Interictal epileptiform discharges (spikes, IEDs) are electrographic markers of epileptic tissue and their quantification is utilized in planning of surgical resection. Visual analysis of long-term multi-channel intracranial recordings is extremely laborious and prone to bias. Development of new and reliable techniques of automatic spike detection represents a crucial step towards increasing the information yield of intracranial recordings and to improve surgical outcome. In this study, we designed a novel and robust detection algorithm that adaptively models statistical distributions of signal envelopes and enables discrimination of signals containing IEDs from signals with background activity. This detector demonstrates performance superior both to human readers and to an established detector. It is even capable of identifying low-amplitude IEDs which are often missed by experts and which may represent an important source of clinical information. Application of the detector to non-epileptic intracranial data from patients with intractable facial pain revealed the existence of sharp transients with waveforms reminiscent of interictal discharges that can represent biological sources of false positive detections. Identification of these transients enabled us to develop and propose secondary processing steps, which may exclude these transients, improving the detector's specificity and having important implications for future development of spike detectors in general.

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SUMMARYPurpose: Variable predictors of postsurgical seizure outcome have been reported in children with tuberous sclerosis complex (TSC). We analyzed a large surgical series of pediatric TSC patients in order to identify prognostic factors crucial for selection of subjects for epilepsy surgery. Methods: Thirty-three children with TSC who underwent excisional epilepsy surgery at Miami Children's Hospital were retrospectively reviewed. A total of 29 clinical, neuropsychological, electroencephalography (EEG), magnetic resonance imaging (MRI), and surgical variables were analyzed and related to seizure outcomes. Univariate Barnard's exact test, Wilcoxon's rank-sum test, and multivariate statistical Cox's model were used to examine the significance of associations between the variables and seizure outcome. Key Findings: Eighteen patients (55%) have been seizure-free 2 years after (final) surgery; postoperative complications occurred in five subjects (15%). Complete removal of epileptogenic tissue detected by both MRI and intracranial EEG, regional scalp interictal EEG patterns, and agreement of interictal and ictal EEG localization were the most powerful predictors of seizure-free outcome. Other significant predictors included occurrence of regional scalp ictal EEG patterns, fewer brain regions affected by tubers, presence of preoperative hemiparesis, and one-stage surgery. Remaining factors such as age at seizure onset, incidence of infantile spasms or other seizure types, duration of epilepsy, seizure frequency, mental retardation, as well as types and extent of resections did not influence outcome. Significance: Perioperative features rather than preoperative variables are the most important determinants of postsurgical seizure outcome in patients with TSC. Our findings may assist in the surgical management of these patients.