Download or read book Adaptive Internal Models in Neuroscience written by Mireille E. Broucke and published by . This book was released on 2022-05-31 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the open questions in neuroscience is the function of the cerebellum, a major brain region involved in regulation of the motor systems, speech, emotion, and other cognitive functions of the body. In this monograph the author makes and tests a hypothesis that the primary function of the cerebellum is disturbance rejection of exogenous reference and disturbance signals. In achieving this goal, the author provides a brief historical overview of computational theories of cerebellar function and of the relevant parts of control theory in the area of regulator theory, and then presents a chronological review of subjects in control theory related to the hypothesis. The author begins with classical regulator theory and highlight some aspects that are not suited to the modeling of the cerebellum. Then adaptive control theory is reviewed in terms of error models. To test the hypothesis on cerebellar function, the author applies adaptive internal model designs to several motor systems regulated by the cerebellum. These include the slow eye movement systems: the vestibulo-ocular reflex, gaze holding, smooth pursuit, and the optokinetic system. Finally, discrete time behaviors regulated by the cerebellum are investigated. In all, this monograph provides a unifying framework to explain how the cerebellum can contribute to so many different systems in the body. This monograph is an important comprehensive study of modeling the cerebellum using control theory techniques. It will be of interest to neuroscientists and control theorists working on understanding the function of the human brain.

Download or read book Adaptive Internal Models for Motor Control and Visual Prediction written by Wolfram Schenck and published by Logos Verlag Berlin GmbH. This book was released on 2008 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, computational models of adaptive motor control and visuomotor coordination are explored and developed. These models relate to hypotheses on how sensorimotor processing in biological organisms might be organized at an abstract level; furthermore, these models and their specific implementations offer solutions for technical problems in the domain of adaptive robotics. For this reason, both biological and technical aspects are addressed. On the one hand, this thesis focuses on the learning of so-called internal models (Miall et al., 1993; Kawato, 1999): "forward models", which predict the sensory consequences of the agent''s own actions, and "inverse models", which act like motor controllers and generate motor commands. In this area, new strategies and algorithms for learning are suggested and tested on both simulated and real-world robot setups. This work contributes to the understanding of the "building blocks" of integrated sensorimotor processing. On the other hand, this thesis suggests complex models of sensorimotor coordination: In a study on the grasping to extrafoveal targets with a robot arm, it is explored how forward and inverse models may interact, and a second study addresses the question how visual perception of space might arise from the learning of sensorimotor relationships. The theoretical part of the thesis starts with a close view on sensorimotor processing. The cognitivist approach and the embodied approach to sensorimotor processing are contrasted with each other, providing evidence from psychological and neurophysiological studies in favor of the latter. It is outlined how the application of robots fits into the embodied approach as research method. Furthermore, internal models are defined in a formal way, and an overview of their role in models of perception and cognition is provided, with a special emphasis on anticipation and predictive forward models. Afterwards, a thorough overview of internal models in adaptive motor control (covering both kinematics and dynamics) and a novel learning strategy for kinematic control problems ("learning by averaging") are presented. The experimental work comprises four different studies. First, a detailed comparison study of various motor learning strategies for kinematic problems is presented. The performance of "feedback error learning" (Kawato et al., 1987), "distal supervised learning" (Jordan and Rumelhart, 1992), and "direct inverse modeling" (e.g., Kuperstein, 1987) is directly compared on several learning tasks from the domain of eye and arm control (on simulated setups). Moreover, an improved version of direct inverse modeling on the basis of abstract recurrent networks and learning by averaging are included in the comparison. The second study is dedicated to the learning of a visual forward model for a robot camera head. This forward model predicts the visual consequences of camera movements for all pixels of the camera image. The presented learning algorithm is able to overcome the two main difficulties of visual prediction: first, the high dimensionality of the input and output space, and second, the need to detect which part of the visual output is non-predictable. To demonstrate the robustness of the presented learning algorithm, the work is not carried out on plain camera images, but on distorted "retinal images" with a decreasing resolution towards the corners. In the third experimental chapter, a model for grasping to extrafoveal (non-fixated) targets is presented. It is implemented on a robot setup, consisting of a camera head and a robot arm. This model is based on the premotor theory of attention (Rizzolatti et al., 1994) and adds one specific hypothesis: Attention shifts caused by saccade programming imply a prediction of the retinal foveal images after the saccade. For this purpose, the visual forward model from the preceding study is used. Based on this model, several grasping modes are compared; the obtained results are qualitatively congruent with the performance that can be expected from human subjects. The fourth study is based on the theory that visual perception of space and shape is based on an internal simulation process which relies on forward models (Moeller, 1999). This theory is tested by synthetic modeling in the task domain of block pushing with a robot arm.

