caa a22 4500 445295074 CHVBK 20180317142539.0 cr unu---uuuuu 170323e20100601xx s 000 0 eng 10.1007/s11571-010-9107-z doi (NATIONALLICENCE)springer-10.1007/s11571-010-9107-z A method for the estimation of functional brain connectivity from time-series data [Elektronische Daten] [A. Wilmer, M. de Lussanet, M. Lappe] A central issue in cognitive neuroscience is which cortical areas are involved in managing information processing in a cognitive task and to understand their temporal interactions. Since the transfer of information in the form of electrical activity from one cortical region will in turn evoke electrical activity in other regions, the analysis of temporal synchronization provides a tool to understand neuronal information processing between cortical regions. We adopt a method for revealing time-dependent functional connectivity. We apply statistical analyses of phases to recover the information flow and the functional connectivity between cortical regions for high temporal resolution data. We further develop an evaluation method for these techniques based on two kinds of model networks. These networks consist of coupled Rössler attractors or of coupled stochastic Ornstein-Uhlenbeck systems. The implemented time-dependent coupling includes uni- and bi-directional connectivities as well as time delayed feedback. The synchronization dynamics of these networks are analyzed using the mean phase coherence, based on averaging over phase-differences, and the general synchronization index. The latter is based on the Shannon entropy. The combination of these with a parametric time delay forms the basis of a connectivity pattern, which includes the temporal and time lagged dynamics of the synchronization between two sources. We model and discuss potential artifacts. We find that the general phase measures are remarkably stable. They produce highly comparable results for stochastic and periodic systems. Moreover, the methods proves useful for identifying brief periods of phase coupling and delays. Therefore, we propose that the method is useful as a basis for generating potential functional connective models. Springer Science+Business Media B.V., 2010 Functional connectivity nationallicence Time-delayed phase synchronization nationallicence MEG magnetencephalography nationallicence Network analysis nationallicence Wilmer A. Deptartment of Psychology, Westf. Wilhelms-University, Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience (OCC), Münster, Germany aut de Lussanet M. Deptartment of Psychology, Westf. Wilhelms-University, Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience (OCC), Münster, Germany aut Lappe M. Deptartment of Psychology, Westf. Wilhelms-University, Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience (OCC), Münster, Germany aut Cognitive Neurodynamics Springer Netherlands 4/2(2010-06-01), 133-149 1871-4080 4:2<133 2010 4 11571 https://doi.org/10.1007/s11571-010-9107-z text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11571-010-9107-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wilmer A. Deptartment of Psychology, Westf. Wilhelms-University, Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience (OCC), Münster, Germany aut NATIONALLICENCE 700 1- de Lussanet M. Deptartment of Psychology, Westf. Wilhelms-University, Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience (OCC), Münster, Germany aut NATIONALLICENCE 700 1- Lappe M. Deptartment of Psychology, Westf. Wilhelms-University, Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience (OCC), Münster, Germany aut NATIONALLICENCE 773 0- Cognitive Neurodynamics Springer Netherlands 4/2(2010-06-01), 133-149 1871-4080 4:2<133 2010 4 11571 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer