Analysis of the non-stationary EEG by means of an approximate canonical expansion

The mathematical framework of the canonical expansion of a random time function has been applied to the analysis of the electroencephalogram. The proposed method has been adapted for a computersuited algorithm by using an orthogonalization concept of the vector space theory. The offered solution avoids the mathematical difficulties of the rigorous theory of Karhunen-Loeve expansion. Moreover, the results of the analysis highlight new aspects of the physical properties of the electroencephalogram. Suggestions with regard to the non-linear character of the oscillators generating electrical activity seem to be valid.     

Segmentation of the epileptic EEG by means of a finite state automation

The aims and merits of the syntactical decomposition of the epileptic EEG are discussed in some detail. General assumptions in the design of segmenting algorithm - an essential part of the reduction of data program - are considered and a working example of segmenting routine os presented. This routine is designed as a finite state automaton, equivalent to a formal regular grammar. The performance of the routine on two sets of experimental data is presented and its intrinsic stability is shown in terms of cluster analysis of the segments produced. Means of extension of the proposed scheme to other cases of potential interest as well as possible applications in the higher level syntactical analysis are pointed out.     

EEG Feature extraction using parcor coefficients

This study presents pattern recognition experiments of the electroencephalogram. The components of the feature vector are built up by Parcor coefficients which provide a simple structure of the covariance matrix. The BAYES classifier is implemented which is theoretically best in minimizing the error rate. The MAHALANOBIS classifier is used too by means of an averaged covariance matrix. The performance of the classifier is tested in experiment by computing the error rate.     

Calculation errors of time-varying flux control coefficients obtained from elasticity coefficients by means of summation and connectivity theorems in metabolic control analysis

This paper investigates the accuracy of a matrix method proposed by other researchers to calculate time-varying flux control coefficients (dynamic FCCs) from elasticity coefficients by means of summation and connectivity theorems in the framework of metabolic control analysis. A mathematical model for the fed-batch penicillin V fermentation process is used as a case example for discussion. Calculated results reveal that this method produces significant calculation errors because the theorems are essentially valid only in steady state, although it may provide rough time-transient behaviors of FCCs. Strictly, therefore, dynamic FCCs should be directly calculated from the differential equations for metabolite concentrations and sensitivities.     

Toxicology analysis by means of the JSM-method

MOTIVATION: A model for learning potential causes of toxicity from positive and negative examples and predicting toxicity for the dataset used in the Predictive Toxicology Challenge (PTC) is presented. The learning model assumes that the causes of toxicity can be given as substructures common to positive examples that are not substructures of negative examples. This assumption results in the choice of a learning model, called the JSM-method, and a language for representing chemical compounds, called the Fragmentary Code of Substructure Superposition (FCSS). By means of the latter, chemical compounds are represented as sets of substructures which are 'biologically meaningful' from the expert point of view. RESULTS: The chosen learning model and representation language show comparatively good performance for the PTC dataset: for three sex/species groups the predictions were ROC optimal, for one group the prediction was nearly optimal. The predictions tend to be conservative (few predictions and almost no errors), which can be explained by the specific features of the learning model. AVAILABILITY: by request to finn@viniti.ru; serge@viniti.ru, http://ki-www2.intellektik.informatik.tu-darmstadt.de/~jsm/QDA.     

Identification of EEG patterns occurring in anesthesia by means of autoregressive parameters.

In EEG analysis an automatic pattern recognition is of interest. In this paper the usefulness of autoregressive parameters to classify EEG segments recorded during anesthesia is examined. Assuming that the AR parameters are multivariate normally distributed, parametric methods of discriminant analysis can be applied. The results show that AR parameters have high discriminating power and that the lowest error classification rate (smaller than 3%) is obtained by using quadratic discriminant functions. Consequently autoregressive parameters are efficient for classifying EEG segments into general stages of anesthesia.     

Evaluation of diffusion coefficients by means of an approximate steady-state condition in sedimentation velocity distributions

This investigation examined the feasibility of manipulating the rotor speed in sedimentation velocity experiments to spontaneously generate an approximate steady-state condition where the extent of diffusional spreading is matched exactly by the boundary sharpening arising from negative s–c dependence. Simulated sedimentation velocity distributions based on the sedimentation characteristics for a purified mucin preparation were used to illustrate a simple procedure for determining the diffusion coefficient from such steady-state distributions in situations where the concentration dependence of the sedimentation coefficient, s = s⁰/(1 + Kc), was quantified in terms of the limiting sedimentation coefficient as c → 0 (s⁰) and the concentration coefficient (K). Those simulations established that spontaneous generation of the approximate steady state could well be a feature of sedimentation velocity distributions for many unstructured polymer systems because the requirement that Kc_oω²s⁰/D be between 46 and 183 cm⁻² is not unduly restrictive. Although spontaneous generation of the approximate steady state is also a theoretical prediction for structured macromolecular solutes exhibiting linear concentration dependence of the sedimentation coefficient, s = s⁰(1 − kc), the required value of k is far too large for any practical advantage to be taken of this approach with globular proteins.     

Basic steps of EEG topogram analysis development by the Livanov's school

The basic steps of development of the topogram analysis technique are outlined with its prerequisites. A topogram is defined as a set of momentary EEG values simultaneously recorded from the whole scalp surface with multiple electrodes. Experimental evidence points to existence of two main types of the spatiotemporal organization of the cortical potentials varying in time in the whole range of the EEG frequencies. Animal and human experimental data are described which reveal either dominance of one of these types or their complex interaction.     

Oxygen transfer coefficients by dynamic model moment analysis

A new method to estimate the oxygen transfer coefficient (K_La) from the experimental dynamic response data is presented. Employing a linear model which allows for gas phase, diffusion film, and oxygen electrode dynamics, the first moment of the response curve is simply related to the sum of the model parameters. Two separate experiments are used to characterize the measurement dynamics and to measure the unknown K_La parameter. The simple calculation procedure involves only measuring the area above the response curves.     

Pharmaco-EEG analysis by means of FFT and FAD

The EEG effects of a single oral dose of diazepam, amitriptyline and pernazine were studied in 26 healthy volunteers. The EEG analysis was performed by means of FFT and a new parametric method FAD. The results indicate that the FAD method reveals drug changes significantly more often than does the FFT analysis and that the medication effects are more clearly defined by the FAD. The method can be useful in the assessment of the subtle effects of the psychotropic drugs.     

Single-event-related potential analysis by means of fragmentary decomposition

 A recently developed fragmentary decomposition method is employed to analyse single-trial event-related potentials (ERPs), thereby extending the traditional method of averaging. Using a conventional auditory oddball paradigm with 40 target stimuli, single-trial ERPs in 40 normal subjects were analysed for midline scalp (Fz, Cz and Pz) recording sites. The normalization effect, reported in our previous study of eye blink EMGs and proposed to be a characteristic property of a wide class of non-stationary physiological processes, was found to apply to these single-trial ERPs. Fragmentary decomposition of single-trial ERPs may be regarded as re-statement of the normalization effect. This allows both pre-stimulus EEGs and post-stimulus ERPs to be regarded as overlapping generic mass potentials (GMPs), with a characteristic Gaussian amplitude spectrum. On theoretical and empirical grounds we uniquely deduce a model GMP using an introduced “bud” function, and physically support it by the resting and transient conditions. The model takes into account the shape of the component, which suggests a simple relationship between the peak latency and the time of the component onset. Given that GMPs may be manipulated and sorted out, we present principles of the fragmentary synthesis, i.e. probabilistic ERP reconstructions on the basis of individual and ensemble properties of its identified components. Summarizing the component quantification in the form of the dynamic model provides for the first time the opportunity to quantify all significant components in single-trial ERPs. This method of single-trial analysis opens up new possibilities of exploring the dynamical ERP changes within a recording trial, particularly in late component “cognitive” paradigms. Received: 29 August 2000 / Accepted in revised form: 5 February 2001     

Cytogenetic analysis of the tomato genome by means of induced deficiencies

Cytological studies of 74 deficiencies of tomato chromosomes induced by radiation and identified by the pseudo-dominant technique reveal the loci of 35 genes on 18 of the 24 arms of the complement. These findings integrated with data obtained from various trisomic types establish centromere positions, orientation of linkage groups, and markers on all but three of the arms. The prospects of obtaining a specific kind of deficiency for a given region were found to depend on : (1) kind of radiation applied, (2) (non-random) breakage frequency in different parts of the chromosome, (3) stability of broken ends, (4) tolerance of deficiency in different parts of the genome, and (5) relative vigor of the mutant homozygote used to detect the deficiency. Aspects of the frequently observed non-homologous pairing phenomenon are presented and discussed. Marker genes whose loci are known appear to be non-randomly distributed between and within chromosomes. Chromosome exchanges as determined by genetic crossing over and cytologically observed chiasmata are likewise non-randomly distributed between and within chromosomes.Research supported in part by a grant (GM 06209) from the National Institutes of Health, U.S. Public Health Service.     

Determination of dendrigraft poly-L-lysine diffusion coefficients by taylor dispersion analysis

This work focuses on the physicochemical characterization of dendrigraft poly-L-lysines (DGLs) obtained by polymerization of N-carboxyanhydride in buffered water (pH 6.5). Diffusion coefficients (D) and hydrodynamic radii (Rh) of five successive DGL generations were determined by Taylor dispersion analysis (TDA). To our knowledge, this is the first experimental work using TDA for the characterization of dendrimer-like structures. Experimental Rh values obtained by TDA were compared to those derived from dynamic light scattering and size exclusion chromatography coupled to a triple detection (refractive index, viscosimetry, and static light scattering). Significant differences were obtained, especially for the highest generations, as a result of the inherent contribution of aggregates to the light scattering intensity. For that reason, TDA was found to be the most appropriate technique for determining the D values of these hyperbranched macromolecules. Regarding their physicochemical behavior, the experimental results confirm that DGLs are very similar to trifunctional dendrimers (exponential growth of the molar mass, almost linear variation of the hydrodynamic radius, high branching density, and maximum of the intrinsic viscosity or of the free volume fraction for generation 4).