7 Synergetic Interpretation of Patterned Vasomotion Activity …
123
compare the powers of distinctly different activities displayed in the range of “low
frequency” (well below 0.1 Hz, v.i.).
It is common knowledge that the techniques developed in the nonlinear sciences
(“chaos theory”) depend on the identification of characteristic features of the rhythmically modulated output from a “black-box”, i.e. a system too complicated to scrutinise without destroying its basic modes of operation. In this situation, it is possible to
refocus the attention in scientific inquiry: rather than quantifying the “magnitude” of
an activity (reflected in the amplitude of a fluctuation or its power, namely the square
of the amplitude), the temporality of a process can likewise be quantified objectively.
We wish to stress that in last analysis, this logic was first introduced into the natural
sciences in theoretical physics: we follow by extrapolating a discovery made and
popularised by Ruelle and Talkin in their attempt to comprehend complexly timed
hydrodynamic turbulence. A similar logic was later applied to the field of nonlinear
optics in the early phases of constructing pulse-Lasers and led Haken to institute
formal synergetics.
However, as we are now portraying the temporality of dynamically vaxing and
waning periodic activities in the form of “attractor portrays”, we no longer paraphrase as “strange”, but rather as “natural”. This functional logic makes necessary
to develop problem appropriate techniques of data compression, which in taking up
the potentialities of Fourier transformation extends their powerful utility to situations no longer allowing its use. There are many limitations which in a strict physical
sense forbid the conventional technique of portraying the dynamics of non-stationary,
nonlinear and noise afflicted time series as power spectra (see textbooks of theoretical physics and especially van den Houten. It proved to be helpful and depicts
instationary activities subsequent to the transformation of amplitude modulated time
series into the frequency domain. Consensualisation appears and disappears, i.e. the
activity shows the “transiency” so typical for activities “driven” by central nervous
systems. In such situations, conventional power spectra are of not just of questionable theoretical utility: pragmatically speaking, they blur, rather than disclose the
information contained in the recorded activities.
Using the Fourier transformed information about the dynamics of cutaneous perfusion (PPG and LDA activity), it can be pragmatically utilised by displayed it in
the mode of a kind of “histogram” where the amplitude density of fluctuations in
a given frequency band of closely related activities of clearly different origin are
displayed in a non-conventional manner. Rather than constructing plots of powers
as the function of the numerical value of a frequency range, plots were constructed
that display amplitudes as the function of the logarithm of the respective medians
(“frequency chromatograms”). Originally, these were plotted by averaging the information gathered within distinct observations periods, e.g. 5 min or 15 min. This
“coarse grained” analysis had already greatly helped as a pragmatic strategy of
information compression, but was, of course, insufficient in light of the concept
of “quasi-attractors”. In order to cope with emerging and submerging cooperativities between subsystems (ventilatory, cardiac, arteriolar, neurodynamic) in a more
fine-grained fashion, van den Houten developed a strategy to use “gliding” windows,
i.e. to scrutinise temporal changes in the cooperation/superposition of subsystems.
123
compare the powers of distinctly different activities displayed in the range of “low
frequency” (well below 0.1 Hz, v.i.).
It is common knowledge that the techniques developed in the nonlinear sciences
(“chaos theory”) depend on the identification of characteristic features of the rhythmically modulated output from a “black-box”, i.e. a system too complicated to scrutinise without destroying its basic modes of operation. In this situation, it is possible to
refocus the attention in scientific inquiry: rather than quantifying the “magnitude” of
an activity (reflected in the amplitude of a fluctuation or its power, namely the square
of the amplitude), the temporality of a process can likewise be quantified objectively.
We wish to stress that in last analysis, this logic was first introduced into the natural
sciences in theoretical physics: we follow by extrapolating a discovery made and
popularised by Ruelle and Talkin in their attempt to comprehend complexly timed
hydrodynamic turbulence. A similar logic was later applied to the field of nonlinear
optics in the early phases of constructing pulse-Lasers and led Haken to institute
formal synergetics.
However, as we are now portraying the temporality of dynamically vaxing and
waning periodic activities in the form of “attractor portrays”, we no longer paraphrase as “strange”, but rather as “natural”. This functional logic makes necessary
to develop problem appropriate techniques of data compression, which in taking up
the potentialities of Fourier transformation extends their powerful utility to situations no longer allowing its use. There are many limitations which in a strict physical
sense forbid the conventional technique of portraying the dynamics of non-stationary,
nonlinear and noise afflicted time series as power spectra (see textbooks of theoretical physics and especially van den Houten. It proved to be helpful and depicts
instationary activities subsequent to the transformation of amplitude modulated time
series into the frequency domain. Consensualisation appears and disappears, i.e. the
activity shows the “transiency” so typical for activities “driven” by central nervous
systems. In such situations, conventional power spectra are of not just of questionable theoretical utility: pragmatically speaking, they blur, rather than disclose the
information contained in the recorded activities.
Using the Fourier transformed information about the dynamics of cutaneous perfusion (PPG and LDA activity), it can be pragmatically utilised by displayed it in
the mode of a kind of “histogram” where the amplitude density of fluctuations in
a given frequency band of closely related activities of clearly different origin are
displayed in a non-conventional manner. Rather than constructing plots of powers
as the function of the numerical value of a frequency range, plots were constructed
that display amplitudes as the function of the logarithm of the respective medians
(“frequency chromatograms”). Originally, these were plotted by averaging the information gathered within distinct observations periods, e.g. 5 min or 15 min. This
“coarse grained” analysis had already greatly helped as a pragmatic strategy of
information compression, but was, of course, insufficient in light of the concept
of “quasi-attractors”. In order to cope with emerging and submerging cooperativities between subsystems (ventilatory, cardiac, arteriolar, neurodynamic) in a more
fine-grained fashion, van den Houten developed a strategy to use “gliding” windows,
i.e. to scrutinise temporal changes in the cooperation/superposition of subsystems.