Extended causal modeling to assess partial directed coherence in multiple time series with significant instantaneous interactions

DOI10.1007/s00422-010-0406-6zbMath1407.62312OpenAlexW2072522604WikidataQ51649128 ScholiaQ51649128MaRDI QIDQ1631752

Luca Faes, Giandomenico Nollo

Publication date: 7 December 2018

Published in: Biological Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00422-010-0406-6

zbMATH Keywords

Granger causalitymultivariate time seriesEEGpartial directed coherencemultivariate autoregressive modelscardiovascular variability

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Neural biology (92C20)

Related Items (7)

Measuring frequency domain Granger causality for multiple blocks of interacting time series ⋮ A novel method for the identification of synchronization effects in multichannel ECoG with an application to epilepsy ⋮ Evaluation of connectivity estimates using spiking neuronal network models ⋮ Mathematical issues in the inference of causal interactions among multichannel neural signals ⋮ Measuring connectivity in linear multivariate processes: definitions, interpretation, and practical analysis ⋮ Quantification of effective connectivity in the brain using a measure of directed information ⋮ Electroencephalographic Motor Imagery Brain Connectivity Analysis for BCI: A Review

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