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Directed Information Measur...
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
Monografía
monografia Rebiun22814192 https://catalogo.rebiun.org/rebiun/record/Rebiun22814192 m o d | cr nn 008mamaa 140320s2014 gw s 00 0 eng d 9783642544743 9783642544750 9783642544736 9783662522578 10.1007/978-3-642-54474-3 doi UMA.RE eng GPFC bicssc TEC000000 bisacsh 620 23 Directed Information Measures in Neuroscience Recurso electrónico] edited by Michael Wibral, Raul Vicente, Joseph T. Lizier Berlin, Heidelberg Springer Berlin Heidelberg 2014 Berlin, Heidelberg Berlin, Heidelberg Springer Berlin Heidelberg Berlin, Heidelberg Springer Berlin Heidelberg Imprint: Springer 2014 Berlin, Heidelberg Berlin, Heidelberg Springer Berlin Heidelberg Imprint: Springer XIV, 225 p. 51 il., 8 il. col XIV, 225 p. 51 il., 8 il. col Text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Understanding Complex Systems Bibliographic Level Mode of Issuance: Monograph Part I Introduction to Directed Information Measures -- Part II Information Transfer in Neural and Other Physiological Systems -- Part III Recent Advances in the Analysis of Information Processing 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 English Engineering Coding theory Biomedical engineering Complexity. Coding and Information Theory. Biomedical Engineering and Bioengineering. Engineering Coding theory Biomedical engineering Complexity Coding and Information Theory Biomedical Engineering and Bioengineering Wibral, Michael ed. lit Vicente, Raúl ed. lit Lizier, Joseph T ed. lit 3-642-54473-8 Understanding Complex Systems