Simulated resections and RNS placement can optimize post-operative seizure outcomes when guided by fast ripple networks.

Resecting cortical tissue generating high-frequency oscillations (HFOs) has been investigated as a more efficacious alternative to resecting the clinically defined seizure onset zone (SOZ). In this study, we asked if seizure freedom would be achieved using virtual resections of fast ripple (FR) networks. We compared these virtual resections to the individual patient's actual resection and clinical outcome. We conclude that the SOZ is the minimum territory of cortex that must be resected to achieve seizure freedom. By utilizing support vector machines (SVMs) with an accuracy of 0.78 for labeling seizure freedom using factors from FR networks we could predict whether resection of the SOZ corresponded with a seizure free outcome. Furthermore, this approach could identify regions that generate FR autonomously and at high rates outside the SOZ. In the patients who experienced seizures after resection of the SOZ, virtual resections that included the SOZ and other FR generating regions rendered the patient virtually seizure free. We examined responsive neurostimulator system (RNS) patients and virtually targeted the RNS stimulation contacts proximal to sites generating FR. We used the simulations to investigate if the likelihood of a RNS super responder (>90% seizure reduction) outcome would be increased.

Edge-wise analysis reveals white matter connectivity associated with focal to bilateral tonic-clonic seizures.

OBJECTIVE: Focal to bilateral tonic-clonic seizures (FBTCS) represent a challenging subtype of focal temporal lobe epilepsy (TLE) in terms of both severity and treatment response. Most studies have focused on regional brain analysis that is agnostic to the distribution of white matter (WM) pathways associated with a node. We implemented a more selective, edge-wise approach that allowed for identification of the individual connections unique to FBTCS. METHODS: T1-weighted and diffusion-weighted images were obtained from 22 patients with solely focal seizures (FS), 43 FBTCS patients, and 65 age/sex-matched healthy participants (HPs), yielding streamline (STR) connectome matrices. We used diffusion tensor-derived STRs in an edge-wise approach to determine specific structural connectivity changes associated with seizure generalization in FBTCS compared to matched FS and HPs. Graph theory metrics were computed on both node- and edge-based connectivity matrices. RESULTS: Edge-wise analyses demonstrated that all significantly abnormal cross-hemispheric connections belonged to the FBTCS group. Abnormal connections associated with FBTCS were mostly housed in the contralateral hemisphere, with graph metric values generally decreased compared to HPs. In FBTCS, the contralateral amygdala showed selective decreases in the structural connection pathways to the contralateral frontal lobe. Abnormal connections in TLE involved the amygdala, with the ipsilateral side showing increases and the contralateral decreases. All the FS findings indicated higher graph metrics for connections involving the ipsilateral amygdala. Data also showed that some FBTCS connectivity effects are moderated by aging, recent seizure frequency, and longer illness duration. SIGNIFICANCE: Data showed that not all STR pathways are equally affected by the seizure propagation of FBTCS. We demonstrated two key biases, one indicating a large role for the amygdala in the propagation of seizures, the other pointing to the prominent role of cross-hemispheric and contralateral hemisphere connections in FBTCS. We demonstrated topographic reorganization in FBTCS, pointing to the specific WM tracts involved.

Automated Seizure Detection Based on State-Space Model Identification.

In this study, we developed a machine learning model for automated seizure detection using system identification techniques on EEG recordings. System identification builds mathematical models from a time series signal and uses a small number of parameters to represent the entirety of time domain signal epochs. Such parameters were used as features for the classifiers in our study. We analyzed 69 seizure and 55 non-seizure recordings and an additional 10 continuous recordings from Thomas Jefferson University Hospital, alongside a larger dataset from the CHB-MIT database. By dividing EEGs into epochs (1 s, 2 s, 5 s, and 10 s) and employing fifth-order state-space dynamic systems for feature extraction, we tested various classifiers, with the decision tree and 1 s epochs achieving the highest performance: 96.0% accuracy, 92.7% sensitivity, and 97.6% specificity based on the Jefferson dataset. Moreover, as the epoch length increased, the accuracy dropped to 94.9%, with a decrease in sensitivity to 91.5% and specificity to 96.7%. Accuracy for the CHB-MIT dataset was 94.1%, with 87.6% sensitivity and 97.5% specificity. The subject-specific cases showed improved results, with an average of 98.3% accuracy, 97.4% sensitivity, and 98.4% specificity. The average false detection rate per hour was 0.5 ± 0.28 in the 10 continuous EEG recordings. This study suggests that using a system identification technique, specifically, state-space modeling, combined with machine learning classifiers, such as decision trees, is an effective and efficient approach to automated seizure detection.

