TY  - JOUR
A1  - Wibral, Michael
A1  - Vicente, Raul
A1  - Triesch, Jochen
A1  - Pipa, Gordon
T1  - Using transfer entropy to measure the patterns of information flow though cortex : application to MEG recordings from a visual Simon task
T2  - BMC neuroscience
N2  - Poster presentation: Functional connectivity of the brain describes the network of correlated activities of different brain areas. However, correlation does not imply causality and most synchronization measures do not distinguish causal and non-causal interactions among remote brain areas, i.e. determine the effective connectivity [1]. Identification of causal interactions in brain networks is fundamental to understanding the processing of information. Attempts at unveiling signs of functional or effective connectivity from non-invasive Magneto-/Electroencephalographic (M/EEG) recordings at the sensor level are hampered by volume conduction leading to correlated sensor signals without the presence of effective connectivity. Here, we make use of the transfer entropy (TE) concept to establish effective connectivity. The formalism of TE has been proposed as a rigorous quantification of the information flow among systems in interaction and is a natural generalization of mutual information [2]. In contrast to Granger causality, TE is a non-linear measure and not influenced by volume conduction. ...
Y1  - 2009
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/7074
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30-70795
N1  - © 2009 Wibral et al; licensee BioMed Central Ltd.
VL  - 10(Suppl 1)
IS  - P232
ER  -