title: Advanced Insights into Functional Brain Connectivity by Combining Tensor Decomposition and Partial Directed Coherence.
abstract: Quantification of functional connectivity in physiological networks is frequently performed by means of time-variant partial directed coherence (tvPDC), based on time-variant multivariate autoregressive models. The principle advantage of tvPDC lies in the combination of directionality, time variance and frequency selectivity simultaneously, offering a more differentiated view into complex brain networks. Yet the advantages specific to tvPDC also cause a large number of results, leading to serious problems in interpretability. To counter this issue, we propose the decomposition of multi-dimensional tvPDC results into a sum of rank-1 outer products. This leads to a data condensation which enables an advanced interpretation of results. Furthermore it is thereby possible to uncover inherent interaction patterns of induced neuronal subsystems by limiting the decomposition to several relevant channels, while retaining the global influence determined by the preceding multivariate AR estimation and tvPDC calculation of the entire scalp. Finally a comparison between several subjects is considerably easier, as individual tvPDC results are summarized within a comprehensive model equipped with subject-specific loading coefficients. A proof-of-principle of the approach is provided by means of simulated data; EEG data of an experiment concerning visual evoked potentials are used to demonstrate the applicability to real data.
authors.affiliation: Bernstein Group for Computational Neuroscience Jena, Institute of Medical Statistics, Computer Sciences and Documentation, Jena University Hospital, Friedrich Schiller University Jena, Bachstraße 18, Jena, Germany.
authors.forename: Britta
authors.initials: B
authors.lastname: Pester
authors.affiliation: Department of Child and Adolescent Psychiatry, Psychosomatic Medicine and Psychotherapy Jena University Hospital, Friedrich Schiller University Jena, Philosophenweg 3-5, Jena, Germany.
authors.forename: Carolin
authors.initials: C
authors.lastname: Ligges
authors.affiliation: Bernstein Group for Computational Neuroscience Jena, Institute of Medical Statistics, Computer Sciences and Documentation, Jena University Hospital, Friedrich Schiller University Jena, Bachstraße 18, Jena, Germany.
authors.forename: Lutz
authors.initials: L
authors.lastname: Leistritz
authors.affiliation: Bernstein Group for Computational Neuroscience Jena, Institute of Medical Statistics, Computer Sciences and Documentation, Jena University Hospital, Friedrich Schiller University Jena, Bachstraße 18, Jena, Germany.
authors.forename: Herbert
authors.initials: H
authors.lastname: Witte
authors.affiliation: Bernstein Group for Computational Neuroscience Jena, Institute of Medical Statistics, Computer Sciences and Documentation, Jena University Hospital, Friedrich Schiller University Jena, Bachstraße 18, Jena, Germany.
authors.forename: Karin
authors.initials: K
authors.lastname: Schiecke
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D063132:Connectome / Q000379:methods*; D004569:Electroencephalography; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*