Methods Inf Med - Assessing frequency domain causality in cardiovascular time series with instantaneous interactions.

Tópicos

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Resumo

CKGROUND: The partial directed coherence (PDC) is commonly used to assess in the frequency domain the existence of causal relations between two time series measured in conjunction with a set of other time series. Although the multivariate autoregressive (MVAR) model traditionally used for PDC computation accounts only for lagged effects, instantaneous effects cannot be neglected in the analysis of cardiovascular time series.OBJECTIVES: We propose the utilization of an extended MVAR model for PDC computation, in order to improve the evaluation of frequency domain causality in the presence of zero-lag correlations among multivariate time series.METHODS: A procedure for the identification of a MVAR model combining instantaneous and lagged effects is introduced. The coefficients of the extended model are used to estimate an extended PDC (EPDC). EPDC is compared to the traditional PDC on a simulated MVAR process and on real cardiovascular variability series.RESULTS: Simulation results evidence that the presence of zero-lag correlations may produce misleading PDC profiles, while the correct causality patterns can be recovered using EPDC. Application on real data leads to spectral causality estimates which are better interpretable in terms of the known cardiovascular physiology using EPDC than PDC.CONCLUSIONS: This study emphasizes the necessity of including instantaneous effects in the MVAR model used for the computation of PDC in the presence of significant zero-lag correlations in multivariate time series.

Resumo Limpo

ckground partial direct coher pdc common use assess frequenc domain exist causal relat two time seri measur conjunct set time seri although multivari autoregress mvar model tradit use pdc comput account lag effect instantan effect neglect analysi cardiovascular time seriesobject propos util extend mvar model pdc comput order improv evalu frequenc domain causal presenc zerolag correl among multivari time seriesmethod procedur identif mvar model combin instantan lag effect introduc coeffici extend model use estim extend pdc epdc epdc compar tradit pdc simul mvar process real cardiovascular variabl seriesresult simul result evid presenc zerolag correl may produc mislead pdc profil correct causal pattern can recov use epdc applic real data lead spectral causal estim better interpret term known cardiovascular physiolog use epdc pdcconclus studi emphas necess includ instantan effect mvar model use comput pdc presenc signific zerolag correl multivari time seri

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