Written by renowned experts in the field, this book provides a comprehensive and up-to-date overview on neural coding. It describes the principles of neural coding, covers some of the major developments in this area, and presents a complete view of how neurons in the brain encode information. The text not only contains the most important experimental findings, but also 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.
Preface: Rodrigo Quian Quiroga and Stefano Panzeri Methods Physiological Foundations of Neural Signals, Kevin Whittingstall and Nikos Logothetis Biophysics of Extracellular Spikes, Costas Anastassiou, Gyorgy Buzsaki, and Christof Koch Local Field Potentials: Biophysical Origin and Analysis, Gaute Einevoll, Henrik Linden, Tom Tetzlaff, Szymon Leski, and Klas Pettersen Spike Sorting, Juan Martinez and Rodrigo Quian Quiroga Spike-Train Analysis, Ines Samengo, Daniel Elijah, and Marcelo Montemurro Synchronization Measures, Thomas Kreuz Role of Correlations in Population Coding, Peter Latham and Yasser Roudi Decoding and Information Theory in Neuroscience, Rodrigo Quian Quiroga and Stefano Panzeri Experimental Results Neural Coding of Visual Objects, Ed Connor Coding in the Auditory System, Jan Schnupp Somatosensory Coding, Mathew 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 Ghazanfar Population Coding by Place Cells and Grid Cells, Jill Leutgeb, Emily Mankin, and Stefan Leutgeb Coding of Movement Intentions, Hans Scherberger, Rodrigo Quian Quiroga, and Richard Andersen Neural Coding of Short-Term Memory, Stefanie Liebe and Gregor Rainer The Role of Temporal Spike Patterns in Neural Codes, Rasmus Petersen Adaptation and Sensory Coding, Miguel Maravall Sparse and Explicit Neural Coding, Peter Foldiak Information Coding by Cortical Populations, Kenneth Harris The Information Content of Local Field Potentials: Experiments and Models, Alberto Mazzoni, Nikos Logothetis, and Stefano Panzeri Principles of Neural Coding from EEG Signals, Fernando Lopes da Silva Gamma-Band Synchronization and Information Transmission, Martin Vinck, Thilo Womelsdorf, and Pascal Fries Decoding Information from fMRI Signals, Jakov Heinzle and John-Dylan Haynes Theoretical and In-Silico Approaches Dynamics of Neural Networks, Nicolas Brunel Learning and Coding in Neural Networks, Timothee Masquelier and Gustavo Deco Ising Models for Inferring Network Structure from Spike Data, John Hertz, Yasser Roudi, and Joanna Tyrcha Vocal Learning with Inverse Models, Richard Hahnloser and Surya Ganguli Computational Models of Visual Object Recognition, Gabriel Kreiman Coding in neuromorphic VLSI Networks, Giacomo Indiveri Neuroscience open source toolboxes, Robin Ince