1st Edition

Introduction to Dynamic Modeling of Neuro-Sensory Systems

By Robert B. Northrop Copyright 2001
    488 Pages 1 B/W Illustrations
    by CRC Press

    Although neural modeling has a long history, most of the texts available on the subject are quite limited in scope, dealing primarily with the simulation of large-scale biological neural networks applicable to describing brain function. Introduction to Dynamic Modeling of Neuro-Sensory Systems presents the mathematical tools and methods that can describe and predict the dynamic behavior of single neurons, small assemblies of neurons devoted to a single tasks, as well as larger sensory arrays and their underlying neuropile.

    Focusing on small and medium-sized biological neural networks, the author pays particular attention to visual feature extraction, especially the compound eye visual system and the vertebrate retina. For computational efficiency, the treatment avoids molecular details of neuron function and uses the locus approach for medium-scale modeling of arrays. Rather than requiring readers to learn a dedicated simulation program, the author uses the general, nonlinear ordinary differential equation solver Simnonä for all examples and exercises.

    There is both art and science in setting up a computational model that can be validated from existing neurophysiological data. With clear prose, more than 200 figures and photographs, and unique focus, Introduction to Dynamic Modeling of Neuro-Sensory Systems develops the science, nurtures the art, and builds the foundation for more advanced work in neuroscience and the rapidly emerging field of neuroengineering.

    INTRODUCTION TO NEURONS
    Introduction
    Types of Neurons
    Electrical Properties of Nerve Membrane
    Synapses: epsps and ipsps
    Models for the Nerve Action Potential
    Chapter Summary
    Problems
    SELECTED EXAMPLES OF SENSORY RECEPTORS AND SMALL RECEPTOR ARRAYS
    Introduction
    The Generalized Receptor
    Chemoreceptors
    Mechanoreceptors
    Magnetoreceptors
    Electroreceptors
    Gravity Sensors of the Cockroach: Arenivaga sp.
    The Dipteran Haltere
    The Simple "Eye" of Mytilus
    Chapter Summary
    Problems
    ELECTRONIC MODELS OF NEURONS: A HISTORICAL PERSPECTIVE
    Introduction
    Necessary Attributes of Small- and Medium-Scale Neural Models
    Electronic Neural Models (Neuromimes)
    Discussion
    SIMULATION OF THE BEHAVIOR OF SMALL ASSEMBLIES OF NEURONS
    Introduction Simulation of Synaptic Loci
    Dendrites and Local Response Loci
    Integral and Relaxation Pulse Frequency Modulation Models for the Spike Generator Locus (SGL)
    Theoretical Models for Neural Signal Conditioning
    Recurrent Inhibition and Spike Train Pattern Generation
    Chapter Summary
    Problems
    LARGE ARRAYS OF INTERACTING RECEPTORS: THE COMPOUND EYE
    Introduction
    Anatomy of the Arthropod Compound Eye Visual System
    Spatial Resolution of the Compound Eye
    Lateral Inhibition in the Eye of Limulus
    Feature Extraction by the Compound Eye System
    Chapter Summary
    Problems
    LARGE ARRAYS OF INTERACTING RECEPTORS: THE VERTEBRATE RETINA
    Introduction
    Review of the Anatomy and Physiology of the Vertebrate Retina
    Feature Extraction by the Frog's Retina
    Feature Extraction by Other Vertebrate Retinas
    Chapter Summary
    THEORETICAL MODELS OF INFORMATION PROCESSING AND FEATURE EXTRACTION IN VISUAL SENSORY ARRAYS
    Introduction
    Models for Neural Spatial Filters and Feature Extraction in Retinas
    Models for Neural Matched Filters in Vision
    Models for Parallel Processing: Artificial Neural Networks
    Chapter Summary
    Problems
    CHARACTERIZATION OF NEURO-SENSORY SYSTEMS
    Review of Characterization and Identification Means for Linear Systems
    Parsimonious Models for Neural Connectivity Based on Time Series Analysis of Spike Sequences
    Triggered Correlation Applied to the Auditory System
    The White Noise Method of Characterizing Nonlinear Systems
    Chapter Summary
    SOFTWARE FOR SIMULATION OF NEURAL SYSTEMS
    Introduction
    XNBC v8
    Neural Network Simulation Language, or NSL
    Neuron
    GENESIS
    Other Neural Simulation Programs
    Neural Modeling with General, Nonlinear System Simulation Software
    Conclusion
    BIBLIOGRAPHY AND REFERENCES
    APPENDICES
    INDEX

    Biography

    Robert B. Northrop