Characterizing the safety profile of vagus nerve stimulation devices for epilepsy from 21,448 manufacturer and user reports.

OBJECTIVE: This study summarizes medical device reports (MDRs) associated with adverse events for vagus nerve stimulation (VNS) devices indicated for epilepsy as reported by the Manufacturer and User Facility Device Experience (MAUDE) database of the US Food and Drug Administration. METHODS: The MAUDE database was surveyed for MDRs from November 2013 to September 2022 regarding VNS devices for epilepsy. Event descriptions, device problems, correlated patient consequences, and device models were grouped and analyzed in Python. Based on event description, revision surgeries and other unique events were identified. Revenue from VNS device sales was used to approximate growth in their use over time. RESULTS: A total of 21,448 MDRs met the inclusion criteria. High VNS impedance, the most prevalent device malfunction overall (17.0% of MDRs), was the most common factor for 18 of the 102 encountered patient problems and led to 1001 revision surgeries (3371 total revisions). Included in those 18 device malfunctions were 3 of the top 6 occurring patient problems: seizure recurrence (9.9% associated with high impedance; encompassed focal, absence, and grand mal subtypes), death (1.3%), and generalized pain (7.9%). The next 4 top cited device malfunctions-lead fracture (13.7% of MDRs), operational issue (6.6%), battery problem holding charge (4.2%), and premature end-of-life indicator (2.9%)-differed widely in their percentage of cases that did not impact patients (77.4%, 57.3%, 48.9%, and 92.2%, respectively), highlighting differing malfunction severities. Seizure recurrence, the most prevalent patient impact, was the outcome most associated with 32 of the 68 encountered device problems, including high impedance (12.8%), lead fracture (12.2%), operational issue (18.4%), battery problem holding charge (31.2%), and premature end-of-life indicator (8.9%), which comprised the top 5 occurring device problems. In general, MDRs spanned a diverse range including device age, hardware, software, and surgeon or manufacturer error. Trends were seen over time with declining annual MDRs coupled with a rise in the use of VNS devices as gauged by revenue growth. Shifting device and patient problem profiles were also seen in successive models, reflecting engineering updates. CONCLUSIONS: This study characterizes the most common and consequential side effects of VNS devices for epilepsy while clarifying likely causes. In addition, the outcomes of 68 distinct device malfunctions were identified, including many not ubiquitously present in literature, lending critical perspective to clinical practice.

Differential cortical layer engagement during seizure initiation and spread in humans.

Despite decades of research, we still do not understand how spontaneous human seizures start and spread - especially at the level of neuronal microcircuits. In this study, we used laminar arrays of micro-electrodes to simultaneously record the local field potentials and multi-unit neural activities across the six layers of the neocortex during focal seizures in humans. We found that, within the ictal onset zone, the discharges generated during a seizure consisted of current sinks and sources only within the infra-granular and granular layers. Outside of the seizure onset zone, ictal discharges reflected current flow in the supra-granular layers. Interestingly, these patterns of current flow evolved during the course of the seizure - especially outside the seizure onset zone where superficial sinks and sources extended into the deeper layers. Based on these observations, a framework describing cortical-cortical dynamics of seizures is proposed with implications for seizure localization, surgical targeting, and neuromodulation techniques to block the generation and propagation of seizures.

Interictal EEG source connectivity to localize the epileptogenic zone in patients with drug-resistant epilepsy: A machine learning approach.

OBJECTIVE: To deconstruct the epileptogenic networks of patients with drug-resistant epilepsy (DRE) using source functional connectivity (FC) analysis; unveil the FC biomarkers of the epileptogenic zone (EZ); and develop machine learning (ML) models to estimate the EZ using brief interictal electroencephalography (EEG) data. METHODS: We analyzed scalp EEG from 50 patients with DRE who had surgery. We reconstructed the activity (electrical source imaging [ESI]) of virtual sensors (VSs) across the whole cortex and computed FC separately for epileptiform and non-epileptiform EEG epochs (with or without spikes). In patients with good outcome (Engel 1a), four cortical regions were defined: EZ (resection) and three non-epileptogenic zones (NEZs) in the same and opposite hemispheres. Region-specific FC features in six frequency bands and three spatial ranges (long, short, inner) were compared between regions (Wilcoxon sign-rank). We developed ML classifiers to identify the VSs in the EZ using VS-specific FC features. Cross-validation was performed using good outcome data. Performance was compared with poor outcomes and interictal spike localization. RESULTS: FC differed between EZ and NEZs (p < .05) during non-epileptiform and epileptiform epochs, showing higher FC in the EZ than its homotopic contralateral NEZ. During epileptiform epochs, the NEZ in the epileptogenic hemisphere showed higher FC than its contralateral NEZ. In good outcome patients, the ML classifiers reached 75% accuracy to the resection (91% sensitivity; 74% specificity; distance from EZ: 38 mm) using epileptiform epochs (gamma and beta frequency bands) and 62% accuracy using broadband non-epileptiform epochs, both outperforming spike localization (accuracy = 47%; p < .05; distance from EZ: 57 mm). Lower performance was seen in poor outcomes. SIGNIFICANCE: We present an FC approach to extract EZ biomarkers from brief EEG data. Increased FC in various frequencies characterized the EZ during epileptiform and non-epileptiform epochs. FC-based ML models identified the resection better in good than poor outcome patients, demonstrating their potential for presurgical use in pediatric DRE.

