124
H. Schmid-Schönbein
Using a number of additional techniques (such as wavelet-time-transient reconstruction, autoregressive moving average (ARMA-time series), estimates of instantaneous
powers) the logic of “quasi-attractors” was extended by van den Houten with the
aim of displaying “stochastic coherency” and “stochastic synchronisation” in such
a fashion that both the appearance and disappearance of instantaneous frequency
synchronisation and phase synchronisation can be intuitively comprehended by
physicians without specific training in modern topology and nonlinear analysis.
This goal has been achieved in the program package (SANTIS
® ) which combines
the clarity of the frequency chromatographs with the ability of simple time series
to deal with non-stationarity as the most essential aspect of neurodynamic activities
at large: here, the concept “quasi-attractors” is being visualised by “mountains of
relevancy” separated by valleys of irrelevancy on the basis of intuitively comprehensible vaccilating pattern on the screen of computers (see Fig. 7.10). These novel
instruments can replace a host of techniques from the late 1990s allowing to quantify
the spatio-temporal patterns of highly complex, superimposed rhythmic time course
as they have been developed in the last two decades: they all depend on the ability
to extract “information concerning instationary temporality” as it is, for example,
contained in the numerical value of Lyapunov exponents, or in the dimensionality
of processes (which, of course, is “fractal” in the cases of natural quasi-attractors
and, of course, is reflected in the “distance from equilibrium” (or neg-ergodicity
indices responsible for the positioning of complex attractors in the so-called phase
space). In depicting both the time–frequency plots and the original time series, easily
comprehensible information concerning the “overall scope” (German “Spielraum”)
of the complex system in question can be displayed. In simply displaying in the form
of “double plots” both the original time series (with variable temporal resolution
but reliable information concerning the “distance from equilibrium” and the time
frequency diagrams (representing emergence and submergence of cooperation and
thence of “quasi-attractors”), the entire information concerning the spatio-temporal
patterns of cardiovascular events of any kind cannot only be retained at will, but
can be displayed in a form in which the previous history as well as the response to
defined stimuli can be monitored objectively. Records thus obtained in the form of
both fine-grained and coarse-grained plots are easily intuitable and can be adapted
to the problem under investigation. Last not least, the results can be stored and
“replayed” at will and in a more or less comprehensive fashion.
As will be shown in the closing Outlook section, under exceptional, but, of course,
physiologically important conditions, stationarity of periodically fluctuation cardiovascular and respiratory parameters can in fact be induced, for example, when volunteers are made to exercise (easiest when driving a bicycle ergometer) in a fashion
that seems “comfortable” to them. During the “steady state” of such an exercise,
superimposition of periodically varying entities can be also seen, for example, in the
data shown in Fig. 7.5: displaying a situation where a volunteer was asked to drive
the ergometer into a periodicity convenient for him when loaded to 120 W. There
is conspicuous consensualisation between respiratory periodicity (upper panel) and
periodicity of arterial blood pressure, but also a strict coordination between ventilatory and skeletomotor activity, and therefore between cardiac and skeletomuscular
H. Schmid-Schönbein
Using a number of additional techniques (such as wavelet-time-transient reconstruction, autoregressive moving average (ARMA-time series), estimates of instantaneous
powers) the logic of “quasi-attractors” was extended by van den Houten with the
aim of displaying “stochastic coherency” and “stochastic synchronisation” in such
a fashion that both the appearance and disappearance of instantaneous frequency
synchronisation and phase synchronisation can be intuitively comprehended by
physicians without specific training in modern topology and nonlinear analysis.
This goal has been achieved in the program package (SANTIS
® ) which combines
the clarity of the frequency chromatographs with the ability of simple time series
to deal with non-stationarity as the most essential aspect of neurodynamic activities
at large: here, the concept “quasi-attractors” is being visualised by “mountains of
relevancy” separated by valleys of irrelevancy on the basis of intuitively comprehensible vaccilating pattern on the screen of computers (see Fig. 7.10). These novel
instruments can replace a host of techniques from the late 1990s allowing to quantify
the spatio-temporal patterns of highly complex, superimposed rhythmic time course
as they have been developed in the last two decades: they all depend on the ability
to extract “information concerning instationary temporality” as it is, for example,
contained in the numerical value of Lyapunov exponents, or in the dimensionality
of processes (which, of course, is “fractal” in the cases of natural quasi-attractors
and, of course, is reflected in the “distance from equilibrium” (or neg-ergodicity
indices responsible for the positioning of complex attractors in the so-called phase
space). In depicting both the time–frequency plots and the original time series, easily
comprehensible information concerning the “overall scope” (German “Spielraum”)
of the complex system in question can be displayed. In simply displaying in the form
of “double plots” both the original time series (with variable temporal resolution
but reliable information concerning the “distance from equilibrium” and the time
frequency diagrams (representing emergence and submergence of cooperation and
thence of “quasi-attractors”), the entire information concerning the spatio-temporal
patterns of cardiovascular events of any kind cannot only be retained at will, but
can be displayed in a form in which the previous history as well as the response to
defined stimuli can be monitored objectively. Records thus obtained in the form of
both fine-grained and coarse-grained plots are easily intuitable and can be adapted
to the problem under investigation. Last not least, the results can be stored and
“replayed” at will and in a more or less comprehensive fashion.
As will be shown in the closing Outlook section, under exceptional, but, of course,
physiologically important conditions, stationarity of periodically fluctuation cardiovascular and respiratory parameters can in fact be induced, for example, when volunteers are made to exercise (easiest when driving a bicycle ergometer) in a fashion
that seems “comfortable” to them. During the “steady state” of such an exercise,
superimposition of periodically varying entities can be also seen, for example, in the
data shown in Fig. 7.5: displaying a situation where a volunteer was asked to drive
the ergometer into a periodicity convenient for him when loaded to 120 W. There
is conspicuous consensualisation between respiratory periodicity (upper panel) and
periodicity of arterial blood pressure, but also a strict coordination between ventilatory and skeletomotor activity, and therefore between cardiac and skeletomuscular