John C. Lind

A source-imaging (low-resolution electromagnetic tomography) study of the EEGs from unmedicated males with depression

Imaging studies and quantitative EEG have often, but not consistently, implicated the right hemisphere and the left prefrontal cortex in depression. To help clarify this picture, a spatial filter shown to be effective for enhancing differences between EEG populations was combined with an electrical tomographic approach called low-resolution electromagnetic tomography and used to compare the source-current densities from a group of 25 male subjects with depression and a group of 65 matched controls. To elicit differences, comparisons were made during resting conditions and during verbal and spatial cognitive challenges to the subjects. Estimates of the source-current density were derived from 43-electrode recordings of the EEG reduced to the delta, alpha and beta frequency bands. The depressed subjects were unmedicated and selected according to DSM IV criteria. Regions of significantly increased current density in depression compared to controls were generally right hemispheric, while regions of significantly decreased current density were generally frontal and left hemispheric. A within-group comparison of the depressed subjects during the two cognitive challenges suggested a left anterior functional hypoactivation in depression. Retrospective classification of the two groups indicated that the spatial challenge best separated the groups irrespective of frequency band.

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.

Systematic comparisons of interpolation techniques in topographic brain mapping

The performance of one local interpolation technique, the nearest neighbors, and two global spline techniques, one planar and the other spherical, commonly used for topographic mapping of brain potential data has been quantitatively evaluated. The method of evaluation was one of cross-validation where the potential at each site in a 31-electrode full scalp recording montage is predicted by interpolation from the other sites. Errors between the measured potentials and those predicted by interpolation were quantified using 4 measures defined as inaccuracy, precision, bias and tolerance. The evaluation was applied to the background EEGs from 5 normal volunteers and from 4 patients with epilepsy, tumor or stroke. The results indicate that none of the interpolation techniques performed well and that for localized components in the EEG, the errors can increase almost without limit. Further, the global techniques performed significantly better than the local technique with 2 being the best order for the nearest-neighbor technique and 3 for the spline techniques. It is concluded that interpolation should not be used with electrode densities of the order of that provided by the international 10-20 system neither to increase the spatial resolution of the electroencephalogram nor in more sophisticated analysis techniques in quantitative EEG for estimates such as the radial-current density.

Low-resolution electrical tomography of the brain during psychometrically matched verbal and spatial cognitive tasks

EEGs were recorded from 75 normal, young, female subjects during psychometrically matched verbal (WF) and spatial (DL) cognitive tasks to elicit the differences in the electrical source distribution inside the brain. Recordings were obtained using 43 EEG and 3 guard electrodes then visually edited and spatially filtered to remove extracerebral artifacts. Twenty 1‐sec artifact‐free epochs were obtained and analyzed from 42 and 60 subjects during WF and DL respectively. Of these subjects, 20 were placed in a training set and the remainder into a test set. The baseline for the comparison of the two tasks was established by factoring the average cross‐spectral matrices of the training‐set EEGs, computed in the theta, alpha, and beta frequency bands into spatial patterns common to the two tasks. Only those spatial patterns that contributed to the correct classification of subjects in the test set were included in the source analysis. The source‐current density distributions were obtained using the LORETA‐KEY© algorithm. The results show that the source‐current density distribution is related to the putative functional activity in the brain in all three frequency bands. The electrical effects of the tasks are both most highly localized and lateralized in the theta band. The effects in the alpha and beta bands are much more generalized and are strongly lateralized only during one and the other of the tasks respectively. The conclusion is that WF is mainly a left central and bilateral frontal cerebral process while DL is mainly a right central and bilateral posterior cerebral process. Hum. Brain Mapping 12:144–156, 2001.

Gender Differences in Brain Functional Organization During Verbal and Spatial Cognitive Challenges

This is a quantitative EEG study of gender-related differences in brain function. It is novel in that to elicit gender differences, it was necessary to apply a spatial filter to the EEGs that was effective for suppressing components common to different cognitive states. The study involved estimates of both the source-current power density in the brain and the complex coherence between different regions in the brain, the latter probably unique in EEG source analysis. Gender effects are shown in terms of differences in both lateralized source power and complex coherence in response to verbal and spatial cognitive challenges. The results provide evidence that verbal and spatial challenges are more lateralized in males than in females, that females are more verbal than males, that males are more spatial than females, that females verbalize more interpretively than males and that males verbalize more consequentially than females.

EEG source analysis of chronic fatigue syndrome

Sixty-one dextral, unmedicated women with chronic fatigue syndrome (CFS) diagnosed according to the Fukuda criteria (1994) and referred for investigation by rheumatologists and internists were studied with quantitative EEG (43 channels) at rest with eyes open and during verbal and spatial cognitive activation. The EEGs from the patients were compared with recordings from 80 dextral healthy female controls. Only those subjects who could provide 20 1-s artefact-free segments of EEG were admitted into the study. The analysis consisted of the identification of the spatial patterns in the EEGs that maximally differentiated the two groups and the estimation of the cortical source distributions underlying these patterns. Spatial patterns were analyzed in the alpha (8-13Hz) and beta (14-20Hz) bands and the source distributions were estimated using the Borgiotti-Kaplan BEAMFORMER algorithm. The results indicate that the spatial patterns identified were effective in separating the two groups, providing a minimum correct retrospective classification rate of 72% in both frequency bands while the subjects were at rest to a maximum of 83% in the alpha band during the verbal cognitive condition. Underlying cortical source distributions showed significant differences between the two groups in both frequency bands and in all cognitive conditions. Lateralized cortical differences were evident between the two groups in the both frequency bands during both the verbal and spatial cognitive conditions. During these active cognitive conditions, the CFS group showed significantly greater source-current activity than the controls in the left frontal-temporal-parietal regions of the cortex.

A source-imaging (low-resolution electromagnetic tomography) study of the EEGs from unmedicated men with schizophrenia

Imaging studies and quantitative electroencephalography (EEG) have often, but not consistently, implicated the left hemisphere and the prefrontal cortex in schizophrenia. To help clarify this picture, a spatial filter shown to be effective for enhancing differences between EEG populations was combined with low-resolution electromagnetic tomography and used to compare the source-current densities from a group of 57 male subjects with schizophrenia and a group of 65 matched controls. To elicit differences, comparisons were made during resting conditions and during verbal and spatial cognitive challenges to the subjects. Estimates of the source-current density were derived from 43-electrode recordings of the EEG reduced to the delta, alpha and beta frequency bands. The patients were unmedicated and were selected according to DSM-IV criteria. As a group, they were severe, chronic states with both deficit negative and superimposed florid psychotic symptomatology. The results confirm that schizophrenia is a left-hemispheric disorder centered in the temporal and frontal lobes. They also suggest that, in schizophrenia, functions normally performed by these regions in controls are assumed by homologous regions in the opposite hemispheres.

Discriminant Analysis and Equivalent Source Localization of the EEG Related to Cognitive Functions

Discriminant analysis and EEG source localization methods were employed to compare groups of normal subjects during different cognitive conditions using 43-channel EEG recordings in the alpha (8-13 Hz) frequency band. Recordings were obtained from 69 dextral females during 2 passive conditions, Eyes-Open and Eyes-Closed, and 2 active conditions, Word-Finding and Dot-Localization. The cross-spectral matrix between all of the electrode sites was used to characterize the EEGs obtained during each condition. The subjects were partitioned into training and test sets and quadratic discriminant functions were constructed from the training sets to classify the EEGs. The discriminant functions successfully classified both the training and test sets at rates approaching 80%. The classification was repeated using only the diagonal (power spectral) elements of the cross-spectral matrices in the discriminant functions and this approach was successful in discriminating between the EEGs from the passive cognitive conditions but failed to discriminate between the EEGs from the active conditions. Source localization using a modified MUSIC algorithm indicated that the centers of brain electrical activity that distinguished the Eyes-Closed condition from the Eyes-Open condition were located in the medial occipital and right frontal regions. Centers of electrical activity that distinguished the Word-Finding condition from the Dot-Localization condition were located in the right medial posterior and left temporal regions. Validation of the locations of the centers of activity was accomplished by repeating the classification procedures using the spatial patterns generated on the scalp by dipole current sources placed at these locations.

Robust minimum information loss estimation

Two robust estimators of a matrix-valued location parameter are introduced and discussed. Each is the average of the members of a subsample-typically of covariance or cross-spectrum matrices-with the subsample chosen to minimize a function of its average. In one case this function is the Kullback-Leibler discrimination information loss incurred when the subsample is summarized by its average; in the other it is the determinant, subject to a certain side condition. For each, the authors give an efficient computing algorithm, and show that the estimator has, asymptotically, the maximum possible breakdown point. The main motivation is the need for efficient and robust estimation of cross-spectrum matrices, and they present a case study in which the data points originate as multichannel electroencephalogram recordings but are then summarized by the corresponding sample cross-spectrum matrices.