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Objective: Wavelet-crosscorrelation analysis is a new application of wavelet analysis used to show the propagation of epileptiform discharges and to localize the corresponding lesions. We have shown previously that this analysis can help predict brain conditions statistically (Mizuno-Matsumoto et al. 2002). Our objective was to assess whether wavelet-crosscorrelation analysis reveals the initiation and propagation of epileptiform activity in human patients., Methods: The data obtained from three patients with simple partial seizures (SPS) using whole-head magnetoencephalography (MEG) were analyzed by the wavelet-crosscorrelation method. Wavelet-crosscorrelation coefficients (WCC), the coherent structure of each possible pair of signals from 64 MEG channels forvarious periods, and the time lag (TL) in two related signals, were ascertained., Results: We clearly demonstrated both localization of the irritative zone and propagation of the epileptiform discharges., Conclusions: Wavelet-crosscorrelation analysis can help reveal and visualize the dynamic changes of brain conditions. The method of this analysis can compensate for other existing methods for the analysis of MEG, electroencephalography (EEG) or Elecotrocorticography (ECoG)., Significance: Our proposed method suggests that revealing and visualizing the dynamic changes of brain conditions can help clinicians and even patients themselves better understand such conditions.

SAM(g2) analysis, a combination of synthetic aperture magnetometry (SAM) and excess kurtosis (g2) method, is a novel epilepsy analysis procedure based on a spatial filtering technique. By producing a three-dimensional image of the g2 values and superimposing them onto a patient's MR images, this analysis can automatically estimate spike localization from raw MEG epilepsy signals including spikes. The aim of this study is to examine SAM(g2) analysis using MEG signals of an epileptic patient, whose clinical symptoms of colored elementary visual auras had ceased in accordance with the changes of the estimated localizations of the equivalent current dipoles (ECDs) of the interictal spikes. His visual auras were experienced in 1997, while they ceased in 1999 with effective medication. The patient provided written informed consent for the experimental procedures. The MEG signals were recorded in 1997 and 1999, and were analyzed using both ECD and SAM(g2) analyses. For the MEG signals of 1997, ECD analysis estimated most of the interictal spikes in the right fusiform and inferior temporal gyri, which subserve human color processing. SAM(g2) analysis also estimated them in the same areas. For those of 1999, both ECD and SAM(g2) analyses estimated them in the right transverse gyrus of Heschl. As well as ECD analysis, SAM(g2) analysis successfully estimated the changes of the localizations of the interictal spikes in accordance with the changes of the patient's clinical symptoms, indicating that SAM(g2) analysis is useful for detection of interictal spike localization in epileptic patients.

Objective: Extraoperative cortical localizing stimulation (LS) is a standard clinical tool used to assess brain function before epilepsy surgery. However, LS can produce unwanted afterdischarges (ADs). We previously have shown that brief pulses of electrical stimulation (BPS) can terminate ADs caused by cortical stimulation. Our objective was to assess whether wavelet-crosscorrelation analysis could help predict the conditions under which BPS would be most likely to terminate ADs., Methods: We used wavelet-crosscorrelation analysis to get wavelet-correlation coefficients (WCC), and determine time lag (TL) and absolute value of TL (ATL) between two electrodes. For Analysis-1, we compared WCC and ATL in epoch 1 which was before LS, epoch 2 which was after LS but before BPS, and epoch 3 which was after BPS. For Analysis 2, we compared WCC and ATL during epoch 1 under 4 conditions: epochs when ADs subsequently terminated within 2 s after the end of BPS (1A), terminated within 2-5 s (1B), did not terminate within 5 s (1C), and when ADs did not appear (1D)., Results: We found that BPS efficacy in terminating ADs was predicted by (1) low correlation and (2) slow propagation speed between electrode pairs in the 2-10 s period before stimulation., Conclusions: Wavelet-crosscorrelation analysis can help predict conditions during which BPS can abort ADs. It is possible that similar analyses could help predict when BPS or other interventions could abort clinical seizures.

The main objectives of the preoperative evaluation of a patient with medically intractable epileptic seizures are localization of the foci and propagation of the epileptiform discharges. Electrocorticographic (ECoG) data of intractable focal epilepsy were analyzed using an AR model, wavelet analysis, and cross-correlation analysis. In order to derive the time-shifts, the cross correlations of the epileptiform discharges were calculated between electrodes for every unit of time. Further analyses were made by means of a set of contour maps of the time-shifts and sequential two- and three-dimensional visualizations of the time-shift maps in order to localize the epileptic foci and study their propagation process. Two types of foci and propagation were revealed in the results. In the first type, epileptiform discharges were generated at localized focal sites and spread quickly to other sites. In the second type, the foci of epileptiform discharges, which appeared soon after the former bursts, were localized at more than one site, and the discharges tended to spread more slowly. The findings suggest that epileptic phenomena can be caused by at least two kinds of mechanisms in one patient: in the former, the propagation might be mediated through synaptic projections, while in the latter, the extracellular diffusion of an excitatory factor might play an important role. In addition, our newly developed visualization technique for the localization of epileptic foci and the propagation of epileptiform discharges should prove useful in the study of epileptogenesis etiology.