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Mathematics for Neuroscientists de Fabrizio Gabbiani

Mathematics for Neuroscientists

Autor Fabrizio Gabbiani, Steven James Cox
en Limba Engleză Hardback – 26 feb 2017
Mathematics for Neuroscientists, Second Edition, 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.


  • Fully revised material and corrected text
  • Additional chapters on extracellular potentials, motion detection and neurovascular coupling
  • Revised selection of exercises with solutions
  • More than 200 Matlab scripts reproducing the figures as well as a selection of equivalent Python scripts
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Specificații

ISBN-13: 9780128018958
ISBN-10: 012801895X
Pagini: 628
Dimensiuni: 216 x 276 x 42 mm
Greutate: 1.73 kg
Ediția:2
Editura: ELSEVIER SCIENCE

Public țintă

Graduate and post graduate students in neuroscience and psychology looking for an introduction to mathematical methods in neuroscience; researchers in neuroscience and psychology looking for a quick reference for mathematical methods; and students in applied mathematics, physical sciences, engineering who want an introduction to neuroscience in a mathematical context.

Cuprins

1. Introduction2. The Passive Isopotential Cell3. Differential Equations4. The Active Isopotential Cell5. The Quasi-Active Isopotential Cell6. The Passive Cable7. Fourier Series and Transforms8. The Passive Dendritic Tree9. The Active Dendritic Tree10. Extracellular Potential11. Reduced Single Neuron Models12. Probability and Random Variables13. Synaptic Transmission and Quantal Release14. Neuronal Calcium SignalingNeuronal Calcium Signaling15. Neurovascular Coupling, the BOLD Signal and MRI16. The Singular Value Decomposition and ApplicationsThe Singular Value Decomposition and Applications17. Quantification of Spike Train Variability18. Stochastic Processes19. Membrane NoiseMembrane Noise20. Power and Cross-Spectra21. Natural Light Signals and Phototransduction22. Firing Rate Codes and Early Vision23. Models of Simple and Complex Cells24. Models of Motion Detection25. Stochastic Estimation Theory26. Reverse-Correlation and Spike Train Decoding27. Signal Detection Theory28. Relating Neuronal Responses and Psychophysics29. Population CodesPopulation Codes30. Neuronal Networks31. Solutions to Exercises

Recenzii

"This is a big book in more than one sense. It has a large page format measuring about 20cm x 27cm making it easy to open up and take in large swathes of text, equations, and figures. More importantly, it covers a very wide range of mathematical methodologies relevant to neuroscience. ...I would highly recommend this book to those with an interest in computational neuroscience who wish to delve more deeply into the biophysics underlying cell-based dynamics and computations, especially if they are interested in flexing their mathematical muscles." --MathSciNet
Amazon Editorial Reviews for First Edition:"I really think this book is very, very important. This is precisely what has been missing from the field and is badly needed. " --Dr. Kevin Franks, research fellow, Richard Axel's laboratory Columbia University, NYC
"The idea of presenting sufficient maths to understand the theoretical neuroscience, alongside the neuroscience itself, is appealing. The inclusion of Matlab code for all examples and computational figures is an excellent idea. " --David Corney, research fellow, Institute of Ophthalmology, University College London