Increased gamma and decreased fast ripple connections of epileptic tissue: A high-frequency directed network approach.

OBJECTIVE: New 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. METHODS: We 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. RESULTS: We 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%). SIGNIFICANCE: Interictally, 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.

Tailoring epilepsy surgery with fast ripples in the intraoperative electrocorticogram.

OBJECTIVE: Intraoperative electrocorticography (ECoG) can be used to delineate the resection area in epilepsy surgery. High-frequency oscillations (HFOs; 80-500 Hz) seem better biomarkers for epileptogenic tissue than spikes. We studied how HFOs and spikes in combined pre- and postresection ECoG predict surgical outcome in different tailoring approaches. METHODS: We, retrospectively, marked HFOs, divided into fast ripples (FRs; 250-500 Hz) and ripples (80-250 Hz), and spikes in pre- and postresection ECoG sampled at 2,048 Hz in people with refractory focal epilepsy. We defined four groups of electroencephalography (EEG) event occurrence: pre+post- (+/-), pre+post+ (+/+), pre-post+ (-/+) and pre-post- (-/-). We subcategorized three tailoring approaches: hippocampectomy with tailoring for neocortical involvement; lesionectomy of temporal lesions with tailoring for mesiotemporal involvement; and lesionectomy with tailoring for surrounding neocortical involvement. We compared the percentage of resected pre-EEG events, time to recurrence, and the different tailoring approaches to outcome (seizure-free vs recurrence). RESULTS: We included 54 patients (median age, 15.5 years; 25 months of follow-up; 30 seizure free). The percentage of resected FRs, ripples, or spikes in pre-ECoG did not predict outcome. The occurrence of FRs in post-ECoG, given FRs in pre-ECoG (+/-, +/+), predicted outcome (hazard ratio, 3.13; confidence interval = 1.22-6.25; p = 0.01). Seven of 8 patients without spikes in pre-ECoG were seizure free. The highest predictive value for seizure recurrence was presence of FRs in post-ECoG for all tailoring approaches. INTERPRETATION: 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.

High-frequency oscillations: The state of clinical research.

Modern electroencephalographic (EEG) technology contributed to the appreciation that the EEG signal outside the classical Berger frequency band contains important information. In epilepsy, research of the past decade focused particularly on interictal high-frequency oscillations (HFOs) > 80 Hz. The first large application of HFOs was in the context of epilepsy surgery. This is now followed by other applications such as assessment of epilepsy severity and monitoring of antiepileptic therapy. This article reviews the evidence on the clinical use of HFOs in epilepsy with an emphasis on the latest developments. It highlights the growing literature on the association between HFOs and postsurgical seizure outcome. A recent meta-analysis confirmed a higher resection ratio for HFOs in seizure-free versus non-seizure-free patients. Residual HFOs in the postoperative electrocorticogram were shown to predict epilepsy surgery outcome better than preoperative HFO rates. The review further discusses the different attempts to separate physiological from epileptic HFOs, as this might increase the specificity of HFOs. As an example, analysis of sleep microstructure demonstrated a different coupling between HFOs inside and outside the epileptogenic zone. Moreover, there is increasing evidence that HFOs are useful to measure disease activity and assess treatment response using noninvasive EEG and magnetoencephalography. This approach is particularly promising in children, because they show high scalp HFO rates. HFO rates in West syndrome decrease after adrenocorticotropic hormone treatment. Presence of HFOs at the time of rolandic spikes correlates with seizure frequency. The time-consuming visual assessment of HFOs, which prevented their clinical application in the past, is now overcome by validated computer-assisted algorithms. HFO research has considerably advanced over the past decade, and use of noninvasive methods will make HFOs accessible to large numbers of patients. Prospective multicenter trials are awaited to gather information over long recording periods in large patient samples.

Ripples on rolandic spikes: A marker of epilepsy severity.

OBJECTIVE: 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 (ρ = 0.70, p = 0.001), whereas spikes had a borderline significant correlation (ρ = 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.

