A global scale factor in brain topography

Generalized background qEEG abnormalities in localized symptomatic epilepsy

Spectral features of EEG background activity were studied in patients with localized symptomatic epilepsy (LSE), with origin in the frontal or temporal lobes. Z-values of high resolution spectra and measures of the parametric (xi alpha) model of the EEG were obtained for all 10/20 System leads and were compared with those obtained in a control group. Comparisons were performed between syndromic variants of LSE and between subgroups of patients with or without paroxysmal activity in their digital EEGs (dEEG). Marked reduction of the energy in the alpha range and a mild increase in the theta range were found in the patients, unrelated to the syndromic variant of the epilepsy. These deviations from normality were widespread on the scalp and were not related to antiepileptic medication. Non-parametric testing showed a positive correlation between the magnitude of the quantitative EEG abnormalities and the amount of paroxysmal activity in the dEEG. Slowing of the mean frequency of alpha components of the spectra, an actual decrease of power in the alpha range and an increase in the theta range explained the results. The most striking finding of this paper is that focal epileptogenesis may have a generalized impact in the frequency composition of EEG.

The estimation of event related potentials affected by random shifts and scalings

There is considerable evidence for trial to trial variability of the event related potentials (ERPs) within a given subject's recording. This variability influences the outcome of usual procedures in ERP analysis. Better results may be obtained if the sources of variability are explicitly taken into account in an appropriate model. This paper considers a probabilistic model, the random shift and scaling (RSS) model, where the response is modified by a random time shift and a random scale factor. In addition to this, an additional random scale factor which affects both the response and the background noise is taken into account. This time shift and these scale factors are handled as nuisance parameters. Maximum likelihood and least squares estimators of these parameters and the waveform of response are derived for the RSS model. It is shown that the Woody estimate of the ERP reported in earlier work can be derived by restricting the assumptions for the RSS model. Test statistics for hypotheses on means are obtained for the RSS model and a new type of discriminant function. The usefulness of the method is illustrated by means of simulation studies. Receiver operating characteristic (ROC) curves are used to demonstrate that the new type of discriminant performs better than the usual Fisher's Linear Discriminant.