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Book Neural and Computational Modeling of Movement Control

Download or read book Neural and Computational Modeling of Movement Control written by Ning Lan and published by Frontiers Media SA. This book was released on 2017-04-17 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the study of sensorimotor systems, an important research goal has been to understand the way neural networks in the spinal cord and brain interact to control voluntary movement. Computational modeling has provided insight into the interaction between centrally generated commands, proprioceptive feedback signals and the biomechanical responses of the moving body. Research in this field is also driven by the need to improve and optimize rehabilitation after nervous system injury and to devise biomimetic methods of control in robotic devices. This research topic is focused on efforts dedicated to identify and model the neuromechanical control of movement. Neural networks in the brain and spinal cord are known to generate patterned activity that mediates coordinated activation of multiple muscles in both rhythmic and discrete movements, e.g. locomotion and reaching. Commands descending from the higher centres in the CNS modulate the activity of spinal networks, which control movement on the basis of sensory feedback of various types, including that from proprioceptive afferents. The computational models will continue to shed light on the central strategies and mechanisms of sensorimotor control and learning. This research topic demonstrated that computational modeling is playing a more and more prominent role in the studies of postural and movement control. With increasing ability to gather data from all levels of the neuromechanical sensorimotor systems, there is a compelling need for novel, creative modeling of new and existing data sets, because the more systematic means to extract knowledge and insights about neural computations of sensorimotor systems from these data is through computational modeling. While models should be based on experimental data and validated with experimental evidence, they should also be flexible to provide a conceptual framework for unifying diverse data sets, to generate new insights of neural mechanisms, to integrate new data sets into the general framework, to validate or refute hypotheses and to suggest new testable hypotheses for future experimental investigation. It is thus expected that neural and computational modeling of the sensorimotor system should create new opportunities for experimentalists and modelers to collaborate in a joint endeavor to advance our understanding of the neural mechanisms for postural and movement control. The editors would like to thank Professor Arthur Prochazka, who helped initially to set up this research topic, and all authors who contributed their articles to this research topic. Our appreciation also goes to the reviewers, who volunteered their time and effort to help achieve the goal of this research topic. We would also like to thank the staff members of editorial office of Frontiers in Computational Neuroscience for their expertise in the process of manuscript handling, publishing, and in bringing this ebook to the readers. The support from the Editor-in-Chief, Dr. Misha Tsodyks and Dr. Si Wu is crucial for this research topic to come to a successful conclusion. We are indebted to Dr. Si Li and Ms. Ting Xu, whose assistant is important for this ebook to become a reality. Finally, this work is supported in part by grants to Dr. Ning Lan from the Ministry of Science and Technology of China (2011CB013304), the Natural Science Foundation of China (No. 81271684, No. 61361160415, No. 81630050), and the Interdisciplinary Research Grant cross Engineering and Medicine by Shanghai Jiao Tong University (YG20148D09). Dr. Vincent Cheung is supported by startup funds from the Faculty of Medicine of The Chinese University of Hong Kong. Guest Associate Editors Ning Lan, Vincent Cheung, and Simon Gandevia

