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ObjectiveThis study was undertaken to assess reproducibility of the epilepsy outcome and phenotype in a lateral fluid percussion model of posttraumatic epilepsy (PTE) across three study sites.MethodsA total of 525 adult male Sprague Dawley rats were randomized to lateral fluid percussion-induced brain injury (FPI) or sham operation. Of these, 264 were assigned to magnetic resonance imaging (MRI cohort, 43 sham, 221 traumatic brain injury [TBI]) and 261 to electrophysiological follow-up (EEG cohort, 41 sham, 220 TBI). A major effort was made to harmonize the rats, materials, equipment, procedures, and monitoring systems. On the 7th post-TBI month, rats were video-EEG monitored for epilepsy diagnosis.ResultsA total of 245 rats were video-EEG phenotyped for epilepsy on the 7th postinjury month (121 in MRI cohort, 124 in EEG cohort). In the whole cohort (n = 245), the prevalence of PTE in rats with TBI was 22%, being 27% in the MRI and 18% in the EEG cohort (p > .05). Prevalence of PTE did not differ between the three study sites (p > .05). The average seizure frequency was .317 ± .725 seizures/day at University of Eastern Finland (UEF; Finland), .085 ± .067 at Monash University (Monash; Australia), and .299 ± .266 at University of California, Los Angeles (UCLA; USA; p  .05). Of the 219 seizures, 53% occurred as part of a seizure cluster (≥3 seizures/24 h; p >.05 between the study sites). Of the 209 seizures, 56% occurred during lights-on period and 44% during lights-off period (p > .05 between the study sites).SignificanceThe PTE phenotype induced by lateral FPI is reproducible in a multicenter design. Our study supports the feasibility of performing preclinical multicenter trials in PTE to increase statistical power and experimental rigor to produce clinically translatable data to combat epileptogenesis after TBI.

ObjectiveProject 1 of the Preclinical Multicenter Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) consortium aims to identify preclinical biomarkers for antiepileptogenic therapies following traumatic brain injury (TBI). The international participating centers in Finland, Australia, and the United States have made a concerted effort to ensure protocol harmonization. Here, we evaluate the success of harmonization process by assessing the timing, coverage, and performance between the study sites.MethodWe collected data on animal housing conditions, lateral fluid-percussion injury model production, postoperative care, mortality, post-TBI physiological monitoring, timing of blood sampling and quality, MR imaging timing and protocols, and duration of video-electroencephalography (EEG) follow-up using common data elements. Learning effect in harmonization was assessed by comparing procedural accuracy between the early and late stages of the project.ResultsThe animal housing conditions were comparable between the study sites but the postoperative care procedures varied. Impact pressure, duration of apnea, righting reflex, and acute mortality differed between the study sites (p  0.05). Plasma quality was poor in 4% of the samples in UEF, 1% in Monash and 14% in UCLA. More than 97% of the final cohort were MR imaged at all timepoints in all study sites. The timing of imaging did not differ on D2 and D9 (p > 0.05), but varied at D30, 5 months, and ex vivo timepoints (p  0.05). A decrease in acute mortality and increase in plasma quality across time reflected a learning effect in the TBI production and blood sampling protocols.SignificanceOur study is the first demonstration of the feasibility of protocol harmonization for performing powered preclinical multi-center trials for biomarker and therapy discovery of post-traumatic epilepsy.

ObjectiveWe used the lateral fluid percussion injury (LFPI) model of moderate-to-severe traumatic brain injury (TBI) to identify early plasma biomarkers predicting injury, early post-traumatic seizures or neuromotor functional recovery (neuroscores), considering the effect of levetiracetam, which is commonly given after severe TBI.MethodsAdult male Sprague-Dawley rats underwent left parietal LFPI, received levetiracetam (200 mg/kg bolus, 200 mg/kg/day subcutaneously for 7 days [7d]) or vehicle post-LFPI, and were continuously video-EEG recorded (n = 14/group). Sham (craniotomy only, n = 6), and naïve controls (n = 10) were also used. Neuroscores and plasma collection were done at 2d or 7d post-LFPI or equivalent timepoints in sham/naïve. Plasma protein biomarker levels were determined by reverse phase protein microarray and classified according to injury severity (LFPI vs. sham/control), levetiracetam treatment, early seizures, and 2d-to-7d neuroscore recovery, using machine learning.ResultsLow 2d plasma levels of Thr231 -phosphorylated tau protein (pTAU-Thr231 ) and S100B combined (ROC AUC = 0.7790) predicted prior craniotomy surgery (diagnostic biomarker). Levetiracetam-treated LFPI rats were differentiated from vehicle treated by the 2d-HMGB1, 2d-pTAU-Thr231 , and 2d-UCHL1 plasma levels combined (ROC AUC = 0.9394) (pharmacodynamic biomarker). Levetiracetam prevented the seizure effects on two biomarkers that predicted early seizures only among vehicle-treated LFPI rats: pTAU-Thr231 (ROC AUC = 1) and UCHL1 (ROC AUC = 0.8333) (prognostic biomarker of early seizures among vehicle-treated LFPI rats). Levetiracetam-resistant early seizures were predicted by high 2d-IFNγ plasma levels (ROC AUC = 0.8750) (response biomarker). 2d-to-7d neuroscore recovery was best predicted by higher 2d-S100B, lower 2d-HMGB1, and 2d-to-7d increase in HMGB1 or decrease in TNF (P

Objective.Intracranially-recorded interictal high-frequency oscillations (HFOs) have been proposed as a promising spatial biomarker of the epileptogenic zone. However, HFOs can also be recorded in the healthy brain regions, which complicates the interpretation of HFOs. The present study aimed to characterize salient features of physiological HFOs using deep learning (DL).Approach.We studied children with neocortical epilepsy who underwent intracranial strip/grid evaluation. Time-series EEG data were transformed into DL training inputs. The eloquent cortex (EC) was defined by functional cortical mapping and used as a DL label. Morphological characteristics of HFOs obtained from EC (ecHFOs) were distilled and interpreted through a novel weakly supervised DL model.Main results.A total of 63 379 interictal intracranially-recorded HFOs from 18 children were analyzed. The ecHFOs had lower amplitude throughout the 80-500 Hz frequency band around the HFO onset and also had a lower signal amplitude in the low frequency band throughout a one-second time window than non-ecHFOs, resembling a bell-shaped template in the time-frequency map. A minority of ecHFOs were HFOs with spikes (22.9%). Such morphological characteristics were confirmed to influence DL model prediction via perturbation analyses. Using the resection ratio (removed HFOs/detected HFOs) of non-ecHFOs, the prediction of postoperative seizure outcomes improved compared to using uncorrected HFOs (area under the ROC curve of 0.82, increased from 0.76).Significance.We characterized salient features of physiological HFOs using a DL algorithm. Our results suggested that this DL-based HFO classification, once trained, might help separate physiological from pathological HFOs, and efficiently guide surgical resection using HFOs.

Studies of interictal EEG functional connectivity in the epileptic brain seek to identify abnormal interactions between brain regions involved in generating seizures, which clinically often is defined by the seizure onset zone (SOZ). However, there is evidence for abnormal connectivity outside the SOZ (NSOZ), and removal of the SOZ does not always result in seizure control, suggesting, in some cases, that the extent of abnormal connectivity indicates a larger seizure network than the SOZ. To better understand the potential differences in interictal functional connectivity in relation to the seizure network and outcome, we computed event connectivity in the theta (4-8 Hz, ThEC), low-gamma (30-55 Hz, LGEC), and high-gamma (65-95 Hz, HGEC) bands from interictal depth EEG recorded in surgical patients with medication-resistant seizures suspected to begin in the temporal lobe. Analysis finds stronger LGEC and HGEC in SOZ than NSOZ of seizure-free (SF) patients (p = 1.10e-9, 0.0217), but no difference in not seizure-free (NSF) patients. There were stronger LGEC and HGEC between mesial and lateral temporal SOZ of SF than NSF patients (p = 0.00114, 0.00205), and stronger LGEC and ThEC in NSOZ of NSF than SF patients (p = 0.0089, 0.0111). These results show that event connectivity is sensitive to differences in the interactions between regions in SOZ and NSOZ and SF and NSF patients. Patients with differential strengths in event connectivity could represent a well-localized seizure network, whereas an absence of differences could indicate a larger seizure network than the one localized by the SOZ and higher likelihood for seizure recurrence.

Drug-resistant epilepsy (DRE) affects approximately one-third of the patients with epilepsy. Based on experimental findings from animal models and brain tissue from patients with DRE, different hypotheses have been proposed to explain the cause(s) of drug resistance. One is the intrinsic severity hypothesis that posits that drug resistance is an inherent property of epilepsy related to disease severity. Seizure frequency is one measure of epilepsy severity, but frequency alone is an incomplete measure of severity and does not fully explain basic research and clinical studies on drug resistance; thus, other measures of epilepsy severity are needed. One such measure could be pathological high-frequency oscillations (HFOs), which are believed to reflect the neuronal disturbances responsible for the development of epilepsy and the generation of spontaneous seizures. In this manuscript, we will briefly review the intrinsic severity hypothesis, describe basic and clinical research on HFOs in the epileptic brain, and based on this evidence discuss whether HFOs could be a clinical measure of epilepsy severity. Understanding the mechanisms of DRE is critical for producing breakthroughs in the development and testing of novel strategies for treatment.

The epileptic network hypothesis and epileptogenic zone hypothesis are two theories of ictogenesis. The network hypothesis posits that coordinated activity among interconnected nodes produces seizures. The epileptogenic zone hypothesis posits that distinct regions are necessary and sufficient for seizure generation. High-frequency oscillations, and particularly fast ripples, are thought to be biomarkers of the epileptogenic zone. We sought to test these theories by comparing high-frequency oscillation rates and networks in surgical responders and non-responders, with no appreciable change in seizure frequency or severity, within a retrospective cohort of 48 patients implanted with stereo-EEG electrodes. We recorded inter-ictal activity during non-rapid eye movement sleep and semi-automatically detected and quantified high-frequency oscillations. Each electrode contact was localized in normalized coordinates. We found that the accuracy of seizure onset zone electrode contact classification using high-frequency oscillation rates was not significantly different in surgical responders and non-responders, suggesting that in non-responders the epileptogenic zone partially encompassed the seizure onset zone(s) (P > 0.05). We also found that in the responders, fast ripple on oscillations exhibited a higher spectral content in the seizure onset zone compared with the non-seizure onset zone (P 350 Hz. The first was a rate-distance network that multiplied the Euclidian distance between fast ripple-generating contacts by the average rate of fast ripple in the two contacts. The radius of the rate-distance network, which excluded seizure onset zone nodes, discriminated non-responders, including patients not offered resection or responsive neurostimulation due to diffuse multifocal onsets, with an accuracy of 0.77 [95% confidence interval (CI) 0.56-0.98]. The second fast ripple network was constructed using the mutual information between the timing of the events to measure functional connectivity. For most non-responders, this network had a longer characteristic path length, lower mean local efficiency in the non-seizure onset zone, and a higher nodal strength among non-seizure onset zone nodes relative to seizure onset zone nodes. The graphical theoretical measures from the rate-distance and mutual information networks of 22 non- responsive neurostimulation treated patients was used to train a support vector machine, which when tested on 13 distinct patients classified non-responders with an accuracy of 0.92 (95% CI 0.75-1). These results indicate patients who do not respond to surgery or those not selected for resection or responsive neurostimulation can be explained by the epileptic network hypothesis that is a decentralized network consisting of widely distributed, hyperexcitable fast ripple-generating nodes.

