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portada control of arm movement in space: neurophysiological and computational approaches
Type
Physical Book
Illustrated by
Publisher
Author
Year
2011
Language
English
Pages
338
Format
Paperback
Dimensions
24.4x17x1.9 cm
Weight
0.56 kg.
ISBN
3642772374
ISBN13
9783642772375
Categories

control of arm movement in space: neurophysiological and computational approaches

Roberto Caminiti (Illustrated by) · Paul B. Johnson (Illustrated by) · Ives Burnod (Illustrated by) · Springer · Paperback

control of arm movement in space: neurophysiological and computational approaches - Caminiti, Roberto ; Johnson, Paul B. ; Burnod, Ives

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Synopsis "control of arm movement in space: neurophysiological and computational approaches"

The primate forearm is capable of an infinite variety of motions which are performed with power, speed, and finesse. How the brain generates and controls such movements has intrigued and baffled students of motor control for centuries. However, progress toward the better understanding of arm movement control is now being made by researchers in several disciplines. This volume brings together contributions from the fields of neuroanatomy, neurophysiology, behavior, and computational neuroscience. Each chapter presents recent data from current research topics relevant to the problem of controlling arm and hand movements. The multidisciplinary approach adopted in this volume reflects the current trend to combine the methodologies of neuroscience with those of engineering. In this sense, special emphasis has been given to computational developments which have their basis in recent experimental results. Correlations between behavioral motor variables and neural activity in various brain regions, the neural mechanisms of reaching and manipulation control and their underlying visuomotor transformation, and the internal neuronal representation of motor space as seen through population codes, are the main topics treated at both physiological and computational level. . We hope that this volume will help both physiologists to better understand the theoretical bases underlying the neural control of movement, and students of neural networks to adopt more biologically-oriented approaches in their development of new computational strategies.

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