Book Neural and Computational Modeling of Movement Control

Download or read book Neural and Computational Modeling of Movement Control written by and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the study of sensorimotor systems, an important research goal has been to understand the way neural networks in the spinal cord and brain interact to control voluntary movement. Computational modeling has provided insight into the interaction between centrally generated commands, proprioceptive feedback signals and the biomechanical responses of the moving body. Research in this field is also driven by the need to improve and optimize rehabilitation after nervous system injury and to devise biomimetic methods of control in robotic devices. This research topic is focused on efforts dedicated to identify and model the neuromechanical control of movement. Neural networks in the brain and spinal cord are known to generate patterned activity that mediates coordinated activation of multiple muscles in both rhythmic and discrete movements, e.g. locomotion and reaching. Commands descending from the higher centres in the CNS modulate the activity of spinal networks, which control movement on the basis of sensory feedback of various types, including that from proprioceptive afferents. The computational models will continue to shed light on the central strategies and mechanisms of sensorimotor control and learning. This research topic demonstrated that computational modeling is playing a more and more prominent role in the studies of postural and movement control. With increasing ability to gather data from all levels of the neuromechanical sensorimotor systems, there is a compelling need for novel, creative modeling of new and existing data sets, because the more systematic means to extract knowledge and insights about neural computations of sensorimotor systems from these data is through computational modeling. While models should be based on experimental data and validated with experimental evidence, they should also be flexible to provide a conceptual framework for unifying diverse data sets, to generate new insights of neural mechanisms, to integrate new data sets into the general framework, to validate or refute hypotheses and to suggest new testable hypotheses for future experimental investigation. It is thus expected that neural and computational modeling of the sensorimotor system should create new opportunities for experimentalists and modelers to collaborate in a joint endeavor to advance our understanding of the neural mechanisms for postural and movement control. The editors would like to thank Professor Arthur Prochazka, who helped initially to set up this research topic, and all authors who contributed their articles to this research topic. Our appreciation also goes to the reviewers, who volunteered their time and effort to help achieve the goal of this research topic. We would also like to thank the staff members of editorial office of Frontiers in Computational Neuroscience for their expertise in the process of manuscript handling, publishing, and in bringing this ebook to the readers. The support from the Editor-in-Chief, Dr. Misha Tsodyks and Dr. Si Wu is crucial for this research topic to come to a successful conclusion. We are indebted to Dr. Si Li and Ms. Ting Xu, whose assistant is important for this ebook to become a reality. Finally, this work is supported in part by grants to Dr. Ning Lan from the Ministry of Science and Technology of China (2011CB013304), the Natural Science Foundation of China (No. 81271684, No. 61361160415, No. 81630050), and the Interdisciplinary Research Grant cross Engineering and Medicine by Shanghai Jiao Tong University (YG20148D09). Dr. Vincent Cheung is supported by startup funds from the Faculty of Medicine of The Chinese University of Hong Kong. Guest Associate Editors Ning Lan, Vincent Cheung, and Simon Gandevia.

Book Principles of Computational Modelling in Neuroscience

Download or read book Principles of Computational Modelling in Neuroscience written by David Sterratt and published by Cambridge University Press. This book was released on 2023-10-05 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.

Book Neuromechanical Modeling of Posture and Locomotion

Download or read book Neuromechanical Modeling of Posture and Locomotion written by Boris I. Prilutsky and published by Springer. This book was released on 2015-12-30 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuromechanics is a new, quickly growing field of neuroscience research that merges neurophysiology, biomechanics and motor control and aims at understanding living systems and their elements through interactions between their neural and mechanical dynamic properties. Although research in Neuromechanics is not limited by computational approaches, neuromechanical modeling is a powerful tool that allows for integration of massive knowledge gained in the past several decades in organization of motion related brain and spinal cord activity, various body sensors and reflex pathways, muscle mechanical and physiological properties and detailed quantitative morphology of musculoskeletal systems. Recent work in neuromechanical modeling has demonstrated advantages of such an integrative approach and led to discoveries of new emergent properties of neuromechanical systems. Neuromechanical Modeling of Posture and Locomotion will cover a wide range of topics from theoretical studies linking the organization of reflex pathways and central pattern generating circuits with morphology and mechanics of the musculoskeletal system (Burkholder; Nichols; Shevtsova et al.) to detailed neuromechanical models of postural and locomotor control (Bunderson; Edwards, Marking et al., Ting). Furthermore, uniquely diverse modeling approaches will be presented in the book including a theoretical dynamic analysis of locomotor phase transitions (Spardy and Rubin), a hybrid computational modeling that allows for in vivo interactions between parts of a living organism and a computer model (Edwards et al.), a physical neuromechanical model of the human locomotor system (Lewis), and others.

Book Human Robotics

    Book Details:
  • Author : Etienne Burdet
  • Publisher : MIT Press
  • Release : 2013-09-13
  • ISBN : 0262314827
  • Pages : 291 pages

Download or read book Human Robotics written by Etienne Burdet and published by MIT Press. This book was released on 2013-09-13 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: A synthesis of biomechanics and neural control that draws on recent advances in robotics to address control problems solved by the human sensorimotor system. This book proposes a transdisciplinary approach to investigating human motor control that synthesizes musculoskeletal biomechanics and neural control. The authors argue that this integrated approach—which uses the framework of robotics to understand sensorimotor control problems—offers a more complete and accurate description than either a purely neural computational approach or a purely biomechanical one. The authors offer an account of motor control in which explanatory models are based on experimental evidence using mathematical approaches reminiscent of physics. These computational models yield algorithms for motor control that may be used as tools to investigate or treat diseases of the sensorimotor system and to guide the development of algorithms and hardware that can be incorporated into products designed to assist with the tasks of daily living. The authors focus on the insights their approach offers in understanding how movement of the arm is controlled and how the control adapts to changing environments. The book begins with muscle mechanics and control, progresses in a logical manner to planning and behavior, and describes applications in neurorehabilitation and robotics. The material is self-contained, and accessible to researchers and professionals in a range of fields, including psychology, kinesiology, neurology, computer science, and robotics.

