Computational Neuroscience: Theoretical Insights into Brain Function

by Cisek; Drew; Kalaska

• ISBN13: 9780444528230
• ISBN10: 0444528237
• eBook ISBN(s): 9780080555027, 9780444528230
• Edition: 1st
• Format: Hardcover
• Copyright: 2007-11-14
• Publisher: Elsevier Science
• More Book Details
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Summary

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

Table of Contents

The neuronal transfer function: contributions from voltage and time-dependent mechanisms

A simple growth model constructs critical avalanche networks

The dynamics of visual responses in the primary visual cortex

A quantitative theory of immediate visual recognition

Attention in hierarchical models of object recognition

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

Real-time neural coding of memory

Beyond timing in the auditory brainstem: intensity in the avian cochlear nucleus angularis

Neural strategies for optimal processing of sensory signals

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

Sensorimotor optimization in higher dimensions

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

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

Modeling a vertebrate motor system pattern generation, steering and control of body orientation

Modeling the mammalian locomotor CPG: insights from mistakes and perturbations

The neuromechanical tuning hypothesis

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

Modelling sensorimotor control of human upright stance

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

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

A multi-level approach to understanding upper limb function

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

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

Towards a computational neuropsychology of action

Motor control in a meta-network with attractor dynamics

Computing movement geometry a step in sensory-motor transformations

Dynamics systems versus optimal control a unifying view

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