Ripples on spikes show increased phase-amplitude coupling in mesial temporal lobe epilepsy seizure-onset zones.

OBJECTIVE: Ripples (80-150 Hz) recorded from clinical macroelectrodes have been shown to be an accurate biomarker of epileptogenic brain tissue. We investigated coupling between epileptiform spike phase and ripple amplitude to better understand the mechanisms that generate this type of pathologic ripple (pRipple) event. METHODS: We quantified phase amplitude coupling (PAC) between epileptiform electroencephalography (EEG) spike phase and ripple amplitude recorded from intracranial depth macroelectrodes during episodes of sleep in 12 patients with mesial temporal lobe epilepsy. PAC was determined by (1) a phasor transform that corresponds to the strength and rate of ripples coupled with spikes, and a (2) ripple-triggered average to measure the strength, morphology, and spectral frequency of the modulating and modulated signals. Coupling strength was evaluated in relation to recording sites within and outside the seizure-onset zone (SOZ). RESULTS: Both the phasor transform and ripple-triggered averaging methods showed that ripple amplitude was often robustly coupled with epileptiform EEG spike phase. Coupling was found more regularly inside than outside the SOZ, and coupling strength correlated with the likelihood a macroelectrode's location was within the SOZ (p < 0.01). The ratio of the rate of ripples coupled with EEG spikes inside the SOZ to rates of coupled ripples in non-SOZ was greater than the ratio of rates of ripples on spikes detected irrespective of coupling (p < 0.05). Coupling strength correlated with an increase in mean normalized ripple amplitude (p < 0.01), and a decrease in mean ripple spectral frequency (p < 0.05). SIGNIFICANCE: Generation of low-frequency (80-150 Hz) pRipples in the SOZ involves coupling between epileptiform spike phase and ripple amplitude. The changes in excitability reflected as epileptiform spikes may also cause clusters of pathologically interconnected bursting neurons to grow and synchronize into aberrantly large neuronal assemblies.

Robust compression and detection of epileptiform patterns in ECoG using a real-time spiking neural network hardware framework.

Interictal Epileptiform Discharges (IED) and High Frequency Oscillations (HFO) in intraoperative electrocorticography (ECoG) may guide the surgeon by delineating the epileptogenic zone. We designed a modular spiking neural network (SNN) in a mixed-signal neuromorphic device to process the ECoG in real-time. We exploit the variability of the inhomogeneous silicon neurons to achieve efficient sparse and decorrelated temporal signal encoding. We interface the full-custom SNN device to the BCI2000 real-time framework and configure the setup to detect HFO and IED co-occurring with HFO (IED-HFO). We validate the setup on pre-recorded data and obtain HFO rates that are concordant with a previously validated offline algorithm (Spearman's ρ = 0.75, p = 1e-4), achieving the same postsurgical seizure freedom predictions for all patients. In a remote on-line analysis, intraoperative ECoG recorded in Utrecht was compressed and transferred to Zurich for SNN processing and successful IED-HFO detection in real-time. These results further demonstrate how automated remote real-time detection may enable the use of HFO in clinical practice.

