Identification of the temporal components of seizure onset in the scalp EEG

Background: The identification of the earliest indication of rhythmical osc illations and paroxysmal events associated with an epileptic seizure is par amount in identifying the location of the seizure onset in the scalp EEG. I n this work, data-dependent filters are designed that can help reveal obscu re activity at the onset of seizures in problematic EEGs. Methods: Data-dep endent filters were designed using temporal patterns common to selected seg ments from pre-ictal and ictal portions of the scalp EEG. Temporal patterns that accounted for more variance in the ictal segment than in the pre-icta l segment of the scalp EEG were used to form the filters. Results: Applicat ion of the filters to the scalp EEG revealed temporal components in the sei zure onset in the scalp recording that were not obvious in the unfiltered E EG. Examination of the filtered EEG enabled the onset of the seizure to be recognized earlier in the recording. The utility of the filters was confirm ed qualitatively by comparing the scalp recording to the intracranial. reco rding and quantitatively by calculating correlation coefficients between th e scalp and intracranial recordings before and after filtering. Conclusion: The data-dependent approach to EEG filter design allows automatic detectio n of the basic frequencies present in the seizure onset. This approach is m ore effective than narrow band-pass filtering for eliminating artifactual a nd other interference that can obscure the onset of a seizure. Therefore, t emporal-pattern filtering facilitates the identification of seizure onsets in challenging scalp EEGs.