Temporal patterns of human behaviour: are there signs of deterministic 1/f scaling?

Temporal patterns apparently exhibiting scaling properties may originate either from fractal stochastic processes or from causal (i.e., deterministic) dynamics. In general, the distinction between the possible two origins remains a non-trivial task. This holds especially for the interpretation of properties derived from temporal patterns of various types of human behaviour, which were reported repeatedly. We propose here a computational scheme based on a generic intermittency model to test predictability (thus determinism) of a part of a time series with knowledge gathered from another part. The method is applied onto psychodynamic time series related to turns from non-psychosis to psychosis. A nonrandom correlation (ρ=0.76) between prediction and real outcome is found. Our scheme thus provides a particular kind of fractal risk-assessment for this possibly deterministic process. We briefly discuss possible implications of these findings to evaluate the risk to undergo a state transition, in our case a patients risk to enter a next psychotic state. We further point to some problems concerning data sample pecularities and equivalence between data and model setup.