  This work explores the potential of an information-theoretical causality
detection method for unraveling the relation between fluctuating variables in
complex nonlinear systems. The method is tested on some simple though nonlinear
models, and guidelines for the choice of analysis parameters are established.
Then, measurements from magnetically confined fusion plasmas are analyzed. The
selected data bear relevance to the all-important spontaneous confinement
transitions often observed in fusion plasmas, fundamental for the design of an
economically attractive fusion reactor. It is shown how the present method is
capable of clarifying the interaction between fluctuating quantities such as
the turbulence amplitude, turbulent flux, and Zonal Flow amplitude, and
uncovers several interactions that were missed by traditional methods.
