Dynamic characteristics of laser-Doppler flux in normal individuals and patients with Raynaud's phenomenon before and after treatment with nifedipine under different thermal conditions.

The study was aimed at choosing an appropriate characteristic of laser-Doppler flux (LDF) data for (1) distinguishing patients with Raynaud's disease from normal controls and (2) evaluating the effect of nifedipine under different thermal conditions. We checked the reliability of three characteristics of nonlinear dynamics as statistical dimension Ds, correlation dimension D2 and power-law index PLI. Their values depended heavily on the thermal condition. The most reliable characteristics that enabled us to distinguish the patients from normal controls and the effect of nifedipine under definite thermal condition proved to be Ds and PLI. The latter is simple for computation and is thus recommendable for clinical practice. Ds and PLI were higher in patients with Raynaud's compared to normal controls and diminished during the transitions from low to high temperature. However, the characteristics used were unable to distinguish significantly Raynaud's I from Raynaud's II patients.

Dynamic characteristics of laser-Doppler flux data.

Methods for tracking the dynamics of the blood flow microcirculation obtained by laser-Doppler flowmetry (LDF) technique are described. It was shown that LDF signals have complex dynamics. It was mainly characterized by fractal structures and chaos, though multiperiodic, trend-like and stochastic components were also established. Procedures for (i) describing the dynamic structure and (ii) tracking the dynamic changes in time of LDF data are proposed. Examples illustrating the efficiency of these procedures are given using both simulated and LDF data collected in experiments with reactive hyperemia. Irrespective of the universality of the methods, the procedures should be specified according to the problem-oriented clinical and experimental studies.

EEG patterns in theta and gamma frequency range and their probable relation to human voluntary movement organization.

In experiments with EEG accompanying continuous slow goal-directed voluntary movements we found abrupt short-term transients (STs) of the coefficients of EEG time-varying autoregressive (TVAR) model. The onset of STs indicated (i) a positive EEG wave related to an increase of 3-7 Hz oscillations in time period before the movement start, (ii) synchronization of 35-40 Hz prior to movement start and during the movement when the target is nearly reached. Both these phenomena are expressed predominantly over supplementary motor area, premotor and parietal cortices. These patterns were detected after averaging of EEG segments synchronized to the abrupt changes of the TVAR coefficients computed in the time course of EEG single records. The results are discussed regarding the cognitive aspect of organization of goal-directed movements.

Testing procedures for non-stationarity and non-linearity in physiological signals.

Most of the physiological signals (EEG, ECG, blood flow, human gait, etc.) characterize by complex dynamics including both non-stationarities and non-linearities. These time series resemble red noise with long-range correlation and 1/(f beta) power spectrum. A question arises as to how to distinguish the characteristics of the process underlying the signal dynamics from the properties of the observed time series. The classical methods to determine possible non-linear (chaotic) dynamics (e.g. correlation dimension) often fail in such signals because of relatively short data records containing stochastic components and non-stationarities. We report an application of several approaches, aimed at (1) determining of the non-stationarities in the signals and (2) testing whether non-linear dynamics exists. Assessment of the intrinsic correlation properties of the dynamic process and distinguishing the same from external trends was performed using singular spectra and detrended fluctuation analysis. The existence of non-linear dynamics was tested by correlation dimension (modified algorithm of re-embedding) and by correlation integrals of real and surrogate data. The correlation integrals of real signal and surrogate data sets were statistically compared using Kolmogorov-Smirnov (K-S) test. The procedures were tested on EEG and laser-Doppler (LD) blood flow. Our suggestion is that no one approach taken alone is the best for our aims. Instead, a battery of methods should be used.

Method for single-trial readiness potential identification, based on singular spectrum analysis.

This paper presents a brief description and the advantages of the singular spectrum analysis (SSA). SSA has recently been recommended for analysis of short, noisy time series. The method was applied to single trials of EEG activity at Cz, Fz, C4, Pz and C3, recorded 3.6 s prior to and 1.2 s after the onset of a voluntary motor act. This specific activity is known in its averaged form as readiness potential (RP) and is considered to reflect the preparation of the voluntary movement. However, some physiological investigations require identification of the parameters of single-trial RPs-their onset and successive phases. SSA is based on analysis of the principal components in vector space of delay coordinates of time series. As a result, SSA algorithm decomposes real data records to components reflecting the trend, alpha and beta frequency bands, respectively, whose oscillations appear or disappear in different time instants. The latter were interpreted to distinguish different dynamical stages of the movement preparatory process.

Single-trial readiness potentials and fatigue.

The authors propose that the cognitive processes related to internal motivation and volition (e.g., intention and preparation of a voluntary action), influenced by central fatigue, could be identified and characterized by cerebral readiness potentials (RP) using methods of chaotic dynamics. The boundaries of single-trial RP and its successive phases can be detected by tracking the data dynamics, and are represented by chaotically behaved short EEG transitions.

Similarity in shape, timing and amplitude of H- and T-reflex potentials concurrently recorded along the broad skin area over soleus muscle.

Variations in shape, timing and amplitude of both mono- and bipolarly measured H- and T-reflex potentials can be influenced to a great extent by the muscle architecture and the peculiarities of the extracellular potential field. The "best point" for bipolar measurements, where the amplitude of the bipolar H- and T-potentials is maximal, occurred for the various subjects at a distance of 3.0 to 5.0 cm below the insertion of the gastrocnemii on the Achilles tendon. In contrast, the corresponding "best point" for monopolar H- and T-potentials is located 5.0 to 9.0 cm below the gastrocnemii insertion. The shape, total duration and timing of H- and T-potentials, concurrently measured at the various points along soleus muscle are similar. When the amplitude of the monopolar H- and T-potentials are levelled at the "best point" for monopolar measurements, the changes in the amplitude of both sets of potentials, monopolarly and bipolarly measured along soleus muscle, are identical. These results imply similar efferent outputs for both H- and T-reflexes, i.e. recruitment of motoneurons of comparable size.