Intracranially recorded interictal high-frequency oscillations have been proposed as a promising spatial biomarker of the epileptogenic zone. However, its visual verification is time-consuming and exhibits poor inter-rater reliability. Furthermore, no method is currently available to distinguish high-frequency oscillations generated from the epileptogenic zone (epileptogenic high-frequency oscillations) from those generated from other areas (non-epileptogenic high-frequency oscillations). To address these issues, we constructed a deep learning-based algorithm using chronic intracranial EEG data via subdural grids from 19 children with medication-resistant neocortical epilepsy to: (i) replicate human expert annotation of artefacts and high-frequency oscillations with or without spikes, and (ii) discover epileptogenic high-frequency oscillations by designing a novel weakly supervised model. The 'purification power' of deep learning is then used to automatically relabel the high-frequency oscillations to distill epileptogenic high-frequency oscillations. Using 12 958 annotated high-frequency oscillation events from 19 patients, the model achieved 96.3% accuracy on artefact detection (F1 score = 96.8%) and 86.5% accuracy on classifying high-frequency oscillations with or without spikes (F1 score = 80.8%) using patient-wise cross-validation. Based on the algorithm trained from 84 602 high-frequency oscillation events from nine patients who achieved seizure-freedom after resection, the majority of such discovered epileptogenic high-frequency oscillations were found to be ones with spikes (78.6%, P

ObjectiveTo investigate the diagnostic utility of high frequency oscillations (HFOs) via scalp electroencephalogram (EEG) in infantile spasms.MethodsWe retrospectively analyzed interictal slow-wave sleep EEGs sampled at 2,000 Hz recorded from 30 consecutive patients who were suspected of having infantile spasms. We measured the rate of HFOs (80-500 Hz) and the strength of the cross-frequency coupling between HFOs and slow-wave activity (SWA) at 3-4 Hz and 0.5-1 Hz as quantified with modulation indices (MIs).ResultsTwenty-three patients (77%) exhibited active spasms during the overnight EEG recording. Although the HFOs were detected in all children, increased HFO rate and MIs correlated with the presence of active spasms (p

In recent years there has been increasing interest in applying network science tools to EEG data. At the 2018 American Epilepsy Society conference in New Orleans, LA, the yearly session of the Engineering and Neurostimulation Special Interest Group focused on emerging, translational technologies to analyze seizure networks. Each speaker demonstrated practical examples of how network tools can be utilized in clinical care and provide additional data to help care for patients with intractable epilepsy. The groups presented advances using tools from functional connectivity, control theory, and graph theory to analyze human EEG data. These tools have great potential to augment clinical interpretation of EEG signals.

Ripple oscillations (80-200 Hz) in the normal hippocampus are involved in memory consolidation during rest and sleep. In the epileptic brain, increased ripple and fast ripple (200-600 Hz) rates serve as a biomarker of epileptogenic brain. We report that both ripples and fast ripples exhibit a preferred phase angle of coupling with the trough-peak (or On-Off) state transition of the sleep slow wave in the hippocampal seizure onset zone (SOZ). Ripples on slow waves in the hippocampal SOZ also had a lower power, greater spectral frequency, and shorter duration than those in the non-SOZ. Slow waves in the mesial temporal lobe modulated the baseline firing rate of excitatory neurons, but did not significantly influence the increased firing rate associated with ripples. In summary, pathological ripples and fast ripples occur preferentially during the On-Off state transition of the slow wave in the epileptogenic hippocampus, and ripples do not require the increased recruitment of excitatory neurons.

Studies of chronic epilepsy show pathological high frequency oscillations (HFOs) are associated with brain areas capable of generating epileptic seizures. Only a few of these studies have focused on HFOs during the development of epilepsy, but results suggest pathological HFOs could be a biomarker of epileptogenesis. The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy" (EpiBioS4Rx) is a multi-center project designed to identify biomarkers of epileptogenesis after a traumatic brain injury (TBI) and evaluate treatments that could modify or prevent the development of post-traumatic epilepsy. One goal of the EpiBioS4Rx project is to assess whether HFOs could be a biomarker of post-traumatic epileptogenesis. The current study describes the work towards this goal, including the development of common surgical procedures and EEG protocols, an interim analysis of the EEG for HFOs, and identifying issues that need to be addressed for a robust biomarker analysis. At three participating sites - University of Eastern Finland (UEF), Monash University in Melbourne (Melbourne) and University of California, Los Angeles (UCLA) - TBI was induced in adult male Sprague-Dawley rats by lateral fluid-percussion injury. After injury and in sham-operated controls, rats were implanted with screw and microwire electrodes positioned in neocortex and hippocampus to record EEG. A separate group of rats had serial magnetic resonance imaging after injury and then implanted with electrodes at 6 months. Recordings 28 days post-injury were available from UEF and UCLA, but not Melbourne due to technical issues with their EEG files. Analysis of recordings from 4 rats - UEF and UCLA each had one TBI and one sham-operated control - showed EEG contained evidence of HFOs. Computer-automated algorithms detected a total of 1,819 putative HFOs and of these only 40 events (2%) were detected by all three sites. Manual review of all events verified 130 events as HFO and the remainder as false positives. Review of the 40 events detected by all three sites was associated with 88% agreement. This initial report from the EpiBioS4Rx Consortium demonstrates the standardization of EEG electrode placements, recording protocol and long-term EEG monitoring, and differences in detection algorithm HFO results between sites. Additional work on detection strategy, detection algorithm performance, and training in HFO review will be performed to establish a robust, preclinical evaluation of HFOs as a biomarker of post-traumatic epileptogenesis.

RationaleThe Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) Centre without walls is an NIH funded multicenter consortium. One of EpiBioS4Rx projects is a preclinical post-traumatic epileptogenesis biomarker study that involves three study sites: The University of Eastern Finland, Monash University (Melbourne) and the University of California Los Angeles. Our objective is to create a platform for evaluating biomarkers and testing new antiepileptogenic treatments for post-traumatic epilepsy (PTE) using the lateral fluid percussion injury (FPI) model in rats. As only 30-50% of rats with severe lateral FPI develop PTE by 6 months post-injury, prolonged video-EEG monitoring is crucial to identify animals with PTE. Our objective is to harmonize the surgical and data collection procedures, equipment, and data analysis for chronic EEG recording in order to phenotype PTE in this rat model across the three study sites.MethodsTraumatic brain injury (TBI) was induced using lateral FPI in adult male Sprague-Dawley rats aged 11-12 weeks. Animals were divided into two cohorts: a) the long-term video-EEG follow-up cohort (Specific Aim 1), which was implanted with EEG electrodes within 24 h after the injury; and b) the magnetic resonance imaging (MRI) follow-up cohort (Specific Aim 2), at 5 months after lateral FPI. Four cortical epidural screw electrodes (2 ipsilateral, 2 contralateral) and three intracerebral bipolar electrodes were implanted (septal CA1 and the dentate gyrus, layers II and VI of the perilesional cortex both anterior and posterior to the injury site). During the 7th post-TBI month, animals underwent 4 weeks of continuous video-EEG recordings to diagnose of PTE.ResultsAll centers harmonized the induction of TBI and surgical procedures for the implantation of EEG recordings, utilizing 4 or more EEG recording channels to cover areas ipsilateral and contralateral to the brain injury, perilesional cortex and the hippocampus and dentate gyrus. Ground and reference screw electrodes were implanted. At all sites the minimum sampling rate was 512 Hz, utilizing a finite impulse response (FIR) and impedance below 10 KΩ through the entire recording. As part of the quality control criteria we avoided electrical noise, and monitoring changes in impedance over time and the appearance of noise on the recordings. To reduce electrical noise, we regularly checked the integrity of the cables, stability of the EEG recording cap and the appropriate connection of the electrodes with the cables. Following the pipeline presented in this article and after applying the quality control criteria to our EEG recordings all of the sites were successful to phenotype seizure in chronic EEG recordings of animals after TBI.DiscussionDespite differences in video-EEG acquisition equipment used, the three centers were able to consistently phenotype seizures in the lateral fluid-percussion model applying the pipeline presented here. The harmonization of methodology will help to improve the rigor of preclinical research, improving reproducibility of pre-clinical research in the search of biomarkers and therapies to prevent antiepileptogenesis.

Epileptic seizures result from a variety of pathophysiological processes, evidenced by different electrographic ictal onset patterns, as seen on direct brain recordings. The two most common electrographic patterns of focal ictal onset in patients are hypersynchronous (HYP) and low-voltage fast (LVF). Whereas LVF ictal onsets were believed to result from disinhibition; based on similarities with absence seizures, focal HYP ictal onsets were believed to result from increased synchronizing inhibition. Recent findings, however, suggest the differences between these seizure onset types are more complicated and, in some cases, the opposite of these concepts are true. The following review presents evidence that a reduction of tonic inhibition on small pathologically interconnected neuron (PIN) clusters generating pathological high-frequency oscillations (pHFOs), which reflect abnormal synchronously bursting neurons may be the cause of HYP ictal onsets. Increased inhibition preceding LVF ictal onsets are discussed in other reviews in this issue. We postulate that neuronal cell loss following epileptogenic insults can result in structural reorganization, giving rise to small PIN clusters, which generate pHFOs. These clusters have a heterogeneous distribution and are spatially stable over time. Studies have demonstrated that a transient reduction in tonic inhibition causes these clusters to increase in size. This could result in consolidation and synchronization of pHFOs until a critical mass leads to propagation of HYP ictal discharges. Viewed within a network neuroscience framework, local disturbances such as PIN clusters are likely to contribute to large-scale brain network alterations: a better understanding of these epileptogenic networks promises to elucidate mechanisms of ictogenesis, epileptogenesis, and certain comorbidities of epilepsy.

Pathological high frequency oscillations (HFOs) are putative neurophysiological biomarkers of epileptogenic brain tissue. Utilizing HFOs for epilepsy surgery planning offers the promise of improved seizure outcomes for patients with medically refractory epilepsy. This review discusses possible machine learning strategies that can be applied to HFO biomarkers to better identify epileptogenic regions. We discuss the role of HFO rate, and utilizing features such as explicit HFO properties (spectral content, duration, and power) and phase-amplitude coupling for distinguishing pathological HFO (pHFO) events from physiological HFO events. In addition, the review highlights the importance of neuroanatomical localization in machine learning strategies.

The Epilepsy Bioinformatics Study for Anti-epileptogenic Therapy (EpiBioS4Rx) is a longitudinal prospective observational study funded by the National Institute of Health (NIH) to discover and validate observational biomarkers of epileptogenesis after traumatic brain injury (TBI). A multidisciplinary approach has been incorporated to investigate acute electrical, neuroanatomical, and blood biomarkers after TBI that may predict the development of post-traumatic epilepsy (PTE). We plan to enroll 300 moderate-severe TBI patients with a frontal and/or temporal lobe hemorrhagic contusion. Acute evaluation with blood, imaging and electroencephalographic monitoring will be performed and then patients will be tracked for 2 years to determine the incidence of PTE. Validation of selected biomarkers that are discovered in planned animal models will be a principal feature of this work. Specific hypotheses regarding the discovery of biomarkers have been set forth in this study. An international cohort of 13 centers spanning 2 continents will be developed to facilitate this study, and for future interventional studies.

Multi-center preclinical studies can facilitate the discovery of biomarkers of antiepileptogenesis and thus facilitate the diagnosis and treatment development of patients at risk of developing post-traumatic epilepsy. However, these studies are often limited by the difficulty in harmonizing experimental protocols between laboratories. Here, we assess whether the production of traumatic brain injury (TBI) using the lateral fluid-percussion injury (FPI) in adult male Sprague-Dawley rats (12 weeks at the time of injury) was harmonized between three laboratories - located in the University of Eastern Finland (UEF), Monash University in Melbourne, Australia (Melbourne) and The University of California, Los Angeles, USA (UCLA). These laboratories are part of the international multicenter-based project, the Epilepsy Bioinformatics Study for Antiepileptogenesis Therapy (EpiBioS4Rx). Lateral FPI was induced in adult male Sprague-Dawley rats. The success of methodological harmonization was assessed by performing inter-site comparison of injury parameters including duration of anesthesia during surgery, impact pressure, post-impact transient apnea, post-impact seizure-like behavior, acute mortality ( Melbourne > UCLA (p

The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) is an international, multicenter, multidisciplinary study aimed at preventing epileptogenesis (EpiBioS4Rx: https://epibios.loni.usc.edu/). One of the study's major objectives is the discovery of diagnostic, prognostic, and predictive plasma protein and microRNA (miRNA) biomarkers that are sensitive, specific, and translatable to the human condition. Epilepsy due to structural brain abnormalities, secondary to neurological insults such as traumatic brain injury (TBI), currently represents ∼50% of all epilepsy cases. In the preclinical EpiBioS4Rx study, TBI was induced in adult male Sprague Dawley rats using a standardized protocol for lateral fluid-percussion injury. Whole blood was collected from the tail vein at baseline and 2, 9 and 30 days post-injury and processed for plasma separation. Biomaterial properties, sample preparation and integrity, and choice of analysis platform can significantly impact measured marker levels and, in turn, interpretation with respect to injury and/or other variables. We present here the results of procedural harmonization for the first 320 rats included in the EpiBioS4Rx study study, from three international research centers, and preliminary proteomic and miRNA analyses. We also discuss experimental considerations for establishing rigorous quality controls with the goal of harmonizing operating procedures across study sites, and delivering high-quality specimens for preclinical biomarker discovery in a rat model of post-traumatic epilepsy (PTE).

There are no reliable nonictal biomarkers for epilepsy, electroencephalography (EEG) or otherwise, but efforts to identify biomarkers that would predict the development of epilepsy after a potential epileptogenic insult, diagnose the existence of epilepsy, or assess the effects of antiseizure or antiepileptogenic interventions are relying heavily on electrophysiology. The most promising EEG biomarkers to date are pathologic high-frequency oscillations (pHFOs), brief EEG events in the range of 100 to 600 Hz, which are believed to reflect summated action potentials from synchronously bursting neurons. Studies of patients with epilepsy, and experimental animal models, have been based primarily on direct brain recording, which makes pHFOs potentially useful for localizing the epileptogenic zone for surgical resection, but application for other diagnostic and therapeutic purposes is limited. Consequently, recent efforts have involved identification of HFOs recorded with scalp electrodes, and with magnetoencephalography, which may reflect the same pathophysiologic mechanisms as pHFOs recorded directly from the brain. The search is also on for other EEG changes that might serve as epilepsy biomarkers, and candidates include arcuate rhythms, which may reflect repetitive pHFOs, reduction in theta rhythm, which correlates with epileptogenesis in several rodent models of epilepsy, and shortened sleep spindles that correlate with ictogenesis.

ObjectiveIntracellular recordings from cells in entorhinal cortex tissue slices show that low-voltage fast (LVF) onset seizures are generated by inhibitory events. Here, we determined whether increased firing of interneurons occurs at the onset of spontaneous mesial-temporal LVF seizures recorded in patients.MethodsThe seizure onset zone (SOZ) was identified using visual inspection of the intracranial electroencephalogram. We used wavelet clustering and temporal autocorrelations to characterize changes in single-unit activity during the onset of LVF seizures recorded from microelectrodes in mesial-temporal structures. Action potentials generated by principal neurons and interneurons (ie, putative excitatory and inhibitory neurons) were distinguished using waveform morphology and K-means clustering.ResultsFrom a total of 200 implanted microelectrodes in 9 patients during 13 seizures, we isolated 202 single units; 140 (69.3%) of these units were located in the SOZ, and 40 (28.57%) of them were classified as inhibitory. The waveforms of both excitatory and inhibitory units remained stable during the LVF epoch (p > > 0.05). In the mesial-temporal SOZ, inhibitory interneurons increased their firing rate during LVF seizure onset (p

Neurosurgery is an underutilized treatment that can potentially cure drug-refractory epilepsy. Careful, multidisciplinary presurgical evaluation is vital for selecting patients and to ensure optimal outcomes. Advances in neuroimaging have improved diagnosis and guided surgical intervention. Invasive electroencephalography allows the evaluation of complex patients who would otherwise not be candidates for neurosurgery. We review the current state of the assessment and selection of patients and consider established and novel surgical procedures and associated outcome data. We aim to dispel myths that may inhibit physicians from referring and patients from considering neurosurgical intervention for drug-refractory focal epilepsies. Ann Neurol 2018;83:676-690.

OBJECTIVE:Differentiating pathologic and physiologic high-frequency oscillations (HFOs) is challenging. In patients with focal epilepsy, HFOs occur during the transitional periods between the up and down state of slow waves. The preferred phase angles of this form of phase-event amplitude coupling are bimodally distributed, and the ripples (80-150 Hz) that occur during the up-down transition more often occur in the seizure-onset zone (SOZ). We investigated if bimodal ripple coupling was also evident for faster sleep oscillations, and could identify the SOZ. METHODS:Using an automated ripple detector, we identified ripple events in 40-60 min intracranial electroencephalography (iEEG) recordings from 23 patients with medically refractory mesial temporal lobe or neocortical epilepsy. The detector quantified epochs of sleep oscillations and computed instantaneous phase. We utilized a ripple phasor transform, ripple-triggered averaging, and circular statistics to investigate phase event-amplitude coupling. RESULTS:We found that at some individual recording sites, ripple event amplitude was coupled with the sleep oscillatory phase and the preferred phase angles exhibited two distinct clusters (p

ObjectiveRipples (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.MethodsWe 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).ResultsBoth 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).SignificanceGeneration 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.

ObjectivePosttraumatic epilepsy (PTE) accounts for 20% of acquired epilepsies. Experimental models are important for studying epileptogenesis. We previously reported that repetitive high-frequency oscillations with spikes (rHFOSs) occur early after lateral fluid percussion injury (FPI) and may be a biomarker for PTE. The objective of this study was to use multiple electrodes in rat hippocampal and neocortical regions to describe the long-term electroencephalographic and behavioral evolution of rHFOSs and epileptic seizures after traumatic brain injury (TBI).MethodsAdult male rats underwent mild, moderate, or severe FPI or sham injury followed by video-electroencephalography (EEG) recordings with a combination of 16 neocortical and hippocampal electrodes at an early, intermediate, or late time-point after injury, up to 52 weeks. Recordings were analyzed for the presence of rHFOSs and seizures.ResultsAnalysis was done on 28 rats with FPI and 7 shams. Perilesional rHFOSs were recorded in significantly more rats after severe (70.3%) than mild (20%) injury or shams (14.3%). Frequency of occurrence was significantly highest in the early (10.8/h) versus late group (3.2/h). Late focal seizures originating from the same electrodes were recorded in significantly more rats in the late (87.5%) versus early period (22.2%), occurring almost exclusively in injured rats. Seizure duration increased significantly over time, averaging 19 s at the beginning of the early period and 27 s at the end of the late period. Seizure frequency also increased significantly over time, from 4.4 per week in the early group to 26.4 per week in the late group. Rarely, rats displayed early seizures or generalized seizures.SignificanceFPI results in early rHFOSs and later spontaneous focal seizures arising from peri-lesional neocortex, supporting its use as a model for PTE. Epilepsy severity increased over time and was related to injury severity. The association between early rHFOSs and later focal seizures suggests that rHFOSs may be a potential noninvasive biomarker of PTE.

ObjectiveTo investigate possible electroencephalography (EEG) correlates of epileptogenesis after traumatic brain injury (TBI) using the fluid percussion model.MethodsExperiments were conducted on adult 2- to 4-month-old male Sprague-Dawley rats. Two groups of animals were studied: (1) the TBI group with depth and screw electrodes implanted immediately after the fluid percussion injury (FPI) procedure, and (2) a naive age-matched control group with the same electrode implantation montage. Pairs of tungsten microelectrodes (50 μm outer diameter) and screw electrodes were implanted in neocortex inside the TBI core, areas adjacent to TBI, and remote areas. EEG activity, recorded on the day of FPI, and continuously for 2 weeks, was analyzed for possible electrographic biomarkers of epileptogenesis. Video-EEG monitoring was also performed continuously in the TBI group to capture electrographic and behavioral seizures until the caps came off (28-189 days), and for 1 week, at 2, 3, and 6 months of age, in the control group.ResultsPathologic high-frequency oscillations (pHFOs) with a central frequency between 100 and 600 Hz, were recorded from microelectrodes, beginning during the first two post-FPI weeks, in 7 of 12 animals in the TBI group (58%) and never in the controls. pHFOs only occurred in cortical areas within or adjacent to the TBI core. These were associated with synchronous multiunit discharges and popSpikes, duration 15-40 msec. Repetitive pHFOs and EEG spikes (rHFOSs) formed paroxysmal activity, with a unique arcuate pattern, in the frequency band 10-16 Hz in the same areas as isolated pHFOs, and these events were also recorded by screw electrodes. Although loss of caps prevented long-term recordings from all rats, pHFOs and rHFOSs occurred during the first 2 weeks in all four animals that later developed seizures, and none of the rats without these events developed late seizures.SignificancepHFOs, similar to those associated with epileptogenesis in the status rat model of epilepsy, may also reflect epileptogenesis after FPI. rHFOSs could be noninvasive biomarkers of epileptogenesis.

ObjectiveQuantifying the relationship between microelectrode-recorded multi-unit activity (MUA) and local field potentials (LFPs) in distinct brain regions can provide detailed information on the extent of functional connectivity in spatially widespread networks. These methods are common in studies of cognition using non-human animal models, but are rare in humans. Here we applied a neuronal spike-triggered impulse response to electrophysiological recordings from the human epileptic brain for the first time, and we evaluate functional connectivity in relation to brain areas supporting the generation of seizures.ApproachBroadband interictal electrophysiological data were recorded from microwires adapted to clinical depth electrodes that were implanted bilaterally using stereotactic techniques in six presurgical patients with medically refractory epilepsy. MUA and LFPs were isolated in each microwire, and we calculated the impulse response between the MUA on one microwire and the LFPs on a second microwire for all possible MUA/LFP pairs. Results were compared to clinical seizure localization, including sites of seizure onset and interictal epileptiform discharges.Main resultsWe detected significant interictal long-range functional connections in each subject, in some cases across hemispheres. Results were consistent between two independent datasets, and the timing and location of significant impulse responses reflected anatomical connectivity. However, within individual subjects, the spatial distribution of impulse responses was unique. In two subjects with clear seizure localization and successful surgery, the epileptogenic zone was associated with significant impulse responses.SignificanceThe results suggest that the spike-triggered impulse response can provide valuable information about the neuronal networks that contribute to seizures using only interictal data. This technique will enable testing of specific hypotheses regarding functional connectivity in epilepsy and the relationship between functional properties and imaging findings. Beyond epilepsy, we expect that the impulse response could be more broadly applied as a measure of long-range functional connectivity in studies of cognition.

BackgroundThis study sought to predict postsurgical seizure freedom from pre-operative diagnostic test results and clinical information using a rapid automated approach, based on supervised learning methods in patients with drug-resistant focal seizures suspected to begin in temporal lobe.MethodWe applied machine learning, specifically a combination of mutual information-based feature selection and supervised learning classifiers on multimodal data, to predict surgery outcome retrospectively in 20 presurgical patients (13 female; mean age±SD, in years 33±9.7 for females, and 35.3±9.4 for males) who were diagnosed with mesial temporal lobe epilepsy (MTLE) and subsequently underwent standard anteromesial temporal lobectomy. The main advantage of the present work over previous studies is the inclusion of the extent of ipsilateral neocortical gray matter atrophy and spatiotemporal properties of depth electrode-recorded seizures as training features for individual patient surgery planning.ResultsA maximum relevance minimum redundancy (mRMR) feature selector identified the following features as the most informative predictors of postsurgical seizure freedom in this study's sample of patients: family history of epilepsy, ictal EEG onset pattern (positive correlation with seizure freedom), MRI-based gray matter thickness reduction in the hemisphere ipsilateral to seizure onset, proportion of seizures that first appeared in ipsilateral amygdala to total seizures, age, epilepsy duration, delay in the spread of ipsilateral ictal discharges from site of onset, gender, and number of electrode contacts at seizure onset (negative correlation with seizure freedom). Using these features in combination with a least square support vector machine (LS-SVM) classifier compared to other commonly used classifiers resulted in very high surgical outcome prediction accuracy (95%).ConclusionsSupervised machine learning using multimodal compared to unimodal data accurately predicted postsurgical outcome in patients with atypical MTLE.

Pathological high-frequency oscillations (HFOs) (80-800 Hz) are considered biomarkers of epileptogenic tissue, but the underlying complex neuronal events are not well understood. Here, we identify and discuss several outstanding issues or conundrums in regards to the recording, analysis, and interpretation of HFOs in the epileptic brain to critically highlight what is known and what is not about these enigmatic events. High-frequency oscillations reflect a range of neuronal processes contributing to overlapping frequencies from the lower 80 Hz to the very fast spectral frequency bands. Given their complex neuronal nature, HFOs are extremely sensitive to recording conditions and analytical approaches. We provide a list of recommendations that could help to obtain comparable HFO signals in clinical and basic epilepsy research. Adopting basic standards will facilitate data sharing and interpretation that collectively will aid in understanding the role of HFOs in health and disease for translational purpose.

Hypersynchronous (HYP) and low voltage fast (LVF) activity are two separate ictal depth EEG onsets patterns often recorded in presurgical patients with MTLE. Evidence suggests the mechanisms generating HYP and LVF onset seizures are distinct, including differential involvement of hippocampal and extra-hippocampal sites. Yet the extent of extra-hippocampal structural alterations, which could support these two common seizures, is not known. In the current study, preoperative MRI from 24 patients with HYP or LVF onset seizures were analyzed to determine changes in cortical thickness and relate structural changes to spatiotemporal properties of the ictal EEG. Overall, onset and initial ipsilateral spread of HYP onset seizures involved mesial temporal structures, whereas LVF onset seizures involved mesial and lateral temporal as well as orbitofrontal cortex. MRI analysis found reduced cortical thickness correlated with longer duration of epilepsy. However, in patients with HYP onsets, the most affected areas were on the medial surface of each hemisphere, including parahippocampal regions and cingulate gyrus, whereas in patients with LVF onsets, the lateral surface of the anterior temporal lobe and orbitofrontal cortex showed the greatest effect. Most patients with HYP onset seizures were seizure-free after resective surgery, while a higher proportion of patients with LVF onset seizures had only worthwhile improvement. Our findings confirm the view that recurrent seizures cause progressive changes in cortical thickness, and provide information concerning the structural basis of two different epileptogenic networks responsible for MTLE. One, identified by HYP ictal onsets, chiefly involves hippocampus and is associated with excellent outcome after standardized anteromedial temporal resection, while the other also involves lateral temporal and orbitofrontal cortex and a seizure-free surgical outcome occurs less after this procedure. These results suggest that a more extensive tailored resection may be required for patients with the second type of MTLE.

In patients being evaluated for epilepsy and in animal models of epilepsy, electrophysiological recordings are carried to capture seizures to determine the existence of epilepsy. Electroencephalography recordings from the scalp, or sometimes directly from the brain, are also used to locate brain areas where seizure begins, and in surgical treatment help plan the area for resection. As seizures are unpredictable and can occur infrequently, ictal recordings are not ideal in terms of time, cost, or risk when, for example, determining the efficacy of existing or new anti-seizure drugs, evaluating potential anti-epileptogenic interventions, or for prolonged intracerebral electrode studies. Thus, there is a need to identify and validate other electrophysiological biomarkers of epilepsy that could be used to diagnose, treat, cure, and prevent epilepsy. Electroencephalography recordings in the epileptic brain contain other interictal electrophysiological disturbances that can occur more frequently than seizures, such as interictal spikes (IIS) and sharp waves, and from invasive studies using wide bandwidth recording and small diameter electrodes, the discovery of pathological high-frequency oscillations (HFOs) and microseizures. Of IIS, HFOs, and microseizures, a significant amount of recent research has focused on HFOs in the pathophysiology of epilepsy. Results from studies in animals with epilepsy and presurgical patients have consistently found a strong association between HFOs and epileptogenic brain tissue that suggest HFOs could be a potential biomarker of epileptogenicity and epileptogenesis. Here, we discuss several aspects of HFOs, as well as IIS and microseizures, and the evidence that supports their role as biomarkers of epilepsy.

Investigations of interictal epileptiform spikes and seizures have played a central role in the study of epilepsy. The background EEG activity, however, has received less attention. In this chapter we discuss the characteristic features of the background activity of the brain when individuals are at rest and awake (resting wake) and during sleep. The characteristic rhythms of the background EEG are presented, and the presence of 1/f (β) behavior of the EEG power spectral density is discussed and its possible origin and functional significance. The interictal EEG findings of focal epilepsy and the impact of interictal epileptiform spikes on cognition are also discussed.

Mesial temporal lobe epilepsy (MTLE) is the most common of the surgically remediable drug-resistant epilepsies. MRI is the primary diagnostic tool to detect anatomical abnormalities and, when combined with EEG, can more accurately identify an epileptogenic lesion, which is often hippocampal sclerosis in cases of MTLE. As structural imaging technology has advanced the surgical treatment of MTLE and other lesional epilepsies, so too have the analysis techniques that are used to measure different structural attributes of the brain. These techniques, which are reviewed here and have been used chiefly in basic research of epilepsy and in studies of MTLE, have identified different types and the extent of anatomical abnormalities that can extend beyond the affected hippocampus. These results suggest that structural imaging and sophisticated imaging analysis could provide important information to identify networks capable of generating spontaneous seizures and ultimately help guide surgical therapy that improves postsurgical seizure-freedom outcomes.

Between seizures the brain of patients with epilepsy generates pathological patterns of synchronous activity, designated as interictal epileptiform discharges (ID). Using microelectrodes in the hippocampal formations of 8 patients with drug-resistant temporal lobe epilepsy, we studied ID by simultaneously analyzing action potentials from individual neurons and the local field potentials (LFPs) generated by the surrounding neuronal network. We found that ~30% of the units increased their firing rate during ID and 40% showed a decrease during the post-ID period. Surprisingly, 30% of units showed either an increase or decrease in firing rates several hundred of milliseconds before the ID. In 4 patients, this pre-ID neuronal firing was correlated with field high-frequency oscillations at 40-120 Hz. Finally, we observed that only a very small subset of cells showed significant coincident firing before or during ID. Taken together, we suggested that, in contrast to traditional views, ID are generated by a sparse neuronal network and followed a heterogeneous synchronization process initiated over several hundreds of milliseconds before the paroxysmal discharges.