Dear all, We are pleased to announce the publication of the following edited book: "Directed Information Measures in Neuroscience" edited by Michael Wibral, Raul Vicente, Joseph T. Lizier in series "Understanding Complex Systems", Springer, Berlin, 2014. About the book: http://www.springer.com/physics/complexity/book/978-3-642-54473-6 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. Downloads of individual chapters (requires Springer access) via: http://link.springer.com/book/10.1007%2F978-3-642-54474-3 Contents: Section 1 - Introduction to Directed Information Measures Chapter 1. "Transfer Entropy in Neuroscience", Michael Wibral, Raul Vicente, Michael Lindner -- http://link.springer.com/chapter/10.1007/978-3-642-54474-3_1 Chapter 2. "Efficient Estimation of Information Transfer", Raul Vicente, Michael Wibral -- http://link.springer.com/chapter/10.1007/978-3-642-54474-3_2 Section 2 - Information Transfer in Neural and Other Physiological Systems Chapter 3. "Conditional Entropy-Based Evaluation of Information Dynamics in Physiological Systems", Luca Faes, Alberto Porta -- http://link.springer.com/chapter/10.1007/978-3-642-54474-3_3 Chapter 4. "Information Transfer in the Brain: Insights from a Unified Approach", Daniele Marinazzo, Guorong Wu, Mario Pellicoro, Sebastiano Stramaglia -- http://link.springer.com/chapter/10.1007/978-3-642-54474-3_4 Chapter 5. "Function Follows Dynamics: State-Dependency of Directed Functional Influences", Demian Battaglia -- http://link.springer.com/chapter/10.1007/978-3-642-54474-3_5 Chapter 6. "On Complexity and Phase Effects in Reconstructing the Directionality of Coupling in Non-linear Systems", Vasily A. Vakorin, Olga Krakovska, Anthony R. McIntosh -- http://link.springer.com/chapter/10.1007/978-3-642-54474-3_6 Section 3 - Recent Advances in the Analysis of Information Processing Chapter 7. "Measuring the Dynamics of Information Processing on a Local Scale in Time and Space", Joseph T. Lizier -- http://link.springer.com/chapter/10.1007/978-3-642-54474-3_7 Chapter 8. "Parametric and Non-parametric Criteria for Causal Inference from Time-Series", Daniel Chicharro -- http://link.springer.com/chapter/10.1007/978-3-642-54474-3_8 Amazon link: http://www.amazon.com/gp/product/3642544738/ref=as_li_ss_tl?ie=UTF8&camp=1789&creative=390957&creativeASIN=3642544738&tag=joselizi-20&linkCode=as2 Regards, Michael Wibral, Raul Vicente and Joseph Lizier