Investigating Deviations from Dynamical Randomness With Scaling Indices

The information contained in any given experimental time series can be utilized more exhaustively when transition probabilities between states are studied rather than state probabilities alone. Using advanced techniques of time series analysis, it is shown that deviations from dynamical randomness indicate evidence for unexpected temporal correlation features in selected data sets taken from a mind-matter experiment conducted at Freiburg (Germany). The techniques of analysis and a proper error estimation are brie y described, and some preliminary rst results are presented. They encourage further inquiry into processual aspects of deviations from randomness in addition to more straightforward analyses of state probabilities.