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Titlebook: Directed Information Measures in Neuroscience; Michael Wibral,Raul Vicente,Joseph T. Lizier Book 2014 Springer-Verlag Berlin Heidelberg 20

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书目名称Directed Information Measures in Neuroscience
编辑Michael Wibral,Raul Vicente,Joseph T. Lizier
视频video
概述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 inf
丛书名称Understanding Complex Systems
图书封面Titlebook: Directed Information Measures in Neuroscience;  Michael Wibral,Raul Vicente,Joseph T. Lizier Book 2014 Springer-Verlag Berlin Heidelberg 20
描述.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 experi
出版日期Book 2014
关键词Brain connectivity; Causality in neuroscience; EEG data; Effective connectivity; Granger causality; Infor
版次1
doihttps://doi.org/10.1007/978-3-642-54474-3
isbn_softcover978-3-662-52257-8
isbn_ebook978-3-642-54474-3Series ISSN 1860-0832 Series E-ISSN 1860-0840
issn_series 1860-0832
copyrightSpringer-Verlag Berlin Heidelberg 2014
The information of publication is updating

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Information Transfer in the Brain: Insights from a Unified Approachseveral methods. In this chapter we propose some approaches rooted in this framework for the analysis of neuroimaging data. First we will explore how the transfer of information depends on the network structure, showing how for hierarchical networks the information flow pattern is characterized by e
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Function Follows Dynamics: State-Dependency of Directed Functional Influences causal influences between neural populations (described by the so-called .)must be reconfigurable even when the underlying structural connectivity is fixed. Such influences can be quantified through causal analysis of time-series of neural activity with tools like Transfer Entropy. But how can mani
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Measuring the Dynamics of Information Processing on a Local Scale in Time and Spacet the local dynamics of such information processing in space and time can be measured. In this chapter, we review the mathematics of how to measure local entropy and mutual information values at specific observations of time-series processes.We then review how these techniques are used to construct
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Parametric and Non-parametric Criteria for Causal Inference from Time-Seriesn from electrophysiological recordings. This criterion underlies the classical parametric implementation in terms of linear autoregressive processes as well as Transfer entropy, i.e. a non-parametric implementation in the framework of information theory. In the spectral domain, partial directed cohe
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Einführung in das Vergütungsrechtby a variety of directed informationmeasures of which transfer entropy is themost popular, andmost principled one. This chapter presents the basic concepts behind transfer entropy in an intuitive fashion, including graphical depictions of the key concepts. It also includes a special section devoted
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