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

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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

DRAFT

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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下級(jí)

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

Ambulatory

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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