In the light of the results obtained during the last two decades in analysis of signals by time series, it has become evident that the tools of non linear dynamics have their elective role of application in biological, and, in particular, in neuro-physiological and psycho-physiological studies. This work consists in the study of state anxiety as psychological phenomenon characterized by a quantum like model behavior, thus we investigate transitions potentiality à actualization at its basis both in normal and in psycophtological subjects.

Considering that dinamics of state anxiety follows a fractal regime assuming a deterministic-chaotic behavior, we recur to new parameters that are more accurate to evaluate basic characteristics of time series of STAI-S scores.
The methodology is characterized by combination of linear and and non-linear techniques.
The Fast Fourier Transform Fourier Transform (FFT) is a method of linear analysis in the frequency domain that has detected four harmonic oscillating components according to circadian, infradian and ultradian biorythms. These components common to whole experimenatl subjects have a more intensive action in the case of psychopatological subsample. Then FFT provides to differentiate normal partecipants from those with psychopatological diagnosis.

The technique of the variogram (CZF method) detects linear and nonlinear mechanisms that underlie state anxiety process. Variograms have provided two important indications about the variability of state anxiety dynamics in time.
First, for all participants, variograms have confirmed some constant recurrences in specific time lag, and therefore in time: variograms always assume the same increasing and decreasing behaviors in the initial lags (from 4.66 hours to one week) and intermediate lags (from 8 days to 16 days) of the graph, with pronounced peaks of variability into the same timeframe, and then ever lower values until to close to zero in the intervals of ending-lag (one month).
FInto this general distribution of variability, it has identified a further illustration of state anxiety according to normal, normal-psychopathological and psychopathological subgroup: people of the same subgroup show overlapping traits of growth and decrease variability as well as the same points of increase along graphic descending and ascending trait.

These results allow us to formulate an important consideration: mental entities involved in phenomenon of state anxiety act according to its own internal function both general and specific in relation to the conditions of normality and psychopathology. Specific variability indeces of variogram discriminate time dinamics of state anxiety of normal subjects and psychopathological. This evidence is confirmed by statistical t-test and F-test at 99% of accuracy, instead according to predictions, there is a similarity between normal-psychopathological and psychopathological sbsample. Finally, in order to quantify the amount of variability at low or high STAI-S score level, we use the method of Poincare plot that consists in the reconstruction of time series of data in the two-dimensional phase space. Poincaré Plot provides two new indices: SD1 reflects variability at the level of "low scores" category while SD2 reflects variability at the level of "high scores".