Residual FRs in post-resection ECoG are prognostic markers for seizure recurrence, especially if their number is high. Tailoring could rely on FRs, but requires careful assessment of the ECoG, as FRs in functionally eloquent areas might not be pathologic.

FRs that persist before and after resection predict poor postsurgical outcome. These findings hold for different tailoring approaches. FRs can thus be used for tailoring epilepsy surgery with repeated intraoperative ECoG measurements. Ann Neurol 2017;81:664-676.

SUMMARYObjective: Children with rolandic spikes may or may not have seizures, ranging from benign rolandic epilepsy to severe atypical rolandic epilepsy. We investigated whether ripples (80-250 Hz), superimposed on rolandic spikes in surface electroencephalography (EEG), can differentiate between different entities. Methods: In this cohort study we analyzed the EEG studies of children with rolandic spikes without other EEG or magnetic resonance imaging (MRI) abnormalities. They were divided into the following three groups: (1) rolandic spikes but no epilepsy, (2) typical rolandic epilepsy, and (3) atypical and symptomatic rolandic epilepsy. Ripples superimposed on rolandic spikes were marked in 10 minutes of EEG, and compared to the number of seizures before the EEG. Receiver operating characteristic (ROC) curves were constructed to determine the predictive value of ripples and spikes for having epilepsy (groups 2 and 3) and for differentiating benign courses (groups 1 or 2) from atypical and symptomatic epilepsy (group 3). Ripples were also marked in the time frequency spectrum of averaged rolandic spikes. Results: Ripples were found in 13 of 22 children. Children without epilepsy showed no ripples, except for a single child with only one ripple. The number of ripples showed a significant positive correlation with the number of seizures (q = 0.70, p = 0.001), whereas spikes had a borderline significant correlation (q = 0.43, p = 0.05). Presence of more than two ripples was a predictor for having seizures (area under the curve [AUC] 0.84), whereas spikes could not predict having seizures (AUC 0.53). More than five ripples predicted the difference between benign courses and atypical and symptomatic epilepsy (AUC 0.91, sensitivity 63%, specificity 100%). Ripples in the time frequency spectra appeared in all children and were not related to seizures. Significance: Absence of ripples on top of rolandic spikes predicts a relative benign clinical entity, whereas in the presence of several ripples, the child is likely to have more seizures than classical rolandic epilepsy, and pharmacologic treatment might be needed.

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ObjectiveNew insights into high‐frequency electroencephalographic activity and network analysis provide potential tools to improve delineation of epileptic tissue and increase the chance of postoperative seizure freedom. Based on our observation of high‐frequency oscillations “spreading outward” from the epileptic source, we hypothesize that measures of directed connectivity in the high‐frequency range distinguish epileptic from healthy brain tissue.MethodsWe retrospectively selected refractory epilepsy patients with a malformation of cortical development or tumor World Health Organization grade I/II who underwent epilepsy surgery with intraoperative electrocorticography for tailoring the resection based on spikes. We assessed directed functional connectivity in the theta (4‐8 Hz), gamma (30‐80 Hz), ripple (80‐250 Hz), and fast ripple (FR; 250‐500 Hz) bands using the short‐time direct directed transfer function, and calculated the total, incoming, and outgoing propagation strength for each electrode. We compared network measures of electrodes covering the resected and nonresected areas separately for patients with good and poor outcome, and of electrodes with and without spikes, ripples, and FRs (group level: paired t test; patient level: Mann‐Whitney U test). We selected the measure that could best identify the resected area and channels with epileptic events using the area under the receiver operating characteristic curve, and calculated the positive and negative predictive value, sensitivity, and specificity.ResultsWe found higher total and outstrength in the ripple and gamma bands in resected tissue in patients with good outcome (rippletotal: P = .01; rippleout: P = .04; gammatotal: P = .01; gammaout: P = .01). Channels with events showed lower total and instrength, and higher outstrength in the FR band, and higher total and outstrength in the ripple, gamma, and theta bands (FRtotal: P = .05; FRin: P < .01; FRout: P = .02; gammatotal: P < .01; gammain: P = .01; gammaout: P < .01; thetatotal: P = .01; thetaout: P = .01). The total strength in the gamma band was most distinctive at the channel level (positive predictive value [PPV]good = 74%, PPVpoor = 43%).SignificanceInterictally, epileptic tissue is isolated in the FR band and acts as a driver up to the (fast) ripple frequency range. The gamma band total strength seems promising to delineate epileptic tissue intraoperatively.

ObjectiveHigh frequency oscillations (HFOs; > 80 Hz), especially fast ripples (FRs, 250–500 Hz), are novel biomarkers for epileptogenic tissue. The pathophysiology suggests enhanced functional connectivity within FR generating tissue. Our aim was to determine the relation between brain areas showing FRs and ‘baseline’ functional connectivity within EEG networks, especially in the high frequency bands.MethodsWe marked FRs, ripples (80–250 Hz) and spikes in the electrocorticogram of 14 patients with refractory temporal lobe epilepsy. We assessed ‘baseline’ functional connectivity in epochs free of epileptiform events within these recordings, using the phase lag index. We computed the Eigenvector Centrality (EC) per channel in the FR and gamma band network. We compared EC between channels that did or did not show events at other moments in time.ResultsFR-band EC was higher in channels with than without spikes. Gamma-band EC was lower in channels with ripples and FRs.ConclusionsWe confirmed previous findings of functional isolation in the gamma-band and found a first proof of functional integration in the FR-band network of channels covering presumed epileptogenic tissue.Significance‘Baseline’ high-frequency network parameters might help intra-operative recognition of epileptogenic tissue without the need for waiting for events. These findings can increase our understanding of the ‘architecture’ of epileptogenic networks and help unravel the pathophysiology of HFOs.

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