Download or read book Encyclopedia of Neuroscience written by Marc D. Binder and published by Springer. This book was released on 2008-10-13 with total page 4398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 5000-page masterwork is literally the last word on the topic and will be an essential resource for many. Unique in its breadth and detail, this encyclopedia offers a comprehensive and highly readable guide to a complex and fast-expanding field. The five-volume reference work gathers more than 10,000 entries, including in-depth essays by internationally known experts, and short keynotes explaining essential terms and phrases. In addition, expert editors contribute detailed introductory chapters to each of 43 topic fields ranging from the fundamentals of neuroscience to fascinating developments in the new, inter-disciplinary fields of Computational Neuroscience and Neurophilosophy. Some 1,000 multi-color illustrations enhance and expand the writings.

Download or read book The Nature of Explanation written by K. J. W. Craik and published by CUP Archive. This book was released on 1967-10 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: In his only complete work of any length, Kenneth Craik considers thought as a term for the conscious working of a highly complex machine.

Download or read book Active Inference written by Thomas Parr and published by MIT Press. This book was released on 2022-03-29 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive treatment of active inference, an integrative perspective on brain, cognition, and behavior used across multiple disciplines. Active inference is a way of understanding sentient behavior—a theory that characterizes perception, planning, and action in terms of probabilistic inference. Developed by theoretical neuroscientist Karl Friston over years of groundbreaking research, active inference provides an integrated perspective on brain, cognition, and behavior that is increasingly used across multiple disciplines including neuroscience, psychology, and philosophy. Active inference puts the action into perception. This book offers the first comprehensive treatment of active inference, covering theory, applications, and cognitive domains. Active inference is a “first principles” approach to understanding behavior and the brain, framed in terms of a single imperative to minimize free energy. The book emphasizes the implications of the free energy principle for understanding how the brain works. It first introduces active inference both conceptually and formally, contextualizing it within current theories of cognition. It then provides specific examples of computational models that use active inference to explain such cognitive phenomena as perception, attention, memory, and planning.

Download or read book From Motor Learning to Interaction Learning in Robots written by Olivier Sigaud and published by Springer Science & Business Media. This book was released on 2010-02-04 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: From an engineering standpoint, the increasing complexity of robotic systems and the increasing demand for more autonomously learning robots, has become essential. This book is largely based on the successful workshop “From motor to interaction learning in robots” held at the IEEE/RSJ International Conference on Intelligent Robot Systems. The major aim of the book is to give students interested the topics described above a chance to get started faster and researchers a helpful compandium.

Download or read book Human and Robot Hands written by Matteo Bianchi and published by Springer. This book was released on 2016-02-24 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book looks at the common problems both human and robotic hands encounter when controlling the large number of joints, actuators and sensors required to efficiently perform motor tasks such as object exploration, manipulation and grasping. The authors adopt an integrated approach to explore the control of the hand based on sensorimotor synergies that can be applied in both neuroscience and robotics. Hand synergies are based on goal-directed, combined muscle and kinematic activation leading to a reduction of the dimensionality of the motor and sensory space, presenting a highly effective solution for the fast and simplified design of artificial systems. Presented in two parts, the first part, Neuroscience, provides the theoretical and experimental foundations to describe the synergistic organization of the human hand. The second part, Robotics, Models and Sensing Tools, exploits the framework of hand synergies to better control and design robotic hands and haptic/sensing systems/tools, using a reduced number of control inputs/sensors, with the goal of pushing their effectiveness close to the natural one. Human and Robot Hands provides a valuable reference for students, researchers and designers who are interested in the study and design of the artificial hand.

Download or read book Stevens Handbook of Experimental Psychology and Cognitive Neuroscience Sensation Perception and Attention written by and published by John Wiley & Sons. This book was released on 2018-03-13 with total page 992 pages. Available in PDF, EPUB and Kindle. Book excerpt: II. Sensation, Perception & Attention: John Serences (Volume Editor) (Topics covered include taste; visual object recognition; touch; depth perception; motor control; perceptual learning; the interface theory of perception; vestibular, proprioceptive, and haptic contributions to spatial orientation; olfaction; audition; time perception; attention; perception and interactive technology; music perception; multisensory integration; motion perception; vision; perceptual rhythms; perceptual organization; color vision; perception for action; visual search; visual cognition/working memory.)

