Modeling in the Neurosciences From Biological Systems to Neuromimetic Robotics 2nd Edition by G N Reeke, Poznanski, Lindsay, Rosenberg, Sporns ISBN 0415328683 9780415328685

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Product details: 

ISBN 10: 0415328683 

ISBN 13: 9780415328685

Author: G. N. Reeke, R.R. Poznanski, K. A. Lindsay, J.R. Rosenberg, O. Sporns

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: 

1: Introduction to Modeling in the Neurosciences
2: Patterns of Genetic Interactions: Analysis of mRNA Levels from cDNA Microarrays
3: Calcium Signaling in Dendritic Spines
4: Physiological and Statistical Approaches to Modeling of Synaptic Responses
5: Natural Variability in the Geometry of Dendritic Branching Patterns
6: Multicylinder Models for Synaptic and Gap-Junctional Integration
7: Voltage Transients in Branching Multipolar Neurons with Tapering Dendrites and Sodium Channels
8: Analytical Solutions of the Frankenhaeuser-Huxley Equations Modified for Dendritic Backpropagation of a Single Sodium Spike
9: Inverse Problems for Some Cable Models of Dendrites
10: Equivalent Cables – Analysis and Construction
11: 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
12: Simulation Analyses of Retinal Cell Responses
13: Modeling Intracellular Calcium: Diffusion, Dynamics, and Domains
14: Ephaptic Interactions Between Neurons
15: Cortical Pyramidal Cells
16: Semi-Quantitative Theory of Bistable Dendrites with Potential-Dependent Facilitation of Inward Current
17: Bifurcation Analysis of the Hodgkin-Huxley Equations
18: Highly Efficient Propagation of Random Impulse Trains Across Unmyelinated Axonal Branch Points: Modifications by Periaxonal K+ Accumulation and Sodium Channel Kinetics
19: Dendritic Integration in a Two-Neuron Recurrent Excitatory Network Model
20: Spike-Train Analysis for Neural Systems
21: The Poetics of Tremor
22: Principles and Methods in the Analysis of Brain Networks
23: The Darwin Brain-Based Automata: Synthetic Neural Models and Real-World Devices
24: Toward Neural Robotics: From Synthetic Models to Neuromimetic Implementations

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G N Reeke,Poznanski,Lindsay,Rosenberg,Sporns,Modeling