Z.J. Koles

Spatio-temporal decomposition of the EEG: a general approach to the isolation and localization of sources

The principal-component method of source localization for the background EEG is generalized to arbitrary spatio-temporal decompositions. It is shown that as long as the spatial patterns of the decomposition span the same signal space as the principal spatial components, the computational process of attempting to localize the sources is the same. Decompositions other than the principal components are shown to be superior for the EEG in that they appear to enable individual sources to be better isolated. An example is given using the common spatial pattern decomposition and using a raw varimax rotation of a subset of the common spatial patterns. The results show that the principal component decomposition is almost ineffective for isolating spike and sharp wave activity in an EEG from a patient with epilepsy, that the common spatial pattern decomposition is significantly better and that the varimax rotation is better yet. That the varimax rotation is best is demonstrated by attempting to locate dipole sources inside the brain which account for the spike and sharp wave activity on the scalp. The question which remains is whether there exists some oblique rotation of the basis vectors of the EEG signal space which is optimal for isolating individual sources.

Spatial patterns in the background EEG underlying mental disease in man.

The spatial patterns underlying differences in the background EEGs of schizophrenic, manic and depressed patients and a group of normal controls has been examined during the eyes open and eyes closed resting conditions and during 3 cognitive tasks. The method of principal-component analysis was used to extract spatial patterns which are common to the EEGs of 2 groups but which account for maximally different proportions of the combined variances. The common spatial patterns in all possible pairings of the groups were used to extract variance-related feature vectors from the individual EEG epochs in the 2 groups and the means of these vectors were subjected to statistical analyses. The results of these analyses indicate that there are significant differences in the EEGs from all 4 of the groups. The spatial patterns underlying the features which are significantly different in each comparison are shown graphically and used to suggest which brain regions might be implicated in each of the psychiatric conditions and how these are affected by the cognitive condition. The main results are that the EEGs in the schizophrenic group can be characterized by left-sided hyperactivity, in the depressed group by right-sided hyperactivity and in the manic group by bilateral hyperactivity and that these characteristics are best elicited by different cognitive states.

Computed radial-current topography of the brain: patterns associated with the normal and abnormal EEG ☆

We describe a method for producing estimates of radial-current topography underlying the background EEG. This method is based on the application of the laplacian operator to potentials measured on the scalp using a 31-electrode recording array. The laplacian is applied analytically to a potential surface obtained by bicubic-spline interpolation of the measurements at the electrode sites. The results obtained when the method was applied to the alpha rhythm recorded from a normal volunteer and to the slow wave activity recorded from a neurologic patient are presented. The alpha rhythm is associated with areas of strong radial-current activity in the occipital regions (although dominantly right); for the slow rhythm the activity appears in the medial-frontal region. The radial-current topography for the alpha rhythm suggests rotating dipole generators in the occipital lobes whereas it is suggestive of a radially oriented dipole in the case of the delta activity. Discussion is focused upon the apparent advantages of radial-current topography for localizing brain electrical activity, upon the strengths and weaknesses of the method, and upon the observation that the topography of radial current activity obtained would have been difficult to predict from a visual examination of raw EEG traces alone.

