  We propose a straightforward extension of symbolic transfer entropy to enable
the investigation of delayed directional relationships between coupled
dynamical systems from time series. Analyzing time series from chaotic model
systems, we demonstrate the applicability and limitations of our approach. Our
findings obtained from applying our method to infer delayed directed
interactions in the human epileptic brain underline the importance of our
approach for improving the construction of functional network structures from
data.
