Computational Neuroscience: Theoretical Insights into Brain Function :Theoretical Insights into Brain Function ( Volume 165 )

Publication subTitle :Theoretical Insights into Brain Function

Publication series :Volume 165

Author: Cisek   Paul;Drew   Trevor;Kalaska   John  

Publisher: Elsevier Science‎

Publication year: 2007

E-ISBN: 9780080555027

P-ISBN(Paperback): 9780444528230

P-ISBN(Hardback):  9780444528230

Subject: Q189 Neurobiology;Q811.4 biological information theory;R74 Neurology and Psychiatry;TP3 Computers

Language: ENG

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Description

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 neuro

Chapter

Cover

pp.:  1 – 12

List of Contributors

pp.:  6 – 10

Preface

pp.:  10 – 16

Contents

pp.:  12 – 6

Chapter 3. The dynamics of visual responses in the primary visual cortex

pp.:  36 – 48

Chapter 4. A quantitative theory of immediate visual recognition

pp.:  48 – 72

Chapter 5. Attention in hierarchical models of object recognition

pp.:  72 – 94

Chapter 6. Towards a unified theory of neocortex: laminar cortical circuits for vision and cognition

pp.:  94 – 120

Chapter 7. Real-time neural coding of memory

pp.:  120 – 138

Chapter 8. Beyond timing in the auditory brainstem: intensity coding in the avian cochlear nucleus angularis

pp.:  138 – 150

Chapter 9. Neural strategies for optimal processing of sensory signals

pp.:  150 – 170

Chapter 10. Coordinate transformations and sensory integration in the detection of spatial orientation and self-motion: from models to experiments

pp.:  170 – 196

Chapter 11. Sensorimotor optimization in higher dimensions

pp.:  196 – 208

Chapter 12. How tightly tuned are network parameters? Insight from computational and experimental studies in small rhythmic motor networks

pp.:  208 – 216

Chapter 13. Spatial organization and state-dependent mechanisms for respiratory rhythm and pattern generation

pp.:  216 – 236

Chapter 14. Modeling a vertebrate motor system: pattern generation, steering and control of body orientation

pp.:  236 – 250

Chapter 15. Modeling the mammalian locomotor CPG: insights from mistakes and perturbations

pp.:  250 – 270

Chapter 16. The neuromechanical tuning hypothesis

pp.:  270 – 282

Chapter 17. Threshold position control and the principle of minimal interaction in motor actions

pp.:  282 – 298

Chapter 18. Modeling sensorimotor control of human upright stance

pp.:  298 – 314

Chapter 19. Dimensional reduction in sensorimotor systems: a framework for understanding muscle coordination of posture

pp.:  314 – 338

Chapter 20. Primitives, premotor drives, and pattern generation: a combined computational and neuroethological perspective

pp.:  338 – 362

Chapter 21. A multi-level approach to understanding upper limb function

pp.:  362 – 378

Chapter 22. How is somatosensory information used to adapt to changes in the mechanical environment?

pp.:  378 – 388

Chapter 23. Trial-by-trial motor adaptation: a window into elemental neural computation

pp.:  388 – 398

Chapter 24. Towards a computational neuropsychology of action

pp.:  398 – 410

Chapter 25. Motor control in a meta-network with attractor dynamics

pp.:  410 – 426

Chapter 26. Computing movement geometry: a step in sensory-motor transformations

pp.:  426 – 440

Chapter 27. Dynamics systems vs. optimal control „ a unifying view

pp.:  440 – 462

Chapter 28. The place of ’codes’ in nonlinear neurodynamics

pp.:  462 – 478

Chapter 29. From a representation of behavior to the concept of cognitive syntax: a theoretical framework

pp.:  478 – 490

Chapter 30. A parallel framework for interactive behavior

pp.:  490 – 508

Chapter 31. Statistical models for neural encoding, decoding, and optimal stimulus design

pp.:  508 – 524

Chapter 32. Probabilistic population codes and the exponential family of distributions

pp.:  524 – 536

Chapter 33. On the challenge of learning complex functions

pp.:  536 – 550

Chapter 34. To recognize shapes, first learn to generate images

pp.:  550 – 572

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