Aberrant fast spiking interneuronal activity precedes seizure transitions in humans.

There is active debate regarding how GABAergic function changes during seizure initiation and propagation, and whether interneuronal activity drives or impedes the pathophysiology. Here, we track cell-type specific firing during spontaneous human seizures to identify neocortical mechanisms of inhibitory failure. Fast-spiking interneuron activity was maximal over 1 second before equivalent excitatory increases, and showed transitions to out-of-phase firing prior to local tissue becoming incorporated into the seizure-driving territory. Using computational modeling, we linked this observation to transient saturation block as a precursor to seizure invasion, as supported by multiple lines of evidence in the patient data. We propose that transient blocking of inhibitory firing due to selective fast-spiking interneuron saturation-resulting from intense excitatory synaptic drive-is a novel mechanism that contributes to inhibitory failure, allowing seizure propagation.

Sleep Spindle Generation Before and After Epilepsy Surgery: A Source Imaging Study in Children with Drug-Resistant Epilepsy.

INTRODUCTION: Literature lacks studies investigating the cortical generation of sleep spindles in drug-resistant epilepsy (DRE) and how they evolve after resection of the epileptogenic zone (EZ). Here, we examined sleep EEGs of children with focal DRE who became seizure-free after focal epilepsy surgery, and aimed to investigate the changes in the spindle generation before and after the surgery using low-density scalp EEG and electrical source imaging (ESI). METHODS: We analyzed N2-sleep EEGs from 19 children with DRE before and after surgery. We identified slow (8-12 Hz) and fast spindles (13-16 Hz), computed their spectral features and cortical generators through ESI and computed their distance from the EZ and irritative zone (IZ). We performed two-way ANOVA testing the effect of spindle type (slow vs. fast) and surgical phase (pre-surgery vs. post-surgery) on each feature. RESULTS: Power, frequency and cortical activation of slow spindles increased after surgery (p < 0.005), while this was not seen for fast spindles. Before surgery, the cortical generators of slow spindles were closer to the EZ (57.3 vs. 66.2 mm, p = 0.007) and IZ (41.3 vs. 55.5 mm, p = 0.02) than fast spindle generators. CONCLUSIONS: Our data indicate alterations in the EEG slow spindles after resective epilepsy surgery. Fast spindle generation on the contrary did not change after surgery. Although the study is limited by its retrospective nature, lack of healthy controls, and reduced cortical spatial sampling, our findings suggest a spatial relationship between the slow spindles and the epileptogenic generators.

Somatic Mosaicism in PIK3CA Variant Correlates With Stereoelectroencephalography-Derived Electrophysiology.

Objectives: Brain-limited pathogenic somatic variants are associated with focal pediatric epilepsy, but reliance on resected brain tissue samples has limited our ability to correlate epileptiform activity with abnormal molecular pathology. We aimed to identify the pathogenic variant and map variant allele fractions (VAFs) across an abnormal region of epileptogenic brain in a patient who underwent stereoelectroencephalography (sEEG) and subsequent motor-sparing left frontal disconnection. Methods: We extracted genomic DNA from peripheral blood, brain tissue resected from peri-sEEG electrode regions, and microbulk brain tissue adherent to sEEG electrodes. Samples were mapped based on an anatomic relationship with the presumed seizure onset zone (SOZ). We performed deep panel sequencing of amplified and unamplified DNA to identify pathogenic variants with subsequent orthogonal validation. Results: We detect a pathogenic somatic PIK3CA variant, c.1624G>A (p.E542K), in the brain tissue samples, with VAF inversely correlated with distance from the SOZ. In addition, we identify this variant in amplified electrode-derived samples, albeit with lower VAFs. Discussion: We demonstrate regional mosaicism across epileptogenic tissue, suggesting a correlation between variant burden and SOZ. We also validate a pathogenic variant from individual amplified sEEG electrode-derived brain specimens, although further optimization of techniques is required.