Book Computational and Robotic Models of the Hierarchical Organization of Behavior

Download or read book Computational and Robotic Models of the Hierarchical Organization of Behavior written by Gianluca Baldassarre and published by Springer Science & Business Media. This book was released on 2013-11-19 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Current robots and other artificial systems are typically able to accomplish only one single task. Overcoming this limitation requires the development of control architectures and learning algorithms that can support the acquisition and deployment of several different skills, which in turn seems to require a modular and hierarchical organization. In this way, different modules can acquire different skills without catastrophic interference, and higher-level components of the system can solve complex tasks by exploiting the skills encapsulated in the lower-level modules. While machine learning and robotics recognize the fundamental importance of the hierarchical organization of behavior for building robots that scale up to solve complex tasks, research in psychology and neuroscience shows increasing evidence that modularity and hierarchy are pivotal organization principles of behavior and of the brain. They might even lead to the cumulative acquisition of an ever-increasing number of skills, which seems to be a characteristic of mammals, and humans in particular. This book is a comprehensive overview of the state of the art on the modeling of the hierarchical organization of behavior in animals, and on its exploitation in robot controllers. The book perspective is highly interdisciplinary, featuring models belonging to all relevant areas, including machine learning, robotics, neural networks, and computational modeling in psychology and neuroscience. The book chapters review the authors' most recent contributions to the investigation of hierarchical behavior, and highlight the open questions and most promising research directions. As the contributing authors are among the pioneers carrying out fundamental work on this topic, the book covers the most important and topical issues in the field from a computationally informed, theoretically oriented perspective. The book will be of benefit to academic and industrial researchers and graduate students in related disciplines.

Book Progress in Motor Control

    Book Details:
  • Author : Michael J. Richardson
  • Publisher : Springer Science & Business Media
  • Release : 2013-01-09
  • ISBN : 1461454654
  • Pages : 205 pages

Download or read book Progress in Motor Control written by Michael J. Richardson and published by Springer Science & Business Media. This book was released on 2013-01-09 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is the most recent installment of the Progress in Motor Control series. It contains contributions based on presentations by invited speakers at the Progress in Motor Control VIII meeting held in Cincinnati, OH, USA in July, 2011. Progress in Motor Control is the official scientific meeting of the International Society of Motor Control (ISMC). The Progress in Motor Control VIII meeting, and consequently this volume, provide a broad perspective on the latest research on motor control in humans and other species.

Book Modularity in Motor Control  From Muscle Synergies to Cognitive Action Representation

Download or read book Modularity in Motor Control From Muscle Synergies to Cognitive Action Representation written by Andrea d'Avella and published by Frontiers Media SA. This book was released on 2016-04-21 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mastering a rich repertoire of motor behaviors, as humans and other animals do, is a surprising and still poorly understood outcome of evolution, development, and learning. Many degrees-of-freedom, non-linear dynamics, and sensory delays provide formidable challenges for controlling even simple actions. Modularity as a functional element, both structural and computational, of a control architecture might be the key organizational principle that the central nervous system employs for achieving versatility and adaptability in motor control. Recent investigations of muscle synergies, motor primitives, compositionality, basic action concepts, and related work in machine learning have contributed to advance, at different levels, our understanding of the modular architecture underlying rich motor behaviors. However, the existence and nature of the modules in the control architecture is far from settled. For instance, regularity and low-dimensionality in the motor output are often taken as an indication of modularity but could they simply be a byproduct of optimization and task constraints? Moreover, what are the relationships between modules at different levels, such as muscle synergies, kinematic invariants, and basic action concepts? One important reason for the new interest in understanding modularity in motor control from different viewpoints is the impressive development in cognitive robotics. In comparison to animals and humans, the motor skills of today’s best robots are limited and inflexible. However, robot technology is maturing to the point at which it can start approximating a reasonable spectrum of isolated perceptual, cognitive, and motor capabilities. These advances allow researchers to explore how these motor, sensory and cognitive functions might be integrated into meaningful architectures and to test their functional limits. Such systems provide a new test bed to explore different concepts of modularity and to address the interaction between motor and cognitive processes experimentally. Thus, the goal of this Research Topic is to review, compare, and debate theoretical and experimental investigations of the modular organization of the motor control system at different levels. By bringing together researchers seeking to understand the building blocks for coordinating many muscles, for planning endpoint and joint trajectories, and for representing motor and behavioral actions in memory we aim at promoting new interactions between often disconnected research areas and approaches and at providing a broad perspective on the idea of modularity in motor control. We welcome original research, methodological, theoretical, review, and perspective contributions from behavioral, system, and computational motor neuroscience research, cognitive psychology, and cognitive robotics.

