Overview
- Reflects the most recent developments in the quantification of information transfer via directed information measures
- Provides the reader with the state-of-the-art concepts and tools for measuring information transfer in the brain and includes applications to real data sets
- Makes the reader familiar with the concept of transfer entropy – the most popular measure of information transfer
- Edited and written by the most active researchers in the field
- Includes supplementary material: sn.pub/extras
Part of the book series: Understanding Complex Systems (UCS)
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Table of contents (8 chapters)
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Front Matter
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Introduction to Directed Information Measures
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Front Matter
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Information Transfer in Neural and Other Physiological Systems
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Front Matter
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Recent Advances in the Analysis of Information Processing
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Front Matter
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Back Matter
Keywords
About this book
Analysis of information transfer has found rapid adoption in neuroscience, where a highly dynamic transfer of information continuously runs on top of the brain's slowly-changing anatomical connectivity. Measuring such transfer is crucial to understanding how flexible information routing and processing give rise to higher cognitive function. Directed Information Measures in Neuroscience reviews recent developments of concepts and tools for measuring information transfer, their application to neurophysiological recordings and analysis of interactions. Written by the most active researchers in the field the book discusses the state of the art, future prospects and challenges on the way to an efficient assessment of neuronal information transfer. Highlights include the theoretical quantification and practical estimation of information transfer, description of transfer locally in space and time, multivariate directed measures, information decomposition among a set of stimulus/responses variables and the relation between interventional and observational causality. Applications to neural data sets and pointers to open source software highlight the usefulness of these measures in experimental neuroscience. With state-of-the-art mathematical developments, computational techniques and applications to real data sets, this book will be of benefit to all graduate students and researchers interested in detecting and understanding the information transfer between components of complex systems.
Editors and Affiliations
Bibliographic Information
Book Title: Directed Information Measures in Neuroscience
Editors: Michael Wibral, Raul Vicente, Joseph T. Lizier
Series Title: Understanding Complex Systems
DOI: https://doi.org/10.1007/978-3-642-54474-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2014
Hardcover ISBN: 978-3-642-54473-6Published: 04 April 2014
Softcover ISBN: 978-3-662-52257-8Published: 03 September 2016
eBook ISBN: 978-3-642-54474-3Published: 20 March 2014
Series ISSN: 1860-0832
Series E-ISSN: 1860-0840
Edition Number: 1
Number of Pages: XIV, 225
Number of Illustrations: 43 b/w illustrations, 8 illustrations in colour
Topics: Complexity, Coding and Information Theory, Biomedical Engineering and Bioengineering