Complications of Intracranial Multimodal Monitoring for Neurocritical Care: A Systematic Review and Meta-Analysis.

Intracranial multimodal monitoring (iMMM) is increasingly used for neurocritical care. However, concerns arise regarding iMMM invasiveness considering limited evidence in its clinical significance and safety profile. We conducted a synthesis of evidence regarding complications associated with iMMM to delineate its safety profile. We performed a systematic review and meta-analysis (PROSPERO Registration Number: CRD42021225951) according to the Preferred Reporting Items for Systematic Review and Meta-Analysis and Peer Review of Electronic Search Strategies guidelines to retrieve evidence from studies reporting iMMM use in humans that mention related complications. We assessed risk of bias using the Newcastle-Ottawa Scale and funnel plots. The primary outcomes were iMMM complications. The secondary outcomes were putative risk factors. Of the 366 screened articles, 60 met the initial criteria and were further assessed by full-text reading. We included 22 studies involving 1206 patients and 1434 iMMM placements. Most investigators used a bolt system (85.9%) and a three-lumen device (68.8%), mainly inserting iMMM into the most injured hemisphere (77.9%). A total of 54 postoperative intracranial hemorrhages (pooled rate of 4%; 95% confidence interval [CI] 0-10%; I2 86%, p < 0.01 [random-effects model]) was reported, along with 46 misplacements (pooled rate of 6%; 95% CI 1-12%; I2 78%, p < 0.01) and 16 central nervous system infections (pooled rate of 0.43%; 95% CI 0-2%; I2 64%, p < 0.01). We found 6 system breakings, 18 intracranial bone fragments, and 5 cases of pneumocephalus. Currently, iMMM systems present a similar safety profile as intracranial devices commonly used in neurocritical care. Long-term outcomes of prospective studies will complete the benefit-risk assessment of iMMM in neurocritical care. Consensus-based reporting guidelines on iMMM use are needed to bolster future collaborative efforts.

Machine learning models for predicting seizure outcome after MR-guided laser interstitial thermal therapy in children.

OBJECTIVE: MR-guided laser interstitial thermal therapy (MRgLITT) is associated with lower seizure-free outcome but better safety profile compared to open surgery. However, the predictors of seizure freedom following MRgLITT remain uncertain. This study aimed to use machine learning to predict seizure-free outcome following MRgLITT and to identify important predictors of seizure freedom in children with drug-resistant epilepsy. METHODS: This multicenter study included children treated with MRgLITT for drug-resistant epilepsy at 13 epilepsy centers. The authors used clinical data, diagnostic investigations, and ablation features to predict seizure-free outcome at 1 year post-MRgLITT. Patients from 12 centers formed the training cohort, and patients in the remaining center formed the testing cohort. Five machine learning algorithms were developed on the training data by using 10-fold cross-validation, and model performance was measured on the testing cohort. The models were developed and tested on the complete feature set. Subsequently, 3 feature selection methods were used to identify important predictors. The authors then assessed performance of the parsimonious models based on these important variables. RESULTS: This study included 268 patients who underwent MRgLITT, of whom 44.4% had achieved seizure freedom at 1 year post-MRgLITT. A gradient-boosting machine algorithm using the complete feature set yielded the highest area under the curve (AUC) on the testing set (AUC 0.67 [95% CI 0.50-0.82], sensitivity 0.71 [95% CI 0.47-0.88], and specificity 0.66 [95% CI 0.50-0.81]). Logistic regression, random forest, support vector machine, and neural network yielded lower AUCs (0.58-0.63) compared to the gradient-boosting machine but the findings were not statistically significant (all p > 0.05). The 3 feature selection methods identified video-EEG concordance, lesion size, preoperative seizure frequency, and number of antiseizure medications as good prognostic features for predicting seizure freedom. The parsimonious models based on important features identified by univariate feature selection slightly improved model performance compared to the complete feature set. CONCLUSIONS: Understanding the predictors of seizure freedom after MRgLITT will assist with prognostication.

