Single neuron computation /

This book contains twenty-two original contributions that provide a comprehensive overview of computational approaches to understanding a single neuron structure. The focus on cellular-level processes is twofold. From a computational neuroscience perspective, a thorough understanding of the informat...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: McKenna, Thomas M., Davis, Joel L., 1942-, Zornetzer, Steven F.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boston : Academic Press, �1992.
Colección:Neural networks, foundations to applications.
Temas:
Neural networks (Computer science)
Neural computers.
Neural Conduction > physiology
Neural Networks, Computer
Neurons > physiology
Neurons > ultrastructure
R�eseaux neuronaux (Informatique)
Ordinateurs neuronaux.
COMPUTERS > General.
Neural computers
Inteligencia artificial.
Artificial intelligence
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover; Single Neuron Computation; Copyright Page; Table of Contents; Contributors; Preface; PART I: COMPUTATION IN DENDRITES AND SPINES; Chapter 1. Electrotonic Models of Neuronal Dendrites and Single Neuron Computation; I. Introduction; II. Estimating the Electrotonic Structure of a Cell; III. The Dynamic Range of Computational Possibilities Exhibited by Neurons; IV. Synaptic Modification in Dendritic Spines; V. Summary; Acknowledgments; References; Chapter 2. Canonical Neurons and Their Computational Organization; I. Historical Background for the Complex Neuron
  • II. Development of the Computational Representation of the Complex NeuronIII. Strategies for Neuronal Modeling; IV. The Concept of the Canonical Neuron; V. Hierarchical Organization of Canonical Neurons in the Olfactory System; VI. The Cortical Pyramidal Neuron; Acknowledgments; References; Chapter 3. Computational Models of Hippocampal Neurons; I. Neuromorphometry; II. Electrotonic Structure; III. Computer Simulations; IV. Methods and Results; V. Summary and Conclusions; Acknowledgment; References; Chapter 4. Hebbian Computations in Hippocampal Dendrites and Spines; I. Introduction
  • II. Nodes and NeuronsIII. Voltage Gradients in Dendrites and Spines; IV. Spatial Representation of Electrotonic Structure; V. Voltage-Dependent Synaptic Modification; VI. Self-Organization and Pattern Association; VII. Summary and Conclusions; Acknowledgments; References; Chapter 5. Synaptic Integration by Electro-Diffusion in Dendritic Spines; I. Introduction; II. Cable Model Predictions; III. Limitations of the Cable Model; IV. Electro-Diffusion Model Predictions; V. The Cable Model for Electro-Diffusion; VI. Discussion; Acknowledgments; References
  • Chapter 6. Dendritic Morphology, Inward Rectification, and the Functional Properties of Neostriatal NeuronsI. Introduction; II. Firing Pattern of Neostriatal Spiny Projection Neurons; III. Distribution of Synaptic Inputs on the Spiny Projection Neuron; IV. A Model of the Spiny Neuron; V. Input Resistance and Electrotonic Length of the Passive Model; VI. Effect of Fast Anomalous Rectification on Input Resistance and Time Constant; VII. If the Time Constant Is Not Constant, the Length Constant Is Not Either; VIII. Synaptic Integration in the Spiny Neuron
  • IX. Dendritic Spines and Synaptic StrengthX. Effect of Fast Anomalous Rectification on Synaptic Integration; XI. Implications for Neostriatal Function; Acknowledgments; References; Chapter 7. Analog and Digital Processing in Single Nerve Cells: Dendritic Integration and Axonal Propagation; I. Introduction; II. Methods; III. Results; IV. Discussion; Acknowledgment; References; Chapter 8. Functions of Very Distal Dendrites: Experimental and Computational Studies of Layer I Synapses on Neocortical Pyramidal Cells; I. The Significance of Cortical Layer I

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