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Quantitative analysis of directional strengths in jointly stationary linear multivariate processes
Published in
2010
PMID: 20364350
Volume: 103
   
Issue: 2
Pages: 119 - 133
Abstract
Identification and analysis of directed influences in multivariate systems is an important problem in many scientific areas. Recent studies in neuroscience have provided measures to determine the network structure of the process and to quantify the total effect in terms of energy transfer. These measures are based on joint stationary representations of a multivariate process using vector auto-regressive (VAR) models. A few important issues remain unaddressed though. The primary outcomes of this study are (i) a theoretical proof that the total coupling strength consists of three components, namely, the direct, indirect, and the interference produced by the direct and indirect effects, (ii) expressions to estimate/calculate these effects, and (iii) a result which shows that the well-known directed measure for linear systems, partial directed coherence (PDC) only aids in structure determination but does not provide a normalized measure of the direct energy transfer. Simulation case studies are shown to illustrate the theoretical results. © 2010 Springer-Verlag.
About the journal
JournalBiological Cybernetics
ISSN03401200
Open AccessNo
Concepts (23)
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    AUTO-REGRESSIVE
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    Coupling strengths
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    DIRECT ENERGY TRANSFERS
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    DIRECTED TRANSFER FUNCTIONS
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    DIRECTIONAL STRENGTH
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    Indirect effects
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    Multivariate process
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    MULTIVARIATE SYSTEMS
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    NETWORK STRUCTURES
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    PARTIAL DIRECTED COHERENCE
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    Quantitative analysis
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    Structure determination
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    Theoretical result
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    Three component
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    TOTAL EFFECT
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    Cements
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    Energy transfer
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    Linear systems
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    Transfer functions
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    Article
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    Multivariate analysis
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    Theoretical model
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    Models, theoretical