Influence of extent and age at corpus callosotomy on seizure outcomes. A single center experience.

Corpus callosotomy (CC) is a palliative treatment for drop seizures in patients with drug-resistant nonlocalizable epilepsy. We compared drop seizure outcomes between patients undergoing anterior CC versus complete CC and examined factors impacting outcomes for drop seizures including age at CC and duration of epilepsy. A retrospective review of patients who underwent CC between 2003 and 2022 with a minimum of 6 months postsurgical follow-up was included. Outcome measure for drop seizures included seizure reduction ≥50% from baseline as well as elimination of drop seizures. Thirty-eight patients were included. Overall, ≥50% reduction in drop seizures occurred in nearly 70% (23 out of 33) patients with complete elimination in 58% (19 out of 33). Compared with anterior CC (n = 13), patients undergoing complete CC (n = 25) had increased likelihood of ≥50% reduction (p = 0.006) or elimination (p = 0.024) of drop seizures. Regression analysis showed that complete CC was the primary predictor for improved drop seizure outcomes (elimination, p = 0.014 or ≥50% reduction, p = 0.006), while age at CC and duration of epilepsy did not impact the outcomes. Compared to anterior CC, complete CC was significantly more likely to lead to improvement/freedom from drop seizures. Age at CC or duration of epilepsy did not influence drop seizure outcomes.

Focal drug-resistant temporal lobe epilepsy associated with an ipsilateral anterior choroidal artery aneurysm: illustrative case.

BACKGROUND: The occurrence of both an intracranial aneurysm and epilepsy, especially drug-resistant epilepsy (DRE), is rare. Although the overall incidence of aneurysms associated with DRE is unclear, it is thought to be particularly infrequent in the pediatric population. Surgical ligation of the offending aneurysm has been reported in conjunction with resolving seizure activity, although few cases have cited a combined approach of aneurysm ligation and resection of an epileptogenic focus. OBSERVATIONS: We present the case of a 14-year-old female patient with drug-resistant temporal lobe epilepsy and an ipsilateral supraclinoid internal carotid artery aneurysm. Seizure semiology, electroencephalography monitoring, and magnetic resonance imaging all indicated a left temporal epileptogenic focus, in addition to an incidental aneurysm. The authors recommended a combined surgery involving resection of the temporal lesion and surgical clip ligation of the aneurysm. Near-total resection and successful ligation were achieved, and the patient has remained seizure free since surgery at 1 year postoperatively. LESSONS: In patients with focal DRE and an adjacent intracranial aneurysm, a combined surgical approach involving both resection and surgical ligation can be used. Several surgical timing and neuroanesthetic considerations should be made to ensure the overall safety and efficacy of this procedure.

Electromagnetic source imaging predicts surgical outcome in children with focal cortical dysplasia.

OBJECTIVE: To evaluate the diagnostic accuracy of electromagnetic source imaging (EMSI) in localizing spikes and predict surgical outcome in children with drug resistant epilepsy (DRE) due to focal cortical dysplasia (FCD). METHODS: We retrospectively analyzed magnetoencephalography (MEG) and high-density (HD-EEG) data from 23 children with FCD-associated DRE who underwent intracranial EEG and surgery. We localized spikes using equivalent current dipole (ECD) fitting, dipole clustering, and dynamical statistical parametric mapping (dSPM) on EMSI, electric source imaging (ESI), and magnetic source imaging (MSI). We calculated the distance from the seizure onset zone (DSOZ) and resection (DRES). We estimated receiver operating characteristic (ROC) curves with Youden's index (J) to predict outcome. RESULTS: EMSI presented shorter DSOZ (15.18 ± 9.06 mm) and DRES (8.56 ± 6.24 mm) compared to ESI (DSOZ: 25.04 ± 16.20 mm, p < 0.009; DRES: 18.88 ± 17.30 mm, p < 0.03) and MSI (DSOZ: 23.37 ± 8.98 mm, p < 0.03; DRES: 15.51 ± 10.11 mm, p < 0.02) for clustering in patients with good outcome. Clustering showed shorter DSOZ and DRES compared to ECD fitting and dSPM (p < 0.05). EMSI had higher performance as outcome predictor (J = 70.63%) compared to ESI (J = 41.27%) and MSI (J = 33.33%) for clustering. CONCLUSIONS: EMSI provides superior localization and improved predictive performance than individual modalities. SIGNIFICANCE: EMSI can help the surgical planning and facilitate the localization of epileptogenic foci.

