title: Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance.
abstract: Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies.
authors: Center for Lifespan Psychology, Max Planck Institute for Human Development Berlin, Germany.
authors: Viktor
authors: V
authors: Müller
authors: Center for Lifespan Psychology, Max Planck Institute for Human DevelopmentBerlin, Germany; Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes UMR_S 1106, Aix-Marseille UniversitéMarseille, France.
authors: Dionysios
authors: D
authors: Perdikis
authors: Department of Psychology, University of Virginia Charlottesville, VA, USA.
authors: Timo
authors: T
authors: von Oertzen
authors: Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes UMR_S 1106, Aix-Marseille UniversitéMarseille, France; Centre National de la Recherche Scientifique, Institut des Sciences du Mouvement UMR 7287, Aix-Marseille UniversitéMarseille, France.
authors: Rita
authors: R
authors: Sleimen-Malkoun
authors: Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes UMR_S 1106, Aix-Marseille Université Marseille, France.
authors: Viktor
authors: V
authors: Jirsa
authors: Center for Lifespan Psychology, Max Planck Institute for Human DevelopmentBerlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Aging ResearchBerlin, Germany; Department of Political and Social Sciences, European University InstituteSan Domenico di Fiesole (FI), Italy.
authors: Ulman
authors: U
authors: Lindenberger
keywords: auditory oddball performance; directional coupling; functional connectivity; graph-theoretical approach; hyper-frequency network; network topology dynamics; resting state