Book From Neuron to Cognition via Computational Neuroscience

Download or read book From Neuron to Cognition via Computational Neuroscience written by Michael A. Arbib and published by MIT Press. This book was released on 2016-11-04 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, integrated, and accessible textbook presenting core neuroscientific topics from a computational perspective, tracing a path from cells and circuits to behavior and cognition. This textbook presents a wide range of subjects in neuroscience from a computational perspective. It offers a comprehensive, integrated introduction to core topics, using computational tools to trace a path from neurons and circuits to behavior and cognition. Moreover, the chapters show how computational neuroscience—methods for modeling the causal interactions underlying neural systems—complements empirical research in advancing the understanding of brain and behavior. The chapters—all by leaders in the field, and carefully integrated by the editors—cover such subjects as action and motor control; neuroplasticity, neuromodulation, and reinforcement learning; vision; and language—the core of human cognition. The book can be used for advanced undergraduate or graduate level courses. It presents all necessary background in neuroscience beyond basic facts about neurons and synapses and general ideas about the structure and function of the human brain. Students should be familiar with differential equations and probability theory, and be able to pick up the basics of programming in MATLAB and/or Python. Slides, exercises, and other ancillary materials are freely available online, and many of the models described in the chapters are documented in the brain operation database, BODB (which is also described in a book chapter). Contributors Michael A. Arbib, Joseph Ayers, James Bednar, Andrej Bicanski, James J. Bonaiuto, Nicolas Brunel, Jean-Marie Cabelguen, Carmen Canavier, Angelo Cangelosi, Richard P. Cooper, Carlos R. Cortes, Nathaniel Daw, Paul Dean, Peter Ford Dominey, Pierre Enel, Jean-Marc Fellous, Stefano Fusi, Wulfram Gerstner, Frank Grasso, Jacqueline A. Griego, Ziad M. Hafed, Michael E. Hasselmo, Auke Ijspeert, Stephanie Jones, Daniel Kersten, Jeremie Knuesel, Owen Lewis, William W. Lytton, Tomaso Poggio, John Porrill, Tony J. Prescott, John Rinzel, Edmund Rolls, Jonathan Rubin, Nicolas Schweighofer, Mohamed A. Sherif, Malle A. Tagamets, Paul F. M. J. Verschure, Nathan Vierling-Claasen, Xiao-Jing Wang, Christopher Williams, Ransom Winder, Alan L. Yuille