The role of superficial and deep layers in the generation of high frequency oscillations and interictal epileptiform discharges in the human cortex.

Describing intracortical laminar organization of interictal epileptiform discharges (IED) and high frequency oscillations (HFOs), also known as ripples. Defining the frequency limits of slow and fast ripples. We recorded potential gradients with laminar multielectrode arrays (LME) for current source density (CSD) and multi-unit activity (MUA) analysis of interictal epileptiform discharges IEDs and HFOs in the neocortex and mesial temporal lobe of focal epilepsy patients. IEDs were observed in 20/29, while ripples only in 9/29 patients. Ripples were all detected within the seizure onset zone (SOZ). Compared to hippocampal HFOs, neocortical ripples proved to be longer, lower in frequency and amplitude, and presented non-uniform cycles. A subset of ripples (≈ 50%) co-occurred with IEDs, while IEDs were shown to contain variable high-frequency activity, even below HFO detection threshold. The limit between slow and fast ripples was defined at 150 Hz, while IEDs' high frequency components form clusters separated at 185 Hz. CSD analysis of IEDs and ripples revealed an alternating sink-source pair in the supragranular cortical layers, although fast ripple CSD appeared lower and engaged a wider cortical domain than slow ripples MUA analysis suggested a possible role of infragranularly located neural populations in ripple and IED generation. Laminar distribution of peak frequencies derived from HFOs and IEDs, respectively, showed that supragranular layers were dominated by slower (< 150 Hz) components. Our findings suggest that cortical slow ripples are generated primarily in upper layers while fast ripples and associated MUA in deeper layers. The dissociation of macro- and microdomains suggests that microelectrode recordings may be more selective for SOZ-linked ripples. We found a complex interplay between neural activity in the neocortical laminae during ripple and IED formation. We observed a potential leading role of cortical neurons in deeper layers, suggesting a refined utilization of LMEs in SOZ localization.

Functional connectivity discriminates epileptogenic states and predicts surgical outcome in children with drug resistant epilepsy.

Normal brain functioning emerges from a complex interplay among regions forming networks. In epilepsy, these networks are disrupted causing seizures. Highly connected nodes in these networks are epilepsy surgery targets. Here, we assess whether functional connectivity (FC) using intracranial electroencephalography can quantify brain regions epileptogenicity and predict surgical outcome in children with drug resistant epilepsy (DRE). We computed FC between electrodes on different states (i.e. interictal without spikes, interictal with spikes, pre-ictal, ictal, and post-ictal) and frequency bands. We then estimated the electrodes' nodal strength. We compared nodal strength between states, inside and outside resection for good- (n = 22, Engel I) and poor-outcome (n = 9, Engel II-IV) patients, respectively, and tested their utility to predict the epileptogenic zone and outcome. We observed a hierarchical epileptogenic organization among states for nodal strength: lower FC during interictal and pre-ictal states followed by higher FC during ictal and post-ictal states (p < 0.05). We further observed higher FC inside resection (p < 0.05) for good-outcome patients on different states and bands, and no differences for poor-outcome patients. Resection of nodes with high FC was predictive of outcome (positive and negative predictive values: 47-100%). Our findings suggest that FC can discriminate epileptogenic states and predict outcome in patients with DRE.

Spike propagation mapping reveals effective connectivity and predicts surgical outcome in epilepsy.

