مکانیک نظری شبکه‌های عصبی بیولوژیکی

Theoretical Mechanics of Biological Neural Networks presents an extensive and coherent discusson and formulation of the generation and integration of neuroelectric signals in single neurons. The approach relates computer simulation programs for neurons of arbitrary complexity to fundamental gating processes of transmembrance ionic fluxes of synapses of excitable membranes. Listings of representative computer programs simulating arbitrary neurons, and local and composite neural networks are included. * Develops a theory of dynamic similarity for characterising the firing rate sensitivites of neurons in terms of their characteristic anatomical and physiological parameters. * Presents the sequential configuration theory - a theoretical presentation of coordinated firing patterns in entire neural populations. * Presents the outlines of mechanics for multiple interacting networks in composite systems. Content: Front Matter , Page iii Copyright , Page iv Dedication , Page v Preface , Pages ix-xii Chapter 1 - Introduction to a Theoretical Mechanics of Neural Networks , Pages 1-7 Chapter 2 - Introduction to the Mechanics of Neuroelectric Signalling , Pages 11-28 Chapter 3 - Physical Foundations of Neuroelectrical Signalling: Transmembrane Ionic Balances and Fluxes , Pages 29-43 Chapter 4 - The Membrane Equation and its Equivalent Circuit as the Central Governing Equation for Neuroelectric Signals , Pages 45-58 Chapter 5 - The Membrane Equation in Space: The Mechanics of Neurons with Dendrites , Pages 59-84 Chapter 6 - The Membrane Equation in Time: The Generation of Synaptic and Action Potentials , Pages 85-108 Chapter 7 - Computational Representation of Neuroelectric Signalling , Pages 109-140 Chapter 8 - An Overview of the Dynamic Similarity Approach to Neuronal Firing Levels , Pages 143-152 Chapter 9 - Parametric Characterization of Neuronal Firing: General Mathematical Formulation , Pages 153-166 Chapter 10 - Parametric Characterization of Neuronal Firing with Spatially Distributed Input , Pages 167-177 Chapter 11 - Universal Firing Rate Transfer Curve for Temporally Regular Input , Pages 179-189 Chapter 12 - Universal Firing Rate Transfer Curve for Randomly Temporally Irregular Input , Pages 191-201 Chapter 13 - Introduction to Coordinated Firing Patterns in Neural Networks , Pages 205-210 Chapter 14 - The Sequential Configuration Model for Firing Patterns in Neural Networks , Pages 211-234 Chapter 15 - Properties of Unorganized Activity in Recurrently Connected Networks , Pages 235-249 Chapter 16 - Memory Capacity in Recurrently Connected Networks , Pages 251-272 Chapter 17 - Toward a Mechanics of Composite Neural Networks and Synaptic Junctions , Pages 275-288 Chapter 18 - A Theory of Representation and Embedding of Memory Traces in Hippocampal Networks , Pages 289-300 Chapter 19 - Composite Cortical Networks as Systems of Multimodal Oscillators , Pages 301-319 Chapter 20 - Contextual Overview of Organization in Cortical Networks , Pages 321-336 Chapter 21 - Broad Principles of Systemic Operations in Nervous Systems , Pages 337-349 Afterword , Pages 351-358 Appendix , Pages 359-373 INDEX , Pages 375-377 NEURAL NETWORKS: FOUNDATIONS TO APPLICATIONS , Page 379 Presents a discussion and formulation of the generation and integration of neuroelectric signals in single neurons. This work develops a theory of dynamic similarity for characterising the firing rate sensitivites of neurons in terms of their characteristic anatomical and physiological parameters. It also presents sequential configuration theory.