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Mathematics for neuroscientists /
This book presents a comprehensive introduction to mathematical and computational methods used in neuroscience to describe and model neural components of the brain from ion channels to single neurons, neural networks and their relation to behavior. The book contains more than 200 figures generated u...
| Clasificación: | Libro Electrónico |
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| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London, United Kingdom :
Academic Press is an imprint of Elsevier,
2017.
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| Edición: | Second edition. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- 1. Introduction; 2. The Passive Isopotential Cell; 3. Differential Equations; 4. The Active Isopotential Cell; 5. The Quasi-Active Isopotential Cell; 6. The Passive Cable; 7. Fourier Series and Transforms; 8. The Passive Dendritic Tree; 9. The Active Dendritic Tree; 10. Extracellular Potential; 11. Reduced Single Neuron Models; 12. Probability and Random Variables; 13. Synaptic Transmission and Quantal Release; 14. Neuronal Calcium Signaling; 15. Energy, Metabolism and Neuro-Vascular Coupling; 16. The Singular Value Decomposition and Applications; 17. Quantification of Spike Train Variability; 18. Stochastic Processes; 19. Membrane Noise; 20. Power and Cross Spectra; 21. Natural Light Signals and Phototransduction; 22. Firing Rate Codes and Early Vision; 23. Models of Simple and Complex Cells; 24. Motion Detection; 25. Stochastic Estimation Theory; 26. Reverse-Correlation and Spike Train Decoding; 27. Signal Detection Theory; 28. Relating Neuronal Responses and Psychophysics; 29. Population Codes; 30. Neuronal Networks