Book Neuro motor control and feed forward models of locomotion in humans

Download or read book Neuro motor control and feed forward models of locomotion in humans written by Marco Iosa and published by Frontiers Media SA. This book was released on 2015-07-29 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Locomotion involves many different muscles and the need of controlling several degrees of freedom. Despite the Central Nervous System can finely control the contraction of individual muscles, emerging evidences indicate that strategies for the reduction of the complexity of movement and for compensating the sensorimotor delays may be adopted. Experimental evidences in animal and lately human model led to the concept of a central pattern generator (CPG) which suggests that circuitry within the distal part of CNS, i.e. spinal cord, can generate the basic locomotor patterns, even in the absence of sensory information. Different studies pointed out the role of CPG in the control of locomotion as well as others investigated the neuroplasticity of CPG allowing for gait recovery after spinal cord lesion. Literature was also focused on muscle synergies, i.e. the combination of (locomotor) functional modules, implemented in neuronal networks of the spinal cord, generating specific motor output by imposing a specific timing structure and appropriate weightings to muscle activations. Despite the great interest that this approach generated in the last years in the Scientific Community, large areas of investigations remain available for further improvement (e.g. the influence of afferent feedback and environmental constrains) for both experimental and simulated models. However, also supraspinal structures are involved during locomotion, and it has been shown that they are responsible for initiating and modifying the features of this basic rhythm, for stabilising the upright walking, and for coordinating movements in a dynamic changing environment. Furthermore, specific damages into spinal and supraspinal structures result in specific alterations of human locomotion, as evident in subjects with brain injuries such as stroke, brain trauma, or people with cerebral palsy, in people with death of dopaminergic neurons in the substantia nigra due to Parkinson’s disease, or in subjects with cerebellar dysfunctions, such as patients with ataxia. The role of cerebellum during locomotion has been shown to be related to coordination and adaptation of movements. Cerebellum is the structure of CNS where are conceivably located the internal models, that are neural representations miming meaningful aspects of our body, such as input/output characteristics of sensorimotor system. Internal model control has been shown to be at the basis of motor strategies for compensating delays or lacks in sensorimotor feedbacks, and some aspects of locomotion need predictive internal control, especially for improving gait dynamic stability, for avoiding obstacles or when sensory feedback is altered or lacking. Furthermore, despite internal model concepts are widespread in neuroscience and neurocognitive science, neurorehabilitation paid far too little attention to the potential role of internal model control on gait recovery. Many important scientists have contributed to this Research Topic with original studies, computational studies, and review articles focused on neural circuits and internal models involved in the control of human locomotion, aiming at understanding the role played in control of locomotion of different neural circuits located at brain, cerebellum, and spinal cord levels.

Book The Computational Neurobiology of Reaching and Pointing

Download or read book The Computational Neurobiology of Reaching and Pointing written by Reza Shadmehr and published by MIT Press. This book was released on 2004-10-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the computational biology of reaching and pointing, with an emphasis on motor learning. Neuroscience involves the study of the nervous system, and its topics range from genetics to inferential reasoning. At its heart, however, lies a search for understanding how the environment affects the nervous system and how the nervous system, in turn, empowers us to interact with and alter our environment. This empowerment requires motor learning. The Computational Neurobiology of Reaching and Pointing addresses the neural mechanisms of one important form of motor learning. The authors integrate material from the computational, behavioral, and neural sciences of motor control that is not available in any other single source. The result is a unified, comprehensive model of reaching and pointing. The book is intended to be used as a text by graduate students in both neuroscience and bioengineering and as a reference source by experts in neuroscience, robotics, and other disciplines. The book begins with an overview of the evolution, anatomy, and physiology of the motor system, including the mechanisms for generating force and maintaining limb stability. The sections that follow, "Computing Locations and Displacements", "Skills, Adaptations, and Trajectories", and "Predictions, Decisions, and Flexibility", present a theory of sensorially guided reaching and pointing that evolves organically based on computational principles rather than a traditional structure-by-structure approach. The book also includes five appendixes that provide brief refreshers on fundamentals of biology, mathematics, physics, and neurophysiology, as well as a glossary of relevant terms. The authors have also made supplemental materials available on the Internet. These web documents provide source code for simulations, step-by-step derivations of certain mathematical formulations, and expanded explanations of some concepts.

Book Computational Neuroscience  Theoretical Insights into Brain Function

Download or read book Computational Neuroscience Theoretical Insights into Brain Function written by Paul Cisek and published by Elsevier. This book was released on 2007-11-14 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational neuroscience is a relatively new but rapidly expanding area of research which is becoming increasingly influential in shaping the way scientists think about the brain. Computational approaches have been applied at all levels of analysis, from detailed models of single-channel function, transmembrane currents, single-cell electrical activity, and neural signaling to broad theories of sensory perception, memory, and cognition. This book provides a snapshot of this exciting new field by bringing together chapters on a diversity of topics from some of its most important contributors. This includes chapters on neural coding in single cells, in small networks, and across the entire cerebral cortex, visual processing from the retina to object recognition, neural processing of auditory, vestibular, and electromagnetic stimuli, pattern generation, voluntary movement and posture, motor learning, decision-making and cognition, and algorithms for pattern recognition. Each chapter provides a bridge between a body of data on neural function and a mathematical approach used to interpret and explain that data. These contributions demonstrate how computational approaches have become an essential tool which is integral in many aspects of brain science, from the interpretation of data to the design of new experiments, and to the growth of our understanding of neural function.• Includes contributions by some of the most influential people in the field of computational neuroscience• Demonstrates how computational approaches are being used today to interpret experimental data• Covers a wide range of topics from single neurons, to neural systems, to abstract models of learning

