Modeling in the Neurosciences : From Biological Systems to Neuromimetic Robotics.

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 ""in...

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Bibliographic Details
Main Author:	Reeke, G. N.
Corporate Author:	Taylor & Francis
Other Authors:	Poznanski, R. R., Lindsay, K. A., Rosenberg, J. R., Sporns, O.
Format:	eBook
Language:	English
Language Notes:	English.
Published:	Hoboken : Taylor and Francis, 2004.
Edition:	2nd ed.
Subjects:	Neurons > Computer simulation. Neurons > Mathematical models. Neural networks (Neurobiology) Computational neuroscience. Biological models. Cells. Nervous system. Life sciences. Mathematical models. Physical sciences. Anatomy. Neurons. Neurosciences. Computer simulation. Digital computer simulation. Models, Biological Cells Nervous System Biological Science Disciplines Computing Methodologies Models, Theoretical Information Science Natural Science Disciplines Anatomy Investigative Techniques. Disciplines and Occupations. Analytical, Diagnostic and Therapeutic Techniques and Equipment. Neurons Neurosciences Models, Neurological Computer Simulation Animal Structures Neurones > Simulation par ordinateur. Neurones > Modèles mathématiques. Réseaux neuronaux (Neurobiologie) Neurosciences informatiques. Modèles biologiques. Cellules. Système nerveux. Sciences de la vie. Modèles mathématiques. Sciences physiques. Anatomie. Neurones. Simulation par ordinateur. biological sciences. mathematical models. physical sciences. anatomy. simulation. Physical sciences Nervous system Mathematical models Life sciences Digital computer simulation Computer simulation Biological models Computational neuroscience Neurons > Computer simulation Neurons > Mathematical models Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Front cover; Contents; Preface to the Second Edition; Contributors; Foreword; About the Editors; 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 SodiumSpike9 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 Current17 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 Devices24 Toward Neural Robotics: From Synthetic Models to Neuromimetic Implementations; Bibliography; Index; Back cover.