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eBook - PDF
Principles of Neural Coding
Rodrigo Quian Quiroga, Stefano Panzeri, Rodrigo Quian Quiroga, Stefano Panzeri
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- 663 pages
- English
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eBook - PDF
Principles of Neural Coding
Rodrigo Quian Quiroga, Stefano Panzeri, Rodrigo Quian Quiroga, Stefano Panzeri
Book details
Table of contents
Citations
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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Table of contents
- Front Cover
- Contents
- Preface
- Editors
- Contributors
- Chapter 1 - Physiological Foundations of Neural Signals
- Chapter 2 - Biophysics of Extracellular Spikes
- Chapter 3 - Local Field Potentials: Biophysical Origin and Analysis
- Chapter 4 - Spike Sorting
- Chapter 5 - Spike-Train Analysis
- Chapter 6 - Synchronization Measures
- Chapter 7 - Role of Correlations in Population Coding
- Chapter 8 - Decoding and Information Theory in Neuroscience
- Chapter 9 - Neural Coding of Visual Objects
- Chapter 10 - Coding in the Auditory System
- Chapter 11 - Coding in the Whisker Sensory System
- Chapter 12 - Neural Coding in the Olfactory System
- Chapter 13 - Coding across Sensory Modalities: Integrating the Dynamic Face with the Voice
- Chapter 14 - Population Coding by Place Cells and Grid Cells
- Chapter 15 - Coding of Movement Intentions
- Chapter 16 - Neural Coding of Short-Term Memory
- Chapter 17 - Role of Temporal Spike Patterns in Neural Codes
- Chapter 18 - Adaptation and Sensory Coding
- Chapter 19 - Sparse and Explicit Neural Coding
- Chapter 20 - Information Coding by Cortical Populations
- Chapter 21 - Information Content of Local Field Potentials: Experiments and Models
- Chapter 22 - Principles of Neural Coding from EEG Signals
- Chapter 23 - Gamma-Band Synchronization and Information Transmission
- Chapter 24 - Decoding Information from fMRI Signals
- Chapter 25 - Dynamics of Neural Networks
- Chapter 26 - Learning and Coding in Neural Networks
- Chapter 27 - Ising Models for Inferring Network Structure from Spike Data
- Chapter 28 - Vocal Learning with Inverse Models
- Chapter 29 - Computational Models of Visual Object Recognition
- Chapter 30 - Coding in Neuromorphic VLSIÂ Networks
- Chapter 31 - Open-Source Software for Studying Neural Codes
- Back Cover
Citation styles for Principles of Neural Coding
APA 6 Citation
[author missing]. (2013). Principles of Neural Coding (1st ed.). CRC Press. Retrieved from https://www.perlego.com/book/1628104/principles-of-neural-coding-pdf (Original work published 2013)
Chicago Citation
[author missing]. (2013) 2013. Principles of Neural Coding. 1st ed. CRC Press. https://www.perlego.com/book/1628104/principles-of-neural-coding-pdf.
Harvard Citation
[author missing] (2013) Principles of Neural Coding. 1st edn. CRC Press. Available at: https://www.perlego.com/book/1628104/principles-of-neural-coding-pdf (Accessed: 14 October 2022).
MLA 7 Citation
[author missing]. Principles of Neural Coding. 1st ed. CRC Press, 2013. Web. 14 Oct. 2022.