Download or read book Encyclopedia of Neuroscience Volume 1 written by Larry R. Squire and published by Academic Press. This book was released on 2009-06-12 with total page 12505 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of the Neuroscience explores all areas of the discipline in its focused entries on a wide variety of topics in neurology, neurosurgery, psychiatry and other related areas of neuroscience. Each article is written by an expert in that specific domain and peer reviewed by the advisory board before acceptance into the encyclopedia. Each article contains a glossary, introduction, a reference section, and cross-references to other related encyclopedia articles. Written at a level suitable for university undergraduates, the breadth and depth of coverage will appeal beyond undergraduates to professionals and academics in related fields.

Download or read book The Adaptive Brain I written by and published by Elsevier. This book was released on 1987-01-01 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Adaptive Brain I

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 2016-11-11 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

Download or read book Towards Autonomous Robotic Systems written by Ashutosh Natraj and published by Springer. This book was released on 2014-06-27 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th Conference on Advances in Autonomous Robotics, TAROS 2013, held in Oxford, UK, in August 2013. The 36 revised full papers presented together with 25 extended abstracts were carefully reviewed and selected from 89 submissions. The papers cover various topics such as artificial intelligence, bio-inspired and aerial robotics, computer vision, control, humanoid and robotic arm, swarm robotics, verification and ethics.

Download or read book Neural Plasticity for Rich and Uncertain Robotic Information Streams written by Andrea Soltoggio and published by Frontiers Media SA. This book was released on 2016-10-31 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: Models of adaptation and neural plasticity are often demonstrated in robotic scenarios with heavily pre-processed and regulated information streams to provide learning algorithms with appropriate, well timed, and meaningful data to match the assumptions of learning rules. On the contrary, natural scenarios are often rich of raw, asynchronous, overlapping and uncertain inputs and outputs whose relationships and meaning are progressively acquired, disambiguated, and used for further learning. Therefore, recent research efforts focus on neural embodied systems that rely less on well timed and pre-processed inputs, but rather extract autonomously relationships and features in time and space. In particular, realistic and more complete models of plasticity must account for delayed rewards, noisy and ambiguous data, emerging and novel input features during online learning. Such approaches model the progressive acquisition of knowledge into neural systems through experience in environments that may be affected by ambiguities, uncertain signals, delays, or novel features.

Download or read book Ethics of Artificial Intelligence written by S. Matthew Liao and published by Oxford University Press, USA. This book was released on 2020 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: Should a self-driving car prioritize the lives of the passengers over the lives of pedestrians? Should we as a society develop autonomous weapon systems that are capable of identifying and attacking a target without human intervention? What happens when AIs become smarter and more capable than us? Could they have greater than human moral status? Can we prevent superintelligent AIs from harming us or causing our extinction? At a critical time in this fast-moving debate, thirty leading academics and researchers at the forefront of AI technology development come together to explore these existential questions, including Aaron James (UC Irvine), Allan Dafoe (Oxford), Andrea Loreggia (Padova), Andrew Critch (UC Berkeley), Azim Shariff (Univ. .

Download or read book Computational Theories and Their Implementation in the Brain written by Lucia M. Vaina and published by Oxford University Press. This book was released on 2017 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the late 1960s and early 1970s David Marr produced three astonishing papers in which he gave a detailed account of how the fine structure and known cell types of the cerebellum, hippocampus and neocortex perform the functions that they do. Marr went on to become one of the main founders of Computational Neuroscience. In his classic work 'Vision' he distinguished between the computational, algorithmic, and implementational levels, and the three early theories concerned implementation. However, they were produced when Neuroscience was in its infancy. Now that so much more is known, it is timely to revisit these early theories to see to what extent they are still valid and what needs to be altered to produce viable theories that stand up to current evidence. This book brings together some of the most distinguished scientists in their fields to evaluate Marr's legacy. After a general introduction there are three chapters on the cerebellum, three on the hippocampus and two on the neocortex. The book ends with an appreciation of the life of David Marr by Lucia Vaina.

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 570 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

Download or read book Predictive Mechanisms of the Cerebello Cerebral Networks written by Mario U. Manto and published by Frontiers Media SA. This book was released on 2020-01-24 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: