analysis are employed in BCI and related applications. The book emphasizes the real challenges in non-invasive input due to the complex nature of the human brain and for a variety of applications for analysis, classification and identification of different mental states. Each chapter starts with a description of a non-invasive input example and the need and motivation of the associated AI methods, along with discussions to connect the technology through BCI. Major topics include different AI methods/techniques such as Deep Neural Networks and Machine Learning algorithms for different non-invasive modalities such as EEG, MRI, FMRI for improving the diagnosis and prognosis of numerous disorders of the nervous system, cardiovascular system, musculoskeletal system, respiratory system and various organs of the body. The book also covers applications of AI in the management of chronic conditions, databases, and in the delivery of health services. - Provides readers with an understanding of key applications of Artificial Intelligence to Brain-Computer Interface for acquisition and modelling of non-invasive biomedical signal and image modalities for various conditions and disorders - Integrates recent advancements of Artificial Intelligence to the evaluation of large amounts of clinical data for the early detection of disorders such as Epilepsy, Alcoholism, Sleep Apnea, motor-imagery tasks classification, and others - Includes illustrative examples on how Artificial Intelligence can be applied to the Brain-Computer Interface, including a wide range of case studies in predicting and classification of neurological disorders