Del i serien Springer Series in Computational Neuroscience

Neuromechanical Modeling of Posture and Locomotion

Häftad, Engelska, 2019

2 109 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

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.

Produktinformation

Utgivningsdatum2019-03-29
Mått155 x 235 x 21 mm
Vikt575 g
FormatHäftad
SpråkEngelska
SerieSpringer Series in Computational Neuroscience
Antal sidor368
FörlagSpringer-Verlag New York Inc.
ISBN9781493980086

Tillhör följande kategorier

Boris Prilutsky received his BS degrees in physical education and applied mathematics/ mechanics from Central Institute of Physical Culture in Moscow, Russia and Moscow Institute of Electronic Engineering, respectively, and a PhD in animal movement biomechanics and physiology from Latvian Research Institute of Traumatology and Orthopedics. He is currently an associate professor in the School of Applied Physiology and director of Biomechanics and Motor Control laboratory at the Georgia Institute of Technology and an adjunct associate professor in the Division of Physical Therapy at Emory University School of Medicine. His research interests are biomechanics and neural control of normal and pathological movement. Donald H. Edwards received a B.S. degree in electrical engineering from the Massachusetts Institute of Technology and a Ph.D. in neurobiology from Yale University. He studied sensori-motor integration as a postdoctoral research associate with Donald Kennedyat Stanford University and with Brian Mulloney at University of California, Davis. He joined the faculty at Georgia State University as Assistant Professor of Biology and is currently Regents’ Professor of Neuroscience. His research interests include sensori-motor integration, neuromechanics and the neural control of behavior.

Preface.- Better science through predictive modeling: Numerical tools for understanding neuromechanical interactions.- A neuromechanical model of spinal control of locomotion.- Neural regulation of limb mechanics: Insights from the organization of proprioceptive circuits.- Model-based approaches to understanding musculoskeletal filtering of neural signals.- Modeling the organization of spinal cord neural circuits controlling two-joint muscles.- Muscles: non-linear transformers of motor neuron activity.- Why is neuromechanical modeling of balance and locomotion so hard?.- Neuromusculoskeletal modeling for the adaptive control of posture during locomotion.- Model-based interpretations of experimental data related to the control of balance during stance and gait in humans.- Computing motion dependent afferent activity during cat locomotion using a forward dynamics musculoskeletal model.- Modeling and optimality analysis of pectoral fin locomotion.- Control of cat walking and paw-shakeby a multifunctional central pattern generator.