Book Computational Modeling of Neuromuscular Control of Voluntary Single Joint Movement

Download or read book Computational Modeling of Neuromuscular Control of Voluntary Single Joint Movement written by Alex Krasner and published by . This book was released on 2014 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: While the neuromuscular components involved in moving human joints are well known, there is no unifying model describing how they accomplish it. The dynamics of each individual neuromuscular component, from the brain structures, including cerebral cortex and sub-cortical areas, to the spinal cord, to the contractual apparatus have been formulated previously, but they have not been thoroughly tested, nor integrated into a holistic model of movement. This thesis combined these formulations into a single brain-spinal cord-muscle (BSM) model that illustratesmotion planning by interactions between these brain components . Movement plans originating in the cerebral cortex are processed in the descending motor pathways: brainstem, cerebellum, and spinal circuitry. Execution is coordinated by activation of agonist and antagonist muscle groups, mostly with closed-loop feedback control. Here, I analyzed previously publishedneuromuscular formulations by simulations. I applied several methods for combining piecemeal models of individual components into a unified control system. Results with BSM produced physiologically realistic joint outputs showing new details, not seen in previous models. The BSM model can be useful for detailed analysis of any biological component involved with motion generation, and can help in understanding the underlying causes of motor impairments.

Book Fundamentals of Neural Network Modeling

Download or read book Fundamentals of Neural Network Modeling written by Randolph W. Parks and published by MIT Press. This book was released on 1998 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. Over the past few years, computer modeling has become more prevalent in the clinical sciences as an alternative to traditional symbol-processing models. This book provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. It is intended to make the neural network approach accessible to practicing neuropsychologists, psychologists, neurologists, and psychiatrists. It will also be a useful resource for computer scientists, mathematicians, and interdisciplinary cognitive neuroscientists. The editors (in their introduction) and contributors explain the basic concepts behind modeling and avoid the use of high-level mathematics. The book is divided into four parts. Part I provides an extensive but basic overview of neural network modeling, including its history, present, and future trends. It also includes chapters on attention, memory, and primate studies. Part II discusses neural network models of behavioral states such as alcohol dependence, learned helplessness, depression, and waking and sleeping. Part III presents neural network models of neuropsychological tests such as the Wisconsin Card Sorting Task, the Tower of Hanoi, and the Stroop Test. Finally, part IV describes the application of neural network models to dementia: models of acetycholine and memory, verbal fluency, Parkinsons disease, and Alzheimer's disease. Contributors J. Wesson Ashford, Rajendra D. Badgaiyan, Jean P. Banquet, Yves Burnod, Nelson Butters, John Cardoso, Agnes S. Chan, Jean-Pierre Changeux, Kerry L. Coburn, Jonathan D. Cohen, Laurent Cohen, Jose L. Contreras-Vidal, Antonio R. Damasio, Hanna Damasio, Stanislas Dehaene, Martha J. Farah, Joaquin M. Fuster, Philippe Gaussier, Angelika Gissler, Dylan G. Harwood, Michael E. Hasselmo, J, Allan Hobson, Sam Leven, Daniel S. Levine, Debra L. Long, Roderick K. Mahurin, Raymond L. Ownby, Randolph W. Parks, Michael I. Posner, David P. Salmon, David Servan-Schreiber, Chantal E. Stern, Jeffrey P. Sutton, Lynette J. Tippett, Daniel Tranel, Bradley Wyble

Book Motor Control

    Book Details:
  • Author : Frederic Danion, PhD
  • Publisher : Oxford University Press
  • Release : 2011
  • ISBN : 0195395271
  • Pages : 536 pages

Download or read book Motor Control written by Frederic Danion, PhD and published by Oxford University Press. This book was released on 2011 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motor control has established itself as an area of scientific research characterized by a multi-disciplinary approach. Scientists working in the area of control of voluntary movements come from different backgrounds including but not limited to physiology, physics, psychology, mathematics, neurology, physical therapy, computer science, robotics, and engineering. One of the factors slowing progress in the area has been the lack of communication among researchers representing all these disciplines. A major objective of the current book is to overcome this deficiency and to promote cooperation and mutual understanding among researchers addressing different aspects of the complex phenomenon of motor coordination. The book offers a collection of chapters written by the most prominent researchers in the field. Despite the variety of approaches and methods, all the chapters are united by a common goal: To understand how the central nervous system controls and coordinates natural voluntary movements. This book will be appreciated as a major reference by researchers working in all the subfields that form motor control. It can also be used as a supplementary reading book for graduate courses in such fields as kinesiology, physiology, biomechanics, psychology, robotics, and movement disorders.In one concise volume, Motor Control presents the diversity of the research performed to understand human movement. Deftly organized into 6 primary sections, the editors, Dr Frederic Danion and Dr Mark Latash, have invited the who's who of specialists to write on: MotorControl: Control of a Complex; Cortical Mechanisms of Motor Control; Lessons from Biomechanics; Lessons from Motor Learning and Using Tools; Lessons from Studies of Aging and MotorDisorders; and Lessons from RoboticsMotor Control will quickly become the go-to reference for researchers in this growing field. Researchers from mechanics and engineering to psychology and neurophysiology, as well as clinicians working in motor disorders and rehabilitation, will be equally interested in the pages contained herein.

Book Neurobiology of Motor Control

Download or read book Neurobiology of Motor Control written by Scott L. Hooper and published by John Wiley & Sons. This book was released on 2017-06-12 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: A multi-disciplinary look at the current state of knowledge regarding motor control and movement—from molecular biology to robotics The last two decades have seen a dramatic increase in the number of sophisticated tools and methodologies for exploring motor control and movement. Multi-unit recordings, molecular neurogenetics, computer simulation, and new scientific approaches for studying how muscles and body anatomy transform motor neuron activity into movement have helped revolutionize the field. Neurobiology of Motor Control brings together contributions from an interdisciplinary group of experts to provide a review of the current state of knowledge about the initiation and execution of movement, as well as the latest methods and tools for investigating them. The book ranges from the findings of basic scientists studying model organisms such as mollusks and Drosophila, to biomedical researchers investigating vertebrate motor production to neuroengineers working to develop robotic and smart prostheses technologies. Following foundational chapters on current molecular biological techniques, neuronal ensemble recording, and computer simulation, it explores a broad range of related topics, including the evolution of motor systems, directed targeted movements, plasticity and learning, and robotics. Explores motor control and movement in a wide variety of organisms, from simple invertebrates to human beings Offers concise summaries of motor control systems across a variety of animals and movement types Explores an array of tools and methodologies, including electrophysiological techniques, neurogenic and molecular techniques, large ensemble recordings, and computational methods Considers unresolved questions and how current scientific advances may be used to solve them going forward Written specifically to encourage interdisciplinary understanding and collaboration, and offering the most wide-ranging, timely, and comprehensive look at the science of motor control and movement currently available, Neurobiology of Motor Control is a must-read for all who study movement production and the neurobiological basis of movement—from molecular biologists to roboticists.

Book Computational Explorations in Cognitive Neuroscience

Download or read book Computational Explorations in Cognitive Neuroscience written by Randall C. O'Reilly and published by MIT Press. This book was released on 2000-08-28 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the computational cognitive neuroscience. The goal of computational cognitive neuroscience is to understand how the brain embodies the mind by using biologically based computational models comprising networks of neuronlike units. This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the field. The neural units in the simulations use equations based directly on the ion channels that govern the behavior of real neurons, and the neural networks incorporate anatomical and physiological properties of the neocortex. Thus the text provides the student with knowledge of the basic biology of the brain as well as the computational skills needed to simulate large-scale cognitive phenomena. The text consists of two parts. The first part covers basic neural computation mechanisms: individual neurons, neural networks, and learning mechanisms. The second part covers large-scale brain area organization and cognitive phenomena: perception and attention, memory, language, and higher-level cognition. The second part is relatively self-contained and can be used separately for mechanistically oriented cognitive neuroscience courses. Integrated throughout the text are more than forty different simulation models, many of them full-scale research-grade models, with friendly interfaces and accompanying exercises. The simulation software (PDP++, available for all major platforms) and simulations can be downloaded free of charge from the Web. Exercise solutions are available, and the text includes full information on the software.