Long-Term Home EEG Recording: Wearable and Implantable Devices.

SUMMARY: Electroencephalography (EEG) monitoring has served as a cornerstone in the diagnostic and therapeutic evaluation of epilepsy since its development. This has been accomplished with short-term inpatient video-EEG hospitalization enabling observation of both the semiological and the electrographic features of seizures or with short-term home ambulatory EEG or video-EEG. The advantages of inpatient video-EEG monitoring are limited by high cost, inconvenience, and inability to monitor patients for long periods (weeks or months) as might be done in the outpatient setting. This limitation has impelled the development of wearable EEG devices, which aim to capture high-quality long-term EEG data in a user-friendly and unobtrusive manner. This review article aims to summarize three broad categories of wearable EEG devices, including scalp, subcutaneous, and intracranial EEG. In this review, we will discuss the features of each type of device and the implications for the management of epilepsy. This review does not aim to describe every wearable EEG device on the market but instead seeks to provide a broad overview of the various categories of device that are available, giving examples of each and those in development (with no intention to recommend or advocate for any particular product).

The Temporal Lobe Club: Newer Approaches to Treat Temporal Lobe Epilepsy.

This brief review summarizes presentations at the Temporal Lobe Club Special Interest Group session held in December 2022 at the American Epilepsy Society meeting. The session addressed newer methods to treat temporal epilepsy, including methods currently in clinical use and techniques under investigation. Brief summaries are provided for each of 4 lectures. Dr Chengyuan Wu discussed ablative techniques such as laser interstitial thermal ablation, radiofrequency ablation, focused ultrasound; Dr Joon Kang reviewed neuromodulation techniques including electrical stimulation and focused ultrasound; Dr Julia Makhalova discussed network effects of the aforementioned techniques; and Dr Derek Southwell reviewed inhibitory interneuron transplantation. These summaries are intended to provide a brief overview and references are provided for the reader to learn more about each topic.

Which terms should be used to describe medications used in the treatment of seizure disorders? An ILAE position paper.

A variety of terms, such as "antiepileptic," "anticonvulsant," and "antiseizure" have been historically applied to medications for the treatment of seizure disorders. Terminology is important because using terms that do not accurately reflect the action of specific treatments may result in a misunderstanding of their effects and inappropriate use. The present International League Against Epilepsy (ILAE) position paper used a Delphi approach to develop recommendations on English-language terminology applicable to pharmacological agents currently approved for treating seizure disorders. There was consensus that these medications should be collectively named "antiseizure medications". This term accurately reflects their primarily symptomatic effect against seizures and reduces the possibility of health care practitioners, patients, or caregivers having undue expectations or an incorrect understanding of the real action of these medications. The term "antiseizure" to describe these agents does not exclude the possibility of beneficial effects on the course of the disease and comorbidities that result from the downstream effects of seizures, whenever these beneficial effects can be explained solely by the suppression of seizure activity. It is acknowledged that other treatments, mostly under development, can exert direct favorable actions on the underlying disease or its progression, by having "antiepileptogenic" or "disease-modifying" effects. A more-refined terminology to describe precisely these actions needs to be developed.

Analyses of patients who self-administered diazepam nasal spray for acute treatment of seizure clusters.

For acute treatment of seizure clusters in patients with epilepsy, intranasal administration of acute seizure therapies has been shown to provide accessibility and ease of use to care partners as well as the potential for self-administration by patients. Diazepam nasal spray (Valtoco®) was approved by the US Food and Drug Administration for acute treatment of intermittent, stereotypic episodes of frequent seizure activity (ie, seizure clusters, acute repetitive seizures) in patients with epilepsy aged ≥6 years. Self-administration consistent with the prescribing information is feasible and was reported by a subgroup of patients (n = 27 of 163) in a long-term phase 3 safety study. Data regarding self-administration among these patients with seizure clusters are examined here to explore the safety profiles and measures of effectiveness, as well as the quality of life of those who self-treated. In addition, this focused look at patients who self-administered diazepam nasal spray may offer some insights into the characteristics of patients who may be appropriate for self-administration.

Prediction tools and risk stratification in epilepsy surgery.