Seizure Outcome After Intraoperative Electrocorticography-Tailored Epilepsy Surgery: A Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Tailoring epilepsy surgery using intraoperative electrocorticography (ioECoG) has been debated, and modest number of epilepsy surgery centers apply this diagnostic method. We assessed the current evidence to use ioECoG-tailored epilepsy surgery for improving postsurgical outcome. METHODS: PubMed and Embase were searched for original studies reporting on ≥10 cases who underwent ioECoG-tailored surgery for epilepsy, with a follow-up of at least 6 months. We used a random-effects model to calculate the overall rate of patients achieving favorable seizure outcome (FSO), defined as Engel class I, ILAE class 1, or seizure-free status. Meta-regression was used to investigate potential sources of heterogeneity. We calculated the odds ratio (OR) for estimating variables on FSO:ioECoG vs non-ioECoG-tailored surgery (if included studies contained patients with non-ioECoG-tailored surgery), ioECoG-tailored epilepsy surgery in children vs adults, temporal (TL) vs extratemporal lobe (eTL), MRI-positive vs MRI-negative, and complete vs incomplete resection of tissue that generated interictal epileptiform discharges (IEDs). A Bayesian network meta-analysis was conducted for underlying pathologies. We assessed the evidence certainty using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE). RESULTS: Eighty-three studies (82 observational studies, 1 trial) comprising 3,631 patients with ioECoG-tailored surgery were included. The overall pooled rate of patients who attained FSO after ioECoG-tailored surgery was 74% (95% CI 71-77) with significant heterogeneity, which was predominantly attributed to pathologies and seizure outcome classifications. Twenty-two studies contained non-ioECoG-tailored surgeries. IoECoG-tailored surgeries reached a higher rate of FSO than non-ioECoG-tailored surgeries (OR 2.10 [95% CI 1.37-3.24]; p < 0.01; very low certainty). Complete resection of tissue that displayed IEDs in ioECoG predicted FSO better compared with incomplete resection (OR 3.04 [1.76-5.25]; p < 0.01; low certainty). We found insignificant difference in FSO after ioECoG-tailored surgery in children vs adults, TL vs eTL, or MRI-positive vs MRI-negative. The network meta-analysis showed that the odds of FSO was lower for malformations of cortical development than for tumors (OR 0.47 95% credible interval 0.25-0.87). DISCUSSION: Although limited by low-quality evidence, our meta-analysis shows a relatively good surgical outcome (74% FSO) after epilepsy surgery with ioECoG, especially in tumors, with better outcome for ioECoG-tailored surgeries in studies describing both and better outcome after complete removal of IED areas.

Spatial and temporal properties of intra-operatively recorded spikes and high frequency oscillations in focal cortical dysplasia.

OBJECTIVE: Focal cortical dysplasias (FCD) are characterized by distinct interictal spike patterns and high frequency oscillations (HFOs; ripples: 80-250 Hz; fast ripples: 250-500 Hz) in the intra-operative electrocorticogram (ioECoG). We studied the temporal relation between intra-operative spikes and HFOs and their relation to resected tissue in people with FCD with a favorable outcome. METHODS: We included patients who underwent ioECoG-tailored epilepsy surgery with pathology confirmed FCD and long-term Engel 1A outcome. Spikes and HFOs were automatically detected and visually checked in 1-minute pre-resection-ioECoG. Channels covering resected and non-resected tissue were compared using a logistic mixed model, assessing event numbers, co-occurrence ratios, and time-based properties. RESULTS: We found pre-resection spikes, ripples in respectively 21 and 20 out of 22 patients. Channels covering resected tissue showed high numbers of spikes and HFOs, and high ratios of co-occurring events. Spikes, especially with ripples, have a relatively sharp rising flank with a long descending flank and early ripple onset over resected tissue. CONCLUSIONS: A combined analysis of event numbers, ratios, and temporal relationships between spikes and HFOs may aid identifying epileptic tissue in epilepsy surgery. SIGNIFICANCE: This study shows a promising method for clinically relevant properties of events, closely associated with FCD.

Pausing propofol during neurosurgery to record intraoperative electrocorticography is feasible;10 years of clinical experience.

OBJECTIVE: Intraoperative electrocorticography (ioECoG) during neurosurgery is influenced by anesthetics. In our center we stop the propofol to enable interpretation of ioECoG. We reported our clinical experience and evaluated awareness and hemodynamic changes during the propofol-free periods (PFP). METHODS: We retrospectively included surgeries with paused propofol administration to record ioECoG (period: 2008-2019). Clinical reports were screened for symptoms of awareness. We compared mean arterial blood pressure (MAP; mmHg) and heart rate (HR;bpm) during PFP to baseline (ten minutes preceding PFP). An increase > 15% was defined as clinically relevant. The association between hemodynamic changes and clinical characteristics was analyzed using logistic regression models. RESULTS: Propofol administration was paused 742 times in 352 surgeries (mean PFP duration 9 ± 5 min). No signs of awareness were reported. MAP and HR increased > 15% in 54 and six PFPs. Five PFPs showed both MAP and HR increases. Prolonged PFP was associated with having MAP and HR increase during surgery (OR=1.18, 95%CI [1.12-1.26]). CONCLUSIONS: Signs of inadequate sedation depth were rare. MAP and HR increases were related to the length of PFP. SIGNIFICANCE: We summarize 10 years of clinical experience with pausing propofol administration during epilepsy surgery to record ioECoG without evidence of awareness.

Machine learning for (non-)epileptic tissue detection from the intraoperative electrocorticogram.

OBJECTIVE: Clinical visual intraoperative electrocorticography (ioECoG) reading intends to localize epileptic tissue and improve epilepsy surgery outcome. We aimed to understand whether machine learning (ML) could complement ioECoG reading, how subgroups affected performance, and which ioECoG features were most important. METHODS: We included 91 ioECoG-guided epilepsy surgery patients with Engel 1A outcome. We allocated 71 training and 20 test set patients. We trained an extra trees classifier (ETC) with 14 spectral features to classify ioECoG channels as covering resected or non-resected tissue. We compared the ETC's performance with clinical ioECoG reading and assessed whether patient subgroups affected performance. Explainable artificial intelligence (xAI) unveiled the most important ioECoG features learnt by the ETC. RESULTS: The ETC outperformed clinical reading in five test set patients, was inferior in six, and both were inconclusive in nine. The ETC performed best in the tumor subgroup (area under ROC curve: 0.84 [95%CI 0.79-0.89]). xAI revealed predictors of resected (relative theta, alpha, and fast ripple power) and non-resected tissue (relative beta and gamma power). CONCLUSIONS: Combinations of subtle spectral ioECoG changes, imperceptible by the human eye, can aid healthy and pathological tissue discrimination. SIGNIFICANCE: ML with spectral ioECoG features can support, rather than replace, clinical ioECoG reading, particularly in tumors.

Time-frequency analysis of single pulse electrical stimulation to assist delineation of epileptogenic cortex.

Epilepsy surgery depends on reliable pre-surgical markers of epileptogenic tissue. The current gold standard is the seizure onset zone in ictal, i.e. chronic, electrocorticography recordings. Single pulse electrical stimulation can evoke epileptic, spike-like responses in areas of seizure onset also recorded by electrocorticography. Recently, spontaneous pathological high-frequency oscillations (80-520 Hz) have been observed in the electrocorticogram that are related to epileptic spikes, but seem more specific for epileptogenic cortex. We wanted to see whether a quantitative electroencephalography analysis using time-frequency information including the higher frequency range could be applied to evoked responses by single pulse electrical stimulation, to enhance its specificity and clinical use. Electrocorticography data were recorded at a 2048-Hz sampling rate from 13 patients. Single pulse electrical stimulation (10 stimuli, 1 ms, 8 mA, 0.2 Hz) was performed stimulating pairs of adjacent electrodes. A time-frequency analysis based on Morlet wavelet transformation was performed in a [-1 s : 1 s] time interval around the stimulus and a frequency range of 10-520 Hz. Significant (P = 0.05) changes in power spectra averaged for 10 epochs were computed, resulting in event-related spectral perturbation images. In these images, time-frequency analysis of single pulse-evoked responses, in the range of 10-80 Hz for spikes, 80-250 Hz for ripples and 250-520 Hz for fast ripples, were scored by two observers independently. Sensitivity, specificity and predictive value of time-frequency single pulse-evoked responses in the three frequency ranges were compared with seizure onset zone and post-surgical outcome. In all patients, evoked responses included spikes, ripples and fast ripples. For the seizure onset zone, the median sensitivity of time-frequency single pulse-evoked responses decreased from 100% for spikes to 67% for fast ripples and the median specificity increased from 17% for spikes to 79% for fast ripples. A median positive predictive value for the evoked responses in the seizure onset zone of 17% was found for spikes, 26% for ripples and 37% for fast ripples. Five out of seven patients with <50% of fast ripples removed by resection had a poor outcome. A wavelet transform-based time-frequency analysis of single pulse electrical stimulation reveals evoked responses in the frequency range of spikes, ripples and fast ripples. We demonstrate that time-frequency analysis of single pulse electrical stimulation can assist in delineation of the epileptogenic cortex using time-frequency single pulse-evoked fast ripples as a potential new marker.

Spikes and High Frequency Oscillations in Lateral Neocortical Temporal Lobe Epilepsy: Can They Predict the Success Chance of Hippocampus-Sparing Resections?

Purpose: We investigated the distribution of spikes and HFOs recorded during intraoperative electrocorticography (ioECoG) and tried to elaborate a predictive model for postsurgical outcomes of patients with lateral neocortical temporal lobe epilepsy (TLE) whose mesiotemporal structures are left in situ. Methods: We selected patients with temporal lateral neocortical epilepsy focus who underwent ioECoG-tailored resections without amygdalo-hippocampectomies. We visually marked spikes, ripples (80-250 Hz), and fast ripples (FRs; 250-500 Hz) on neocortical and mesiotemporal channels before and after resections. We looked for differences in event rates and resection ratios between good (Engel 1A) and poor outcome groups and performed logistic regression analysis to identify outcome predictors. Results: Fourteen out of 24 included patients had a good outcome. The poor-outcome patients showed higher rates of ripples on neocortical channels distant from the resection in pre- and post-ioECoG than people with good outcomes (p pre = 0.04, p post = 0.05). Post-ioECoG FRs were found only in poor-outcome patients (N = 3). A prediction model based on regression analysis showed low rates of mesiotemporal post-ioECoG ripples (OR mesio = 0.13, p mesio = 0.04) and older age at epilepsy onset (OR = 1.76, p = 0.04) to be predictors of good seizure outcome. Conclusion: HFOs in ioECoG may help to inform the neurosurgeon of the hippocampus-sparing resection success chance in patients with lateral neocortical TLE.

The spatial relationship between the MRI lesion and intraoperative electrocorticography in focal epilepsy surgery.

MRI and intraoperative electrocorticography are often used in tandem to delineate epileptogenic tissue in resective surgery for focal epilepsy. Both the resection of the MRI lesion and tissue with high rates of electrographic discharges on electrocorticography, e.g. spikes and high-frequency oscillations (80-500 Hz), lead to a better surgical outcome. How MRI and electrographic markers are related, however, is currently unknown. The aim of this study was to find the spatial relationship between MRI lesions and spikes/high-frequency oscillations. We retrospectively included 33 paediatric and adult patients with lesional neocortical epilepsy who underwent electrocorticography-tailored surgery (14 females, median age = 13.4 years, range = 0.6-47.0 years). Mesiotemporal lesions were excluded. We used univariable linear regression to find correlations between pre-resection spike/high-frequency oscillation rates on an electrode and its distance to the MRI lesion. We tested straight lines to the centre and the edge of the MRI lesion, and the distance along the cortical surface to determine which of these distances best reflects the occurrence of spikes/high-frequency oscillations. We conducted a moderator analysis to investigate the influence of the underlying pathology type and lesion volume on our results. We found spike and high-frequency oscillation rates to be spatially linked to the edge of the MRI lesion. The underlying pathology type influenced the spatial relationship between spike/high-frequency oscillation rates and the MRI lesion (P spikes < 0.0001, P ripples < 0.0001), while the lesion volume did not (P spikes = 0.64, P ripples = 0.89). A higher spike rate was associated with a shorter distance to the edge of the lesion for cavernomas [F(1,64) = -1.37, P < 0.0001, η 2 = 0.22], focal cortical dysplasias [F(1,570) = -0.25, P < 0.0001, η 2 = 0.05] and pleomorphic xanthoastrocytomas [F(1,66) = -0.18, P = 0.01, η 2 = 0.09]. In focal cortical dysplasias, a higher ripple rate was associated with a shorter distance [F(1,570) = -0.35, P < 0.0001, η 2 = 0.05]. Conversely, low-grade gliomas showed a positive correlation; the further an electrode was away from the lesion, the higher the rate of spikes [F(1,75) = 0.65, P < 0.0001, η 2 = 0.37] and ripples [F(1,75) = 2.67, P < 0.0001, η 2 = 0.22]. Pathophysiological processes specific to certain pathology types determine the spatial relationship between the MRI lesion and electrocorticography results. In our analyses, non-tumourous lesions (focal cortical dysplasias and cavernomas) seemed to intrinsically generate spikes and high-frequency oscillations, particularly at the border of the lesion. This advocates for a resection of this tissue. Low-grade gliomas caused epileptogenicity in the peritumoural tissue. Whether a resection of this tissue leads to a better outcome is unclear. Our results suggest that the underlying pathology type should be considered when intraoperative electrocorticography is interpreted.

High frequency oscillations associate with neuroinflammation in low-grade epilepsy associated tumors.

OBJECTIVE: High frequency oscillations (HFOs) in intraoperative electrocorticography (ioECoG) are thought to be generated by hyperexcitable neurons. Inflammation may promote neuronal hyperexcitability. We investigated the relation between HFOs and inflammation in tumor-related epilepsy. METHODS: We identified HFOs (ripples 80-250 Hz, fast ripples 250-500 Hz) in the preresection ioECoG of 32 patients with low-grade tumors. Localization of recorded HFOs was classified based on magnetic resonance imaging reconstructions: in tumor, in resected non-tumorous area and outside the resected area. We tested if the following inflammatory markers in the tumor or peritumoral tissue were related to HFOs: activated microglia, cluster of differentiation 3 (CD3)-positive T-cells, interleukin 1-beta (IL1ß), toll-like receptor 4 (TLR4) and high mobility group box 1 protein (HMGB1). RESULTS: Tumors that generated ripples were infiltrated by more CD3-positive cells than tumors without ripples. Ripple rate outside the resected area was positively correlated with IL1ß/TLR4/HMGB1 pathway activity in peritumoral area. These two areas did not directly overlap. CONCLUSIONS: Ripple rates may be associated with inflammatory processes. SIGNIFICANCE: Our findings support that ripple generation and spread might be associated with synchronized fast firing of hyperexcitable neurons due to certain inflammatory processes. This pilot study provides arguments for further investigations in HFOs and inflammation.

Are HFOs in the Intra-operative ECoG Related to Hippocampal Sclerosis, Volume and IQ?

Temporal lobe epilepsy (TLE) is the most common form of refractory focal epilepsy and is often associated with hippocampal sclerosis (HS) and cognitive disturbances. Over the last decade, high frequency oscillations (HFOs) in the intraoperative electrocorticography (ioECoG) have been proposed to be biomarkers for the delineation of epileptic tissue but hippocampal ripples have also been associated with memory consolidation. Healthy hippocampi can show prolonged ripple activity in stereo- EEG. We aimed to identify how the HFO rates [ripples (80-250 Hz, fast ripples (250-500 Hz); prolonged ripples (80-250 Hz, 200-500 ms)] in the pre-resection ioECoG over subtemporal area (hippocampus) and lateral temporal neocortex relate to presence of hippocampal sclerosis, the hippocampal volume quantified on MRI and the severity of cognitive impairment in TLE patients. Volumetric measurement of hippocampal subregions was performed in 47 patients with TLE, who underwent ioECoG. Ripples, prolonged ripples, and fast ripples were visually marked and rates of HFOs were calculated. The intellectual quotient (IQ) before resection was determined. There was a trend toward higher rates of ripples and fast ripples in subtemporal electrodes vs. the lateral neocortex (ripples: 2.1 vs. 1.3/min; fast ripples: 0.9 vs. 0.2/min). Patients with HS showed higher rates of subtemporal fast ripples than other patients (Z = -2.51, p = 0.012). Prolonged ripples were only found in the lateral temporal neocortex. The normalized ratio (smallest/largest) of hippocampal volume was correlated to pre-resection IQ (r = 0.45, p = 0.015). There was no correlation between HFO rates and hippocampal volumes or HFO rates and IQ. To conclude, intra-operative fast ripples were a marker for HS, but ripples and fast ripples were not linearly correlated with either the amount of hippocampal atrophy, nor for pre-surgical IQ.

High-frequency oscillations recorded with surface EEG in neonates with seizures.

OBJECTIVE: Neonatal seizures are often the first symptom of perinatal brain injury. High-frequency oscillations (HFOs) are promising new biomarkers for epileptogenic tissue and can be found in intracranial and surface EEG. To date, we cannot reliably predict which neonates with seizures will develop childhood epilepsy. We questioned whether epileptic HFOs can be generated by the neonatal brain and potentially predict epilepsy. METHODS: We selected 24 surface EEGs sampled at 2048 Hz with 175 seizures from 16 neonates and visually reviewed them for HFOs. Interictal epochs were also reviewed. RESULTS: We found HFOs in thirteen seizures (7%) from four neonates (25%). 5025 ictal ripples (rate 10 to 1311/min; mean frequency 135 Hz; mean duration 66 ms) and 1427 fast ripples (rate 8 to 356/min; mean frequency 298 Hz; mean duration 25 ms) were marked. Two neonates (13%) showed interictal HFOs (285 ripples and 25 fast ripples). Almost all HFOs co-occurred with sharp transients. We could not find a relationship between neonatal HFOs and outcome yet. CONCLUSIONS: Neonatal HFOs co-occur with ictal and interictal sharp transients. SIGNIFICANCE: The neonatal brain can generate epileptic ripples and fast ripples, particularly during seizures, though their occurrence is not common and potential clinical value not evident yet.

High frequency oscillations relate to cognitive improvement after epilepsy surgery in children.

OBJECTIVE: To investigate how high frequency oscillations (HFOs; ripples 80-250 Hz, fast ripples (FRs) 250-500 Hz) and spikes in intra-operative electrocorticography (ioECoG) relate to cognitive outcome after epilepsy surgery in children. METHODS: We retrospectively included 20 children who were seizure free after epilepsy surgery using ioECoG and determined their intelligence quotients (IQ) pre- and two years postoperatively. We analyzed whether the number of HFOs and spikes in pre- and postresection ioECoGs, and their change in the non-resected areas relate to cognitive improvement (with ≥ 5 IQ points increase considered to be clinically relevant (=IQ+ group) and < 5 IQ points as irrelevant (=IQ- group)). RESULTS: The IQ+ group showed significantly more FRs in the resected tissue (p = 0.01) and less FRs in the postresection ioECoG (p = 0.045) compared to the IQ- group. Postresection decrease of ripples on spikes was correlated with postoperative cognitive improvement (correlation coefficient = -0.62 with p = 0.01). CONCLUSIONS: Postoperative cognitive improvement was related to reduction of pathological HFOs signified by removing FR generating areas with subsequently less residual FRs, and decrease of ripples on spikes in the resection edge of the non-resected area. SIGNIFICANCE: HFOs recorded in ioECoG could play a role as biomarkers in the prediction and understanding of cognitive outcome after epilepsy surgery.

Non-harmonicity in high-frequency components of the intra-operative corticogram to delineate epileptogenic tissue during surgery.

