Quantification of Effective Connectivity in the Brain Using a Measure of Directed Information
Joint Authors
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-05-16
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Effective connectivity refers to the influence one neural system exerts on another and corresponds to the parameter of a model that tries to explain the observed dependencies.
In this sense, effective connectivity corresponds to the intuitive notion of coupling or directed causal influence.
Traditional measures to quantify the effective connectivity include model-based methods, such as dynamic causal modeling (DCM), Granger causality (GC), and information-theoretic methods.
Directed information (DI) has been a recently proposed information-theoretic measure that captures the causality between two time series.
Compared to traditional causality detection methods based on linear models, directed information is a model-free measure and can detect both linear and nonlinear causality relationships.
However, the effectiveness of using DI for capturing the causality in different models and neurophysiological data has not been thoroughly illustrated to date.
In addition, the advantage of DI compared to model-based measures, especially those used to implement Granger causality, has not been fully investigated.
In this paper, we address these issues by evaluating the performance of directed information on both simulated data sets and electroencephalogram (EEG) data to illustrate its effectiveness for quantifying the effective connectivity in the brain.
American Psychological Association (APA)
Liu, Ying& Aviyente, Selin. 2012. Quantification of Effective Connectivity in the Brain Using a Measure of Directed Information. Computational and Mathematical Methods in Medicine،Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-486923
Modern Language Association (MLA)
Liu, Ying& Aviyente, Selin. Quantification of Effective Connectivity in the Brain Using a Measure of Directed Information. Computational and Mathematical Methods in Medicine No. 2012 (2012), pp.1-16.
https://search.emarefa.net/detail/BIM-486923
American Medical Association (AMA)
Liu, Ying& Aviyente, Selin. Quantification of Effective Connectivity in the Brain Using a Measure of Directed Information. Computational and Mathematical Methods in Medicine. 2012. Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-486923
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-486923