OBJECTIVE: This study was undertaken to conduct external validation of previously published epilepsy surgery prediction tools using a large independent multicenter dataset and to assess whether these tools can stratify patients for being operated on and for becoming free of disabling seizures (International League Against Epilepsy stage 1 and 2). METHODS: We analyzed a dataset of 1562 patients, not used for tool development. We applied two scales: Epilepsy Surgery Grading Scale (ESGS) and Seizure Freedom Score (SFS); and two versions of Epilepsy Surgery Nomogram (ESN): the original version and the modified version, which included electroencephalographic data. For the ESNs, we used calibration curves and concordance indexes. We stratified the patients into three tiers for assessing the chances of attaining freedom from disabling seizures after surgery: high (ESGS = 1, SFS = 3-4, ESNs > 70%), moderate (ESGS = 2, SFS = 2, ESNs = 40%-70%), and low (ESGS = 2, SFS = 0-1, ESNs < 40%). We compared the three tiers as stratified by these tools, concerning the proportion of patients who were operated on, and for the proportion of patients who became free of disabling seizures. RESULTS: The concordance indexes for the various versions of the nomograms were between .56 and .69. Both scales (ESGS, SFS) and nomograms accurately stratified the patients for becoming free of disabling seizures, with significant differences among the three tiers (p < .05). In addition, ESGS and the modified ESN accurately stratified the patients for having been offered surgery, with significant difference among the three tiers (p < .05). SIGNIFICANCE: ESGS and the modified ESN (at thresholds of 40% and 70%) stratify patients undergoing presurgical evaluation into three tiers, with high, moderate, and low chance for favorable outcome, with significant differences between the groups concerning having surgery and becoming free of disabling seizures. Stratifying patients for epilepsy surgery has the potential to help select the optimal candidates in underprivileged areas and better allocate resources in developed countries.

Functional and anatomical connectivity predict brain stimulation's mnemonic effects.

Closed-loop direct brain stimulation is a promising tool for modulating neural activity and behavior. However, it remains unclear how to optimally target stimulation to modulate brain activity in particular brain networks that underlie particular cognitive functions. Here, we test the hypothesis that stimulation's behavioral and physiological effects depend on the stimulation target's anatomical and functional network properties. We delivered closed-loop stimulation as 47 neurosurgical patients studied and recalled word lists. Multivariate classifiers, trained to predict momentary lapses in memory function, triggered the stimulation of the lateral temporal cortex (LTC) during the study phase of the task. We found that LTC stimulation specifically improved memory when delivered to targets near white matter pathways. Memory improvement was largest for targets near white matter that also showed high functional connectivity to the brain's memory network. These targets also reduced low-frequency activity in this network, an established marker of successful memory encoding. These data reveal how anatomical and functional networks mediate stimulation's behavioral and physiological effects, provide further evidence that closed-loop LTC stimulation can improve episodic memory, and suggest a method for optimizing neuromodulation through improved stimulation targeting.

Pathological neurons generate ripples at the UP-DOWN transition disrupting information transfer.

OBJECTIVE: To confirm and investigate why pathological high-frequency oscillations (pHFOs), including ripples (80-200 Hz) and fast ripples (200-600 Hz), are generated during the UP-DOWN transition of the slow wave and if information transmission mediated by ripple temporal coupling is disrupted in the seizure-onset zone (SOZ). METHODS: We isolated 217 total units from 175.95 intracranial electroencephalography (iEEG) contact-hours of synchronized macro- and microelectrode recordings from 6 patients. Sleep slow oscillation (.1-2 Hz) epochs were identified in the iEEG recording. iEEG HFOs that occurred superimposed on the slow wave were transformed to phasors and adjusted by the phase of maximum firing in nearby units (i.e., maximum UP). We tested whether, in the SOZ, HFOs and associated action potentials (APs) occur more often at the UP-DOWN transition. We also examined ripple temporal correlations using cross-correlograms. RESULTS: At the group level in the SOZ, HFO and HFO-associated AP probability was highest during the UP-DOWN transition of slow wave excitability (p < < .001). In the non-SOZ, HFO and HFO-associated AP was highest during the DOWN-UP transition (p < < .001). At the unit level in the SOZ, 15.6% and 20% of units exhibited more robust firing during ripples (Cohen's d = .11-.83) and fast ripples (d = .36-.90) at the UP-DOWN transition (p < .05 f.d.r. corrected), respectively. By comparison, also in the SOZ, 6.6% (d = .14-.30) and 8.5% (d = .33-.41) of units had significantly less firing during ripples and fast ripples at the UP-DOWN transition, respectively. Additional data shows that ripple and fast ripple temporal correlations, involving global slow waves, between the hippocampus, entorhinal cortex, and parahippocampal gyrus were reduced by >50% in the SOZ compared to the non-SOZ (N = 3). SIGNIFICANCE: The UP-DOWN transition of slow wave excitability facilitates the activation of pathological neurons to generate pHFOs. Ripple temporal correlations across brain regions may be important in memory consolidation and are disrupted in the SOZ, perhaps by pHFO generation.

