1st Edition
Principles of Neural Coding
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.
