Principles of Neural Coding
eBook - PDF

Principles of Neural Coding

  1. 663 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Principles of Neural Coding

About this book

Understanding how populations of neurons encode information is the challenge faced by researchers in the field of neural coding. Focusing on the many mysteries and marvels of the mind has prompted a prominent team of experts in the field to put their heads together and fire up a book on the subject. Simply titled Principles of Neural Coding, this b

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Yes, you can access Principles of Neural Coding by Rodrigo Quian Quiroga, Stefano Panzeri, Rodrigo Quian Quiroga,Stefano Panzeri in PDF and/or ePUB format, as well as other popular books in Medicine & Biotechnology in Medicine. We have over one million books available in our catalogue for you to explore.

Information

Publisher
CRC Press
Year
2013
Print ISBN
9781439853306
eBook ISBN
9781439853313
Edition
1
Topic
Medicine
Subtopic
Biotechnology in Medicine

Table of contents

  1. Front Cover
  2. Contents
  3. Preface
  4. Editors
  5. Contributors
  6. Chapter 1 - Physiological Foundations of Neural Signals
  7. Chapter 2 - Biophysics of Extracellular Spikes
  8. Chapter 3 - Local Field Potentials: Biophysical Origin and Analysis
  9. Chapter 4 - Spike Sorting
  10. Chapter 5 - Spike-Train Analysis
  11. Chapter 6 - Synchronization Measures
  12. Chapter 7 - Role of Correlations in Population Coding
  13. Chapter 8 - Decoding and Information Theory in Neuroscience
  14. Chapter 9 - Neural Coding of Visual Objects
  15. Chapter 10 - Coding in the Auditory System
  16. Chapter 11 - Coding in the Whisker Sensory System
  17. Chapter 12 - Neural Coding in the Olfactory System
  18. Chapter 13 - Coding across Sensory Modalities: Integrating the Dynamic Face with the Voice
  19. Chapter 14 - Population Coding by Place Cells and Grid Cells
  20. Chapter 15 - Coding of Movement Intentions
  21. Chapter 16 - Neural Coding of Short-Term Memory
  22. Chapter 17 - Role of Temporal Spike Patterns in Neural Codes
  23. Chapter 18 - Adaptation and Sensory Coding
  24. Chapter 19 - Sparse and Explicit Neural Coding
  25. Chapter 20 - Information Coding by Cortical Populations
  26. Chapter 21 - Information Content of Local Field Potentials: Experiments and Models
  27. Chapter 22 - Principles of Neural Coding from EEG Signals
  28. Chapter 23 - Gamma-Band Synchronization and Information Transmission
  29. Chapter 24 - Decoding Information from fMRI Signals
  30. Chapter 25 - Dynamics of Neural Networks
  31. Chapter 26 - Learning and Coding in Neural Networks
  32. Chapter 27 - Ising Models for Inferring Network Structure from Spike Data
  33. Chapter 28 - Vocal Learning with Inverse Models
  34. Chapter 29 - Computational Models of Visual Object Recognition
  35. Chapter 30 - Coding in Neuromorphic VLSI Networks
  36. Chapter 31 - Open-Source Software for Studying Neural Codes
  37. Back Cover