Fast ripples reflect increased excitability that primes epileptiform spikes.

The neuronal circuit disturbances that drive inter-ictal and ictal epileptiform discharges remain elusive. Using a combination of extra-operative macro-electrode and micro-electrode inter-ictal recordings in six pre-surgical patients during non-rapid eye movement sleep, we found that, exclusively in the seizure onset zone, fast ripples (200-600 Hz), but not ripples (80-200 Hz), frequently occur <300 ms before an inter-ictal intra-cranial EEG spike with a probability exceeding chance (bootstrapping, P < 1e-5). Such fast ripple events are associated with higher spectral power (P < 1e-10) and correlated with more vigorous neuronal firing than solitary fast ripple (generalized linear mixed-effects model, P < 1e-9). During the intra-cranial EEG spike that follows a fast ripple, action potential firing is lower than during an intra-cranial EEG spike alone (generalized linear mixed-effects model, P < 0.05), reflecting an inhibitory restraint of intra-cranial EEG spike initiation. In contrast, ripples do not appear to prime epileptiform spikes. We next investigated the clinical significance of pre-spike fast ripple in a separate cohort of 23 patients implanted with stereo EEG electrodes, who underwent resections. In non-rapid eye movement sleep recordings, sites containing a high proportion of fast ripple preceding intra-cranial EEG spikes correlate with brain areas where seizures begin more than solitary fast ripple (P < 1e-5). Despite this correlation, removal of these sites does not guarantee seizure freedom. These results are consistent with the hypothesis that fast ripple preceding EEG spikes reflect an increase in local excitability that primes EEG spike discharges preferentially in the seizure onset zone and that epileptogenic brain regions are necessary, but not sufficient, for initiating inter-ictal epileptiform discharges.

Functional and anatomical connectivity predict brain stimulation's mnemonic effects.

Closed-loop direct brain stimulation is a promising tool for modulating neural activity and behavior. However, it remains unclear how to optimally target stimulation to modulate brain activity in particular brain networks that underlie particular cognitive functions. Here, we test the hypothesis that stimulation's behavioral and physiological effects depend on the stimulation target's anatomical and functional network properties. We delivered closed-loop stimulation as 47 neurosurgical patients studied and recalled word lists. Multivariate classifiers, trained to predict momentary lapses in memory function, triggered stimulation of the lateral temporal cortex (LTC) during the study phase of the task. We found that LTC stimulation specifically improved memory when delivered to targets near white matter pathways. Memory improvement was largest for targets near white matter that also showed high functional connectivity to the brain's memory network. These targets also reduced low-frequency activity in this network, an established marker of successful memory encoding. These data reveal how anatomical and functional networks mediate stimulation's behavioral and physiological effects, provide further evidence that closed-loop LTC stimulation can improve episodic memory, and suggest a method for optimizing neuromodulation through improved stimulation targeting.

Pathological neurons generate ripples at the UP-DOWN transition disrupting information transfer.

Objective: To confirm and investigate why pathological HFOs (pHFOs), including Ripples [80-200 Hz] and fast ripples [200-600 Hz], are generated during the UP-DOWN transition of the slow wave and if pHFOs interfere with information transmission. Methods: We isolated 217 total units from 175.95 iEEG contact-hours of synchronized macro- and microelectrode recordings from 6 patients. Sleep slow oscillation (0.1-2 Hz) epochs were identified in the iEEG recording. iEEG HFOs that occurred superimposed on the slow wave were transformed to phasors and adjusted by the phase of maximum firing in nearby units (i.e., maximum UP). We tested whether, in the seizure onset zone (SOZ), HFOs and associated action potentials (AP) occur more often at the UP-DOWN transition. We also examined ripple temporal correlations using cross correlograms. Results: At the group level in the SOZ, HFO and HFO-associated AP probability was highest during the UP-DOWN transition of slow wave excitability (p<<0.001). In the non-SOZ, HFO and HFO-associated AP was highest during the DOWN-UP transition (p<<0.001). At the unit level in the SOZ, 15.6% and 20% of units exhibited more robust firing during ripples (Cohen's d=0.11-0.83) and fast ripples (d=0.36-0.90) at the UP-DOWN transition (p<0.05 f.d.r corrected), respectively. By comparison, also in the SOZ, 6.6% (d=0.14-0.30) and 8.5% (d=0.33-0.41) of units had significantly less firing during ripples and fast ripples at the UP-DOWN transition, respectively. Additional data shows ripple temporal correlations, involving global slow waves, between the hippocampus, entorhinal cortex, and parahippocampal gyrus were reduced by ~50-80% in the SOZ compared to the non-SOZ (N=3). Significance: The UP-DOWN transition of slow wave excitability facilitates the activation of pathological neurons to generate pHFOs. The pathological neurons and pHFOs disrupt ripple temporal correlations across brain regions that transfer information and may be important in memory consolidation.

Long-term outcomes of mesial temporal laser interstitial thermal therapy for drug-resistant epilepsy and subsequent surgery for seizure recurrence: a multi-centre cohort study.

BACKGROUND: Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) is a minimally invasive alternative to surgical resection for drug-resistant mesial temporal lobe epilepsy (mTLE). Reported rates of seizure freedom are variable and long-term durability is largely unproven. Anterior temporal lobectomy (ATL) remains an option for patients with MRgLITT treatment failure. However, the safety and efficacy of this staged strategy is unknown. METHODS: This multicentre, retrospective cohort study included 268 patients consecutively treated with mesial temporal MRgLITT at 11 centres between 2012 and 2018. Seizure outcomes and complications of MRgLITT and any subsequent surgery are reported. Predictive value of preoperative variables for seizure outcome was assessed. RESULTS: Engel I seizure freedom was achieved in 55.8% (149/267) at 1 year, 52.5% (126/240) at 2 years and 49.3% (132/268) at the last follow-up ≥1 year (median 47 months). Engel I or II outcomes were achieved in 74.2% (198/267) at 1 year, 75.0% (180/240) at 2 years and 66.0% (177/268) at the last follow-up. Preoperative focal to bilateral tonic-clonic seizures were independently associated with seizure recurrence. Among patients with seizure recurrence, 14/21 (66.7%) became seizure-free after subsequent ATL and 5/10 (50%) after repeat MRgLITT at last follow-up≥1 year. CONCLUSIONS: MRgLITT is a viable treatment with durable outcomes for patients with drug-resistant mTLE evaluated at a comprehensive epilepsy centre. Although seizure freedom rates were lower than reported with ATL, this series represents the early experience of each centre and a heterogeneous cohort. ATL remains a safe and effective treatment for well-selected patients who fail MRgLITT.

Sudden unexpected death in epilepsy during cenobamate clinical development.

OBJECTIVE: We assessed mortality, sudden unexpected death in epilepsy (SUDEP), and standardized mortality ratio (SMR) among adults treated with cenobamate during the cenobamate clinical development program. METHODS: We retrospectively analyzed deaths among all adults with uncontrolled focal (focal to bilateral tonic-clonic [FBTC], focal impaired awareness, focal aware) or primary generalized tonic-clonic (PGTC) seizures who received ≥1 dose of adjunctive cenobamate in completed and ongoing phase 2 and 3 clinical studies. In patients with focal seizures from completed studies, median baseline seizure frequencies ranged from 2.8 to 11 seizures per 28 days and median epilepsy duration ranged from 20 to 24 years. Total person-years included all days that a patient received cenobamate during completed studies or up to June 1, 2022, for ongoing studies. All deaths were evaluated by two epileptologists. All-cause mortality and SUDEP rates were expressed per 1000 person-years. RESULTS: A total of 2132 patients (n = 2018 focal epilepsy; n = 114 idiopathic generalized epilepsy) were exposed to cenobamate for 5693 person-years. Approximately 60% of patients with focal seizures and all patients in the PGTC study had tonic-clonic seizures. A total of 23 deaths occurred (all in patients with focal epilepsy), for an all-cause mortality rate of 4.0 per 1000 person-years. Five cases of definite or probable SUDEP were identified, for a rate of .88 per 1000 person-years. Of the 23 overall deaths, 22 patients (96%) had FBTC seizures, and all 5 of the SUDEP patients had a history of FBTC seizures. The duration of exposure to cenobamate for patients with SUDEP ranged from 130 to 620 days. The SMR among cenobamate-treated patients in completed studies (5515 person-years of follow-up) was 1.32 (95% confidence interval [CI] .84-2.0), which was not significantly different from the general population. SIGNIFICANCE: These data suggest that effective long-term medical treatment with cenobamate may reduce excess mortality associated with epilepsy.

