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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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Gabbiani, Fabrizio (Autor), Cox, Steven J. (Steven James), 1960- (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London, United Kingdom : Academic Press is an imprint of Elsevier, 2017.
Edición:Second edition.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Gabbiani, Fabrizio,  |e author. 
245 1 0 |a Mathematics for neuroscientists /  |c Fabrizio Gabbiani, Steven J. Cox. 
250 |a Second edition. 
264 1 |a London, United Kingdom :  |b Academic Press is an imprint of Elsevier,  |c 2017. 
300 |a 1 online resource :  |b illustrations (some color) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
588 0 |a Online resource; title from PDF title page (ScienceDirect, viewed March 3, 2017). 
588 0 |a Print version record. 
505 0 |a 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 
520 |a 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 using Matlab code available to the student and scholar. Mathematical concepts are introduced hand in hand with neuroscience, emphasizing the connection between experimental results and theory. 
650 0 |a Computational neuroscience. 
650 0 |a Computational biology. 
650 0 |a Neurosciences. 
650 2 |a Computational Biology  |0 (DNLM)D019295 
650 2 |a Neurosciences  |0 (DNLM)D009488 
650 6 |a Neurosciences informatiques.  |0 (CaQQLa)201-0331109 
650 6 |a Bio-informatique.  |0 (CaQQLa)201-0313075 
650 6 |a Neurosciences.  |0 (CaQQLa)201-0010244 
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650 7 |a Computational neuroscience  |2 fast  |0 (OCoLC)fst00872004 
650 7 |a Neurosciences  |2 fast  |0 (OCoLC)fst01036509 
655 0 |a Electronic books. 
655 4 |a Internet Resources. 
700 1 |a Cox, Steven J.  |q (Steven James),  |d 1960-  |e author. 
776 0 8 |c Original  |z 012801895X  |z 9780128018958  |w (OCoLC)959875855 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780128018958  |z Texto completo