The Effects of Dialysis on Brain Water and EEG in Stable Chronic Uremia

Cerebral edema in uremic animals and humans, as well as an EEG deterioration in humans, has been reported after dialysis. Both are manifestations of the dialysis disequilibrium syndrome (DDS). This study was designed to analyze the changes induced by dialysis in the EEG pattern (spectral analysis), in the cerebral hydration, and ventricular size (computed tomography [CT] of the brain) in a group of 11 stable uremic patients. They volunteered for a randomized crossover study of 4 months each of standard hemodialysis (HD) and hypertonic hemodiafiltration (H HDF). H HDF is a dialysis technique that is shorter and more efficient than HD. An EEG recording, a CT scan of the brain, and blood biochemistry were performed before and after a HD (four hours, blood flow rate 250 mL/min) and a H HDF run (three hours, blood flow rate 400 mL/min). Approximately 6 weeks of stabilization on each treatment were allowed before these studies. No difference was found in the density of seven specific brain structures (base and apical cuts), when comparing pre- v post-HD, pre- v post-H HDF, pre- HD v pre-H HDF, and post-HD v post-H HDF. Furthermore, no difference was evident either in the bicaudate diameter of the lateral ventricles or in the transverse diameter of the third ventricle. In addition, no significant in-between- and within-treatment difference was observed when analyzing the EEG% power (3-7/7-13 Hz) data. In conclusion, this study shows neither a postdialysis change in brain density and ventricular size nor a postdialysis EEG deterioration in a group of stable uremic patients undergoing both a rapid and a standard dialysis treatment.(ABSTRACT TRUNCATED AT 250 WORDS)

Mental activity and the e.e.g.: Task and workload related effects

The e.e.g. was recorded from the left and right parietal and temporal regions of the scalps of 23 normal subjects while they were mentally at rest and then while they were executing tasks intended to engage, firstly, their dominant cerebral hemispheres, and secondly then their nondominant hemispheres. In each of the alpha and gamma frequency bands, 43 features of the e.e.g. expressed in terms of average power densities, coefficients of power density variation, coherencies and phases were calculated for each of the subjects. A method of separating the features which were related to the nature of the mental task from those which were related only to the mental workload represented by each of the tasks is presented. Of the features considered, many were found to be workload related, but only five, namely a power density variance, a right to left power ratio, an anterior to posterior phase angle and two coherency ratios, showed task-dependent behaviour. In this latter group, only two features point to the lateralisation of verbal and spatial cognitive processes to the dominant and nondominant cerebral hemispheres. The problem of the confounding of cerebral and mygenic effects and possible bias in the results owing to this effect is discussed.

Topographic mapping of the EEG: an examination of accuracy and precision.

SummaryThe accuracy and precision of topographic maps depicting scalp potentials and scalp potentials squared have been examined. Electrode placement was that specified by the International 10–20 System and the methods of interpolation bilinear and bicubic splines. The results indicate that, for these interpolation methods, the maximum error expected between the measured scalp quantities and those predicted by interpolation is positively correlated to the root-mean-square value of the measured quantity. Both interpolation methods produce accurate estimates of the interelectrode quantities. Both methods produce precise estimates of the scalp potential in the delta, theta and alpha frequency bands but only poor estimates in the beta band. The precision of the estimates of the scalp potentials squared is poor in all frequency bands. This result indicates that another look at the now common practice of topographically mapping the power-spectral components of the EEG is in order. In general, the bilinear and bicubic spline methods of interpolation perform about equally. This result is used to suggest that because of its additional computational complexity, use of the bicubic method for potential mapping may not be warranted. Advantages of the bicubic method, particularly in radial-current mapping, are however discussed.

A spatial power spectrum analysis of the electroencephalogram

SummaryThe method of spatial power-spectrum analysis has been applied to measurements of the distribution of rms alpha-band potential on the scalp. Data was recorded using the 31-Electrode System and spatial power-spectrum estimates (PSEs) were obtained from Mercator projections of the potential interpolated using the triangular method. PSEs were calculated using the Lim and Malik algorithm for maximum-entropy power-spectrum estimation. In order to investigate the utility of spatial power-spectrum analysis, PSEs were obtained from subjects in two conditions; resting with eyes closed (EC) and resting with eyes open and fixed on a single point (EO). A stepwise discriminant analysis was performed with features from the PSEs and the resultant discriminant function was applied to data not considered in the formulation of the function. Over 92% of test data was correctly classified. The features used in the discriminant function identify spatial waves which are most useful in separating data. The results demonstrate that waves oriented along front-back and right-left lines are most important in separating data into EC and EO groups.