Modeling in the Neurosciences: From Biological Systems to Neuromimetic Robotics
Features
Summary
Computational models of neural networks have proven insufficient to accurately model brain function, mainly as a result of simplifications that ignore the physical reality of neuronal structure in favor of mathematically tractable algorithms and rules. Even the more biologically based "integrate and fire" and "compartmental" styles of modeling suffer from oversimplification in the former case and excessive discretization in the second. This book introduces an integrative approach to modeling neurons and neuronal circuits that retains the integrity of the biological units at all hierarchical levels.
With contributions from more than 40 renowned experts, Modeling in the Neurosciences, Second Edition is essential for those interested in constructing more structured and integrative models with greater biological insight. Focusing on new mathematical and computer models, techniques, and methods, this book represents a cohesive and comprehensive treatment of various aspects of the neurosciences from the molecular to the network level. Many state-of-the-art examples illustrate how mathematical and computer modeling can contribute to the understanding of mechanisms and systems in the neurosciences. Each chapter also includes suggestions of possible refinements for future modeling in this rapidly changing and expanding field.
This book will benefit and inspire the advanced modeler, and will give the beginner sufficient confidence to model a wide selection of neuronal systems at the molecular, cellular, and network levels.
Table of Contents
PREFACE
CONTRIBUTORS
FOREWORD
INTRODUCTION TO MODELING IN THE NEUROSCIENCES
George N. Reeke
PATTERNS OF GENETIC INTERACTIONS: ANALYSIS OF MRNA LEVELS FROM CDNA MICROARRAYS
Larry S. Liebovitch, Lina A. Shehadeh, andd Viktor K. Jirsa
CALCIUM SIGNALING IN DENDRITIC SPINES
William R. Holmes
PHYSIOLOGICAL AND STATISTICAL APPROACHES TO MODELING OF SYNAPTIC RESPONSES
Parag G. Patil, Mike West, Howard V. Wheal, and Dennis A. Turner
NATURAL VARIABILITY IN THE GEOMETRY OF DENDRITIC BRANCHING PATTERNS
Jaap van Pelt and Harry B.M. Uylings
MULTICYLINDER MODELS FOR SYNAPTIC AND GAP-JUNCTIONAL INTEGRATION
Jonathan D. Evans
VOLTAGE TRANSIENTS IN BRANCHING MULTIPOLAR NEURONS WITH TAPERING DENDRITES AND SODIUM CHANNELS
Lloyd L. Glenn and Jeffrey R. Knisley
ANALYTICAL SOLUTIONS OF THE FRANKENHAEUSER-HUXLEY EQUATIONS MODIFIED FOR DENDRITIC BACKPROPAGATION OF A SINGLE SODIUM SPIKE
Roman R. Poznanski
INVERSE PROBLEMS FOR SOME CABLE MODELS OF DENDRITES
Jonathan Bell
EQUIVALENT CABLES-ANALYSIS AND CONSTRUCTION
Kenneth A. Lindsay, Jay R. Rosenberg, and Gayle Tucker
THE REPRESENTATION OF THREE-DIMENSIONAL DENDRITIC STRUCTURE BY A ONE-DIMENSIONAL MODEL-THE CONVENTIONAL CABLE EQUATION AS THE FIRST MEMBER OF A HIERARCHY OF EQUATIONS
Kenneth A. Lindsay, Jay R. Rosenberg, and Gayle Tucker
SIMULATION ANALYSES OF RETINAL CELL RESPONSES
Yoshimi Kamiyama, Akito Ishihara, Toshihiro Aoyama, and Shiro Usui
MODELING INTRACELLULAR CALCIUM: DIFFUSION, DYNAMICS, AND DOMAINS
Gregory D. Smith
EPHAPTIC INTERACTIONS BETWEEN NEURONS
Robert Costalat and Bruno Delord
CORTICAL PYRAMIDAL CELLS
Roger D. Orpwood
SEMI-QUANTITATIVE THEORY OF BISTABLE DENDRITES WITH POTENTIAL-DEPENDENT FACILITATION OF INWARD CURRENT
Aron Gutman, Armantas Baginskas, Jorn Hounsgaard, Natasha Svirskiene, and Gytis Svirskis
BIFURCATION ANALYSIS OF THE HODGKIN-HUXLEY EQUATIONS
Shunsuke Sato, Hidekazu Fukai, Taishin Nomura, and Shinji Doi
HIGHLY EFFICIENT PROPAGATION OF RANDOM IMPULSE TRAINS ACROSS UNMYELINATED AXONAL BRANCH POINTS: MODIFICATIONS BY PERIAXONAL K+ ACCUMULATION AND SODIUM CHANNEL KINETICS
Mel D. Goldfinger
DENDRITIC INTEGRATION IN A TWO-NEURON RECURRENT EXCITATORY NETWORK MODEL
Roman R. Poznanski
SPIKE-TRAIN ANALYSIS FOR NEURAL SYSTEMS
David M. Halliday
THE POETICS OF TREMOR
G.P. Moore and Helen M. Bronte-Stewart
PRINCIPLES AND METHODS IN THE ANALYSIS OF BRAIN NETWORKS
Olaf Sporns
THE DARWIN BRAIN-BASED AUTOMATA: SYNTHETIC NEURAL MODELS AND REAL-WORLD DEVICES
Jeffrey L. Krichmar and George N. Reeke
TOWARD NEURAL ROBOTICS: FROM SYNTHETIC MODELS TO NEUROMIMETIC IMPLEMENTATIONS
Olaf Sporns
BIBLIOGRAPHY
INDEX
Editorial Reviews
"The more we learn about the brain, the more we are convinced that understanding its incomputability will be a key to unlocking its functions. Neuroscience is turning a corner, and this book is helping to usher in a new era. The Second Edition is essential reading for those interested in contemporary approaches to neural modeling."
-Paul Bach-y-Rita, M.D., Professor of Rehabilitation Medicine and Biomedical Engineering, University of Wisconsin, USA
"The brain is an integrative organ of adjustment from gene networks to neuronal networks. The vast complexity involved requires mathematical modeling. The Second Edition advances such an integrative approach, and is undoubtedly a mathematical tour de force. This book will radically change our perception of theoretical and computational neuroscience."
-Roman M. Borisyuk, D.Sc., Professor of Computational Neuroscience, Centre for Theoretical and Computational Neuroscience, University of Plymouth, UK
"Physiologically realistic and integrative models of the brain are the only way forward to lift us clear of the jungle of detail about the brain. The essence of brain function dynamics that they embody will serve as the fundamental fulcrum around which new details (parameters) can be added and tested across scale. This book exemplifies a realistic way forward for an explicit 'integrative neuroscience'."
-Evian Gordon, Ph.D., CEO, The Brain Resource Company, and Scientific Chair (and Founding Director), The Brain Dynamic Centre, Westmead Hospital, Australia
