title: Time-variant partial directed coherence for analysing connectivity: a methodological study.
abstract: For the past decade, the detection and quantification of interactions within and between physiological networks has become a priority-in-common between the fields of biomedicine and computer science. Prominent examples are the interaction analysis of brain networks and of the cardiovascular-respiratory system. The aim of the study is to show how and to what extent results from time-variant partial directed coherence analysis are influenced by some basic estimator and data parameters. The impacts of the Kalman filter settings, the order of the autoregressive (AR) model, signal-to-noise ratios, filter procedures and volume conduction were investigated. These systematic investigations are based on data derived from simulated connectivity networks and were performed using a Kalman filter approach for the estimation of the time-variant multivariate AR model. Additionally, the influence of electrooculogram artefact rejection on the significance and dynamics of interactions in 29 channel electroencephalography recordings, derived from a photic driving experiment, is demonstrated. For artefact rejection, independent component analysis was used. The study provides rules to correctly apply particular methods that will aid users to achieve more reliable interpretations of the results.
authors.affiliation: Institute of Medical Statistics, Computer Sciences and Documentation, Bernstein Group for Computational Neuroscience, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany. lutz.leistritz@mti.uni-jena.de
authors.forename: L
authors.initials: L
authors.lastname: Leistritz
authors.forename: B
authors.initials: B
authors.lastname: Pester
authors.forename: A
authors.initials: A
authors.lastname: Doering
authors.forename: K
authors.initials: K
authors.lastname: Schiecke
authors.forename: F
authors.initials: F
authors.lastname: Babiloni
authors.forename: L
authors.initials: L
authors.lastname: Astolfi
authors.forename: H
authors.initials: H
authors.lastname: Witte
mesh_terms: D000818:Animals; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D063132:Connectome / Q000379:methods*; D005163:Factor Analysis, Statistical; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D012044:Regression Analysis; D009435:Synaptic Transmission / Q000502:physiology*
keywords: effective connectivity; electrooculogram artefact rejection; independent component analysis; partial directed coherence; time-variant multivariate autoregressive modelling