Catálogo de publicaciones - libros
Tutorials in Mathematical Biosciences I: Mathematical Neuroscience
Alla Borisyuk Avner Friedman Bard Ermentrout David Terman
Resumen/Descripción – provisto por la editorial
No disponible.
Palabras clave – provistas por la editorial
Mathematical and Computational Biology; Ordinary Differential Equations; Partial Differential Equations; Computational Mathematics and Numerical Analysis; Neurobiology; Computer Appl. in Life Sciences
Disponibilidad
Institución detectada | Año de publicación | Navegá | Descargá | Solicitá |
---|---|---|---|---|
No detectada | 2005 | SpringerLink |
Información
Tipo de recurso:
libros
ISBN impreso
978-3-540-23858-4
ISBN electrónico
978-3-540-31544-5
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
2005
Información sobre derechos de publicación
© Springer-Verlag Berlin Heidelberg 2005
Cobertura temática
Tabla de contenidos
Introduction to Neurons
Avner Friedman
1. The Structure of Cells 2. Nerve Cells 3. Electrical Circuits and the Hodgkin-Huxley Model 4. The Cable Equation References
Pp. 1-20
An Introduction to Dynamical Systems and Neuronal Dynamics
David Terman
1. Introduction 2. One Dimensional Equations 2.1. The Geometric Approach 2.2. Bifurcations 2.3. Bistability and Hysteresis 3. Two Dimensional Systems 3.1. The Phase Plane 3.2. An Example 3.3. Oscillations 3.4. Local Bifurcations 3.5. Global Bifurcations 3.6. Geometric Singular Perturbation Theory 4. Single Neurons 4.1. Some Biology 4.2. The Hodgkin-Huxley Equations 4.3. Reduced Models 4.4. Bursting Oscillations 4.5. Traveling Wave Solutions 5. Two Mutually Coupled Cells 5.1. Introduction 5.2. Synaptic Coupling 5.3. Geometric Approach 5.4. Synchrony with Excitatory Synapses 5.5. Desynchrony with Inhibitory Synapses 6. Activity Patterns in the Basal Ganglia 6.1. Introduction 6.2. The Basal Ganglia 6.3. The Model 6.4. Activity Patterns 6.5. Concluding Remarks References
Pp. 21-68
Neural Oscillators
Bard Ermentrout
1. Introduction 2. How Does Rhythmicity Arise 3. Phase-Resetting and Coupling Through Maps 4. Doublets, Delays, and More Maps 5. Averaging and Phase Models 5.1. Local Arrays 6. Neural Networks 6.1. Slow Synapses 6.2. Analysis of the Reduced Model 6.3. Spatial Models References
Pp. 69-106
Physiology and Mathematical Modeling of the Auditory System
Alla Borisyuk
1. Introduction 1.1. Auditory System at a Glance 1.2. Sound Characteristics 2. Peripheral Auditory System 2.1. Outer Ear 2.2. Middle Ear 2.3. Inner Ear. Cochlea. Hair Cells. 2.4. Mathematical Modeling of the Peripheral Auditory System 3. Auditory Nerve (AN) 3.1. AN Structure 3.2. Response Properties 3.3. How Is AN Activity Used by Brain? 3.4. Modeling of the Auditory Nerve 4. Cochlear Nuclei 4.1. Basic Features of the CN Structure 4.2. Innervation by the Auditory Nerve Fibers 4.3. Main CN Output Targets 4.4. Classifications of Cells in the CN 4.5. Properties of Main Cell Types 4.6. Modeling of the Cochlear Nuclei 5. Superior Olive. Sound Localization, Jeffress Model 5.1. Medial Nucleus of the Trapezoid Body (MNTB) 5.2. Lateral Superior Olivary Nucleus (LSO) 5.3. Medial Superior Olivary Nucleus (MSO) 5.4. Sound Localization. Coincidence Detector Model 6. Midbrain 6.1. Cellular Organization and Physiology of Mammalian IC 6.2. Modeling of the IPD Sensitivity in the Inferior Colliculus 7. Thalamus and Cortex References
Pp. 107-168