Pre-surgical features of intrinsic brain networks predict single and joint epilepsy surgery outcomes.

Despite the effectiveness of surgical interventions for the treatment of intractable focal temporal lobe epilepsy (TLE), the substrates that support good outcomes are poorly understood. While algorithms have been developed for the prediction of either seizure or cognitive/psychiatric outcomes alone, no study has reported on the functional and structural architecture that supports joint outcomes. We measured key aspects of pre-surgical whole brain functional/structural network architecture and evaluated their ability to predict post-operative seizure control in combination with cognitive/psychiatric outcomes. Pre-surgically, we identified the intrinsic connectivity networks (ICNs) unique to each person through independent component analysis (ICA), and computed: (1) the spatial-temporal match between each person's ICA components and established, canonical ICNs, (2) the connectivity strength within each identified person-specific ICN, (3) the gray matter (GM) volume underlying the person-specific ICNs, and (4) the amount of variance not explained by the canonical ICNs for each person. Post-surgical seizure control and reliable change indices of change (for language [naming, phonemic fluency], verbal episodic memory, and depression) served as binary outcome responses in random forest (RF) models. The above functional and structural measures served as input predictors. Our empirically derived ICN-based measures customized to the individual showed that good joint seizure and cognitive/psychiatric outcomes depended upon higher levels of brain reserve (GM volume) in specific networks. In contrast, singular outcomes relied on systematic, idiosyncratic variance in the case of seizure control, and the weakened pre-surgical presence of functional ICNs that encompassed the ictal temporal lobe in the case of cognitive/psychiatric outcomes. Our data made clear that the ICNs differed in their propensity to provide reserve for adaptive outcomes, with some providing structural (brain), and others functional (cognitive) reserve. Our customized methodology demonstrated that when substantial unique, patient-specific ICNs are present prior to surgery there is a reliable association with poor post-surgical seizure control. These ICNs are idiosyncratic in that they did not match the canonical, normative ICNs and, therefore, could not be defined functionally, with their location likely varying by patient. This important finding suggested the level of highly individualized ICN's in the epileptic brain may signal the emergence of epileptogenic activity after surgery.

Fast ripples reflect increased excitability that primes epileptiform spikes.

The neuronal circuit disturbances that drive interictal and ictal epileptiform discharges remains elusive. Using a combination of extraoperative macro- and micro-electrode interictal recordings in six presurgical patients during non-rapid eye movement (REM) sleep we found that, exclusively in the seizure onset zone, fast ripples (FR; 200-600Hz), but not ripples (80-200 Hz), frequently occur <300 msec before an interictal intracranial EEG (iEEG) spike with a probability exceeding chance (bootstrapping, p<1e-5). Such FR events are associated with higher spectral power (p<1e-10) and correlated with more vigorous neuronal firing than solitary FR (generalized linear mixed-effects model, GLMM, p<1e-3) irrespective of FR power. During the iEEG spike that follows a FR, action potential firing is lower than during a iEEG spike alone (GLMM, p<1e-10), reflecting an inhibitory restraint of iEEG spike initiation. In contrast, ripples do not appear to prime epileptiform spikes. We next investigated the clinical significance of pre-spike FR in a separate cohort of 23 patients implanted with stereo EEG electrodes who underwent resections. In non-REM sleep recordings, sites containing a high proportion of FR preceding iEEG spikes correlate with brain areas where seizures begin more than solitary FR (p<1e-5). Despite this correlation, removal of these sites does not guarantee seizure freedom. These results are consistent with the hypothesis that FR preceding EEG spikes reflect an increase in local excitability that primes EEG spike discharges preferentially in the seizure onset zone and that epileptogenic brain regions are necessary, but not sufficient, for initiating interictal epileptiform discharges.