Modeling in the Neurosciences

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