OBJECTIVE: We aimed to test the potential of auto-regressive model residual modulation (ARRm), an artefact-insensitive method based on non-harmonicity of the high-frequency signal, to identify epileptogenic tissue during surgery. METHODS: Intra-operative electrocorticography (ECoG) of 54 patients with refractory focal epilepsy were recorded pre- and post-resection at 2048Hz. The ARRm was calculated in one-minute epochs in which high-frequency oscillations (HFOs; fast ripples, 250-500Hz; ripples, 80-250Hz) and spikes were marked. We investigated the pre-resection fraction of HFOs and spikes explained by the ARRm (h2-index). A general ARRm threshold was set and used to compare the ARRm to surgical outcome in post-resection ECoG (Pearson X2). RESULTS: ARRm was associated strongest with the number of fast ripples in pre-resection ECoG (h2=0.80, P<0.01), but also with ripples and spikes. An ARRm threshold of 0.47 yielded high specificity (95%) with 52% sensitivity for channels with fast ripples. ARRm values >0.47 were associated with poor outcome at channel and patient level (both P<0.01) in post-resection ECoG. CONCLUSIONS: The ARRm algorithm might enable intra-operative delineation of epileptogenic tissue. SIGNIFICANCE: ARRm is the first unsupervised real-time analysis that could provide an intra-operative, 'on demand' interpretation per electrode about the need to remove underlying tissue to optimize the chance of seizure freedom.

Do clinicians use more question marks?

OBJECTIVE: To quantify the use of question marks in titles of published studies. DESIGN AND SETTING: Literature review. PARTICIPANTS: All Pubmed publications between 1 January 2013 and 31 December 2013 with an available abstract. Papers were classified as being clinical when the search terms clin*, med* or patient* were found anywhere in the paper's title, abstract or the journal's name. Other papers were considered controls. As a verification, clinical journals were compared to non-clinical journals in two different approaches. Also, 50 highest impact journals were explored for publisher group dependent differences. MAIN OUTCOME MEASURE: Total number of question marks in titles. RESULTS: A total of 368,362 papers were classified as clinical and 596,889 as controls. Clinical papers had question marks in 3.9% (95% confidence interval 3.8-4.0%) of titles and other papers in 2.3% (confidence interval 2.3-2.3%; p < 0.001). These findings could be verified for clinical journals compared to non-clinical journals. Different percentages between four publisher groups were found (p < 0.01). CONCLUSION: We found more question marks in titles of clinical papers than in other papers. This could suggest that clinicians often have a question-driven approach to research and scientists in more fundamental research a hypothesis-driven approach. An alternative explanation is that clinicians like catchy titles. Publishing groups might have pro- and anti-question mark policies.

Residual fast ripples in the intraoperative corticogram predict epilepsy surgery outcome.

OBJECTIVE: We studied whether residual high-frequency oscillations (80-500 Hz; ripples, 80-250 Hz), especially fast ripples (FRs, 250-500 Hz), in post-resection intraoperative electrocorticography (ECoG) predicted seizure recurrence in comparison to residual interictal spikes and ictiform spike patterns. METHODS: We studied, retrospectively, ECoG recorded at 2,048 Hz after resection in a cohort of patients with refractory focal epilepsy. We analyzed occurrence and number of residual FRs, ripples, interictal spikes, and ictiform spike patterns within the last minute of each recording and compared these to seizure recurrence. RESULTS: We included 54 patients (median age 15.5 years) with 25 months median follow-up. Twenty-four patients had recurrent seizures. We found residual FRs, ripples, spikes, and ictiform spike patterns in 12, 51, 38, and 9 patients. Nine out of 12 patients with residual FRs had recurrent seizures (p = 0.016, positive predictive value 75%). Other ECoG events did not predict seizure recurrence. Patients with seizures had higher FR rates than seizure-free patients (p = 0.022). FRs near the resection and in distant pathologic areas could have changed the resection in 8 patients without harming functionally eloquent areas. One seizure-free patient had FRs in distant functionally eloquent areas. CONCLUSIONS: 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.