1st Edition

Principles of Neural Coding

Edited By Rodrigo Quian Quiroga, Stefano Panzeri Copyright 2013
    664 Pages 34 Color & 179 B/W Illustrations
    by CRC Press

    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 book covers the complexities of this discipline. It centers on some of the major developments in this area and presents a complete assessment of how neurons in the brain encode information. The book collaborators contribute various chapters that describe results in different systems (visual, auditory, somatosensory perception, etc.) and different species (monkeys, rats, humans, etc). Concentrating on the recording and analysis of the firing of single and multiple neurons, and the analysis and recording of other integrative measures of network activity and network states—such as local field potentials or current source densities—is the basis of the introductory chapters.

    • Provides a comprehensive and interdisciplinary approach
    • Describes topics of interest to a wide range of researchers

    The book then moves forward with the description of the principles of neural coding for different functions and in different species and concludes with theoretical and modeling works describing how information processing functions are implemented. The text not only contains the most important experimental findings, but gives an overview of the main methodological aspects for studying neural coding. In addition, the book describes alternative approaches based on simulations with neural networks and in silico modeling in this highly interdisciplinary topic. It can serve as an important reference to students and professionals.

    Section I Methods

    Physiological Foundations of Neural Signals

    Kevin Whittingstall and Nikos K. Logothetis

    Biophysics of Extracellular Spikes

    Costas A. Anastassiou, György Buzsáki, and Christof Koch

    Local Field Potentials: Biophysical Origin and Analysis

    Gaute T. Einevoll, Henrik Lindén, Tom Tetzlaff, Szymon Łęski,

    and Klas H. Pettersen

    Spike Sorting

    Juan Martínez and Rodrigo Quian Quiroga

    Spike-Train Analysis

    Inés Samengo, Daniel Elijah, and Marcelo A. Montemurro

    Synchronization Measures

    Thomas Kreuz

    Role of Correlations in Population Coding

    Peter E. Latham and Yasser Roudi

    Decoding and Information Theory in Neuroscience

    Rodrigo Quian Quiroga and Stefano Panzeri

    Section II Experimental Results

    Neural Coding of Visual Objects

    Charles E. Connor

    Coding in the Auditory System

    Jan Schnupp

    Coding in the Whisker Sensory System

    Mathew E. Diamond and Ehsan Arabzadeh

    Neural Coding in the Olfactory System

    Ron A. Jortner

    Coding across Sensory Modalities: Integrating the Dynamic Face with the Voice

    Chandramouli Chandrasekaran and Asif A. Ghazanfar

    Population Coding by Place Cells and Grid Cells

    Jill K. Leutgeb, Emily A. Mankin, and Stefan Leutgeb

    Coding of Movement Intentions

    Hansjörg Scherberger, Rodrigo Quian Quiroga, and Richard A. Andersen

    Neural Coding of Short-Term Memory

    Stefanie Liebe and Gregor Rainer

    Role of Temporal Spike Patterns in Neural Codes

    Rasmus S. Petersen

    Adaptation and Sensory Coding

    Miguel Maravall

    Sparse and Explicit Neural Coding

    Peter Földiák

    Information Coding by Cortical Populations

    Kenneth D. Harris

    Information Content of Local Field Potentials: Experiments and Models

    Alberto Mazzoni, Nikos K. Logothetis, and Stefano Panzeri

    Principles of Neural Coding from EEG Signals

    Fernando H. Lopes da Silva

    Gamma-Band Synchronization and Information Transmission

    Martin Vinck, Thilo Womelsdorf, and Pascal Fries

    Decoding Information from fMRI Signals

    Jakob Heinzle and John-Dylan Haynes

    Section III Theoretical and In Silico Approaches

    Dynamics of Neural Networks

    Nicolas Brunel

    Learning and Coding in Neural Networks

    Timothée Masquelier and Gustavo Deco

    Ising Models for Inferring Network Structure from Spike Data

    John A. Hertz, Yasser Roudi, and Joanna Tyrcha

    Vocal Learning with Inverse Models

    Richard H. R. Hahnloser and Surya Ganguli

    Computational Models of Visual Object Recognition

    Gabriel Kreiman

    Coding in Neuromorphic VLSI Networks

    Giacomo Indiveri

    Open-Source Software for Studying Neural Codes

    Robin A. A. Ince

    Biography

    Rodrigo Quian Quiroga is a neuroscientist at the University of Leicester UK. He holds a research chair and is the director of the Centre for Systems Neuroscience and the head of the Bioengineering Research Group at the University of Leicester. In 2010, he obtained the Royal Society Wolfson Research Merit Award. His main research interest is on the study of the principles of visual perception and memory. Together with colleagues at Caltech and UCLA, he discovered what has been named "Concept cells" or "Jennifer Aniston neurons"—neurons in the human brain that play a key role in memory formation.

    Stefano Panzeri received a Laurea in Physics from the University of Torino, and a PhD in computational neuroscience from SISSA, Trieste, Italy. He has held personal research fellowship awards in theoretical physics and computational neuroscience, including an INFN Junior Fellowship in Theoretical Physics at Turin University, an EU Marie Curie Postdoctoral Fellowship at the University of Oxford, and an MRC Research Fellowship in Neuroinformatics at the University of Newcastle. He has worked as senior scientist at the Italian Institute of Technology since 2007 and as chair in the Formal Analysis of Cortical Networks at the University of Glasgow since 2012.