title: Identifying causal networks of neuronal sources from EEG/MEG data with the phase slope index: a simulation study.
abstract: The investigation of functional neuronal synchronization has recently become a growing field of research. With high temporal resolution, electroencephalography and magnetoencephalography are well-suited measurement techniques to identify networks of interacting sources underlying the recorded data. The analysis of the data in terms of effective connectivity, nevertheless, contains intrinsic issues such as the problem of volume conduction and the non-uniqueness of the inverse solution. Here, we briefly introduce a series of existing methods assessing these problems. To determine the locations of interacting brain sources robust to volume conduction, all computations are solely based on the imaginary part of the cross-spectrum as a trustworthy source of information. Furthermore, we demonstrate the feasibility of estimating causal relationships of systems of neuronal sources with the phase slope index in realistically simulated data. Finally, advantages and drawbacks of the applied methodology are highlighted and discussed.
authors: NIRx Medizintechnik GmbH, Baumbachstr. 17, 13189 Berlin, Germany. mail@aewald.net
authors: Arne
authors: A
authors: Ewald
authors: Forooz Shahbazi
authors: FS
authors: Avarvand
authors: Guido
authors: G
authors: Nolte
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D015984:Causality; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D004569:Electroencephalography / Q000379:methods*; D058407:Electroencephalography Phase Synchronization / Q000502:physiology*; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity