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Source localization using single current dipoles estimates equivalent centers of the spiking gray matter. The extent of the active cortex, however, is difficult to assess from scalp EEG because of the unknown individual volume conduction. The spatial scatter of dipole localizations of single spikes has been proposed as a measure of extent. Single spike localization, however, is strongly dependent on the signal-to-noise ratio (SNR), that is, the ratio of spike and background EEG amplitudes. On the other hand, averaging of all spikes yields only the localization of equivalent centers of activity. We investigated the influence of SNR and multiple subaverages on the estimation of spatial extent by comparing the localization scatter of 100 single spikes in 27 spike types of 25 epilepsy patients with 1000 different subaverages computed by random sampling and bootstrapping. Averaging increased SNR and therefore allowed for localization not only at the spike peak but also during spike onset when less cortex is active. In several subjects with known cortical lesions, the single spike scatter considerably exceeded the lesion. Single dipole scatter was highly correlated with SNR (r = -0.83, P < 0.0001) and was greatly reduced when analyzing multiple subaverages of 10, 25, 50, and 100 spikes. Thus, we found a dominant role of the SNR on the estimated extent and improvement by scatterplots based on the dipole localization of randomly sampled subaverages.

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The comparative sensitivity of EEG and magnetoencephalography (MEG) in the visual detection of focal epileptiform activity in simultaneous interictal sleep recordings were investigated. The authors examined 14 patients aged 3.5 to 17 years with localization-related epilepsy. Simultaneous 122-channel whole-head MEG and 33-channel EEG were recorded for 20 to 40 minutes during spontaneous sleep. The EEG and MEG data were separated and four blinded independent reviewers marked the presence and timing of epileptic discharges (ED) in the 28 data segments. EEG and MEG data were matched and spikes identified by at least three reviewers were classified in three categories according to the following criteria: type 1 MEG > EEG, type 2 EEG > MEG (type 1/2: difference of three or more raters), and type 3 EEG = MEG (three or more raters each). The presence of simultaneous sleep changes was visually determined for every single EEG-segment. Spikes with high spatiotemporal correlation were averaged and subjected to single dipole analysis of peak activity in EEG. Out of 4704 marked patterns, 1387 spikes fulfilled the above criteria. In fact, more spikes were unique to MEG (689) than to EEG (136) and to the combination of both modalities (562). ED were detected predominantly by MEG in eight patients and by EEG in two patients. The presence of vertex waves and spindles lead to a significantly higher number of spikes identified only in MEG. Averaging of type 1 spikes produced clear spike activity in EEG in 9 of 12 cases. On the contrary, only 2 of 10 type 2 spikes were visible in MEG after averaging. Dipoles of spikes visible in MEG showed a more tangential orientation compared with more radial dipoles of type 2 spikes. Spike characteristics, e.g., dipole orientation, are a key factor for a sole EEG representation. Exclusive MEG detection is more likely influenced by overlapping background activity in EEG. Because MEG is indifferent to radial activity, i.e., sleep changes, a higher ratio of spikes unique to MEG compared with EEG is detected in the case of overlapping sleep changes.