Neurosurgical intervention is the best available treatment for selected patients with drug resistant epilepsy. For these patients, surgical planning requires biomarkers that delineate the epileptogenic zone, the brain area that is indispensable for the generation of seizures. Interictal spikes recorded with electrophysiological techniques are considered key biomarkers of epilepsy. Yet, they lack specificity, mostly because they propagate across brain areas forming networks. Understanding the relationship between interictal spike propagation and functional connections among the involved brain areas may help develop novel biomarkers that can delineate the epileptogenic zone with high precision. Here, we reveal the relationship between spike propagation and effective connectivity among onset and areas of spread and assess the prognostic value of resecting these areas. We analysed intracranial EEG data from 43 children with drug resistant epilepsy who underwent invasive monitoring for neurosurgical planning. Using electric source imaging, we mapped spike propagation in the source domain and identified three zones: onset, early-spread and late-spread. For each zone, we calculated the overlap and distance from surgical resection. We then estimated a virtual sensor for each zone and the direction of information flow among them via Granger causality. Finally, we compared the prognostic value of resecting these zones, the clinically-defined seizure onset zone and the spike onset on intracranial EEG channels by estimating their overlap with resection. We observed a spike propagation in source space for 37 patients with a median duration of 95 ms (interquartile range: 34-206), a spatial displacement of 14 cm (7.5-22 cm) and a velocity of 0.5 m/s (0.3-0.8 m/s). In patients with good surgical outcome (25 patients, Engel I), the onset had higher overlap with resection [96% (40-100%)] than early-spread [86% (34-100%), P = 0.01] and late-spread [59% (12-100%), P = 0.002], and it was also closer to resection than late-spread [5 mm versus 9 mm, P = 0.007]. We found an information flow from onset to early-spread in 66% of patients with good outcomes, and from early-spread to onset in 50% of patients with poor outcome. Finally, resection of spike onset, but not area of spike spread or the seizure onset zone, predicted outcome with positive predictive value of 79% and negative predictive value of 56% (P = 0.04). Spatiotemporal mapping of spike propagation reveals information flow from onset to areas of spread in epilepsy brain. Surgical resection of the spike onset disrupts the epileptogenic network and may render patients with drug resistant epilepsy seizure-free without having to wait for a seizure to occur during intracranial monitoring.

Spatiotemporal spike-centered averaging reveals symmetry of temporal and spatial components of the spike-LFP relationship during human focal seizures.

The electrographic manifestation of neural activity can reflect the relationship between the faster action potentials of individual neurons and the slower fluctuations of the local field potential (LFP). This relationship is typically examined in the temporal domain using the spike-triggered average. In this study, we add a spatial component to this relationship. Here we first derive a theoretical model of the spike-LFP relationship across a macroelectrode. This mathematical derivation showed a special symmetry in the spike-LFP relationship wherein a sinc function in the temporal domain predicts a sinc function in the spatial domain. We show that this theoretical result is observed in a real-world system by characterizing the spike-LFP relationship using microelectrode array (MEA) recordings of human focal seizures. To do this, we present a approach, termed the spatiotemporal spike-centered average (st-SCA), that allows for visualization of the spike-LFP relationship in both the temporal and spatial domains. We applied this method to 25 MEA recordings obtained from seven patients with pharmacoresistant focal epilepsy. Of the five patients with MEAs implanted in recruited territory, three exhibited spatiotemporal patterns consistent with a sinc function, and two exhibited spatiotemporal patterns resembling deep wells of excitation. These results suggest that in some cases characterization of the spike-LFP relationship in the temporal domain is sufficient to predict the underlying spatial pattern. Finally, we discuss the biological interpretation of these findings and propose that the sinc function may reflect the role of mid-range excitatory connections during seizure activity.

Non-invasive mapping of epileptogenic networks predicts surgical outcome.

Epilepsy is increasingly considered a disorder of brain networks. Studying these networks with functional connectivity can help identify hubs that facilitate the spread of epileptiform activity. Surgical resection of these hubs may lead patients who suffer from drug-resistant epilepsy to seizure freedom. Here, we aim to map non-invasively epileptogenic networks, through the virtual implantation of sensors estimated with electric and magnetic source imaging, in patients with drug-resistant epilepsy. We hypothesize that highly connected hubs identified non-invasively with source imaging can predict the epileptogenic zone and the surgical outcome better than spikes localized with conventional source localization methods (dipoles). We retrospectively analysed simultaneous high-density electroencephalography (EEG) and magnetoencephalography data recorded from 37 children and young adults with drug-resistant epilepsy who underwent neurosurgery. Using source imaging, we estimated virtual sensors at locations where intracranial EEG contacts were placed. On data with and without spikes, we computed undirected functional connectivity between sensors/contacts using amplitude envelope correlation and phase locking value for physiologically relevant frequency bands. From each functional connectivity matrix, we generated an undirected network containing the strongest connections within sensors/contacts using the minimum spanning tree. For each sensor/contact, we computed graph centrality measures. We compared functional connectivity and their derived graph centrality of sensors/contacts inside resection for good (n = 22, ILAE I) and poor (n = 15, ILAE II-VI) outcome patients, tested their ability to predict the epileptogenic zone in good-outcome patients, examined the association between highly connected hubs removal and surgical outcome and performed leave-one-out cross-validation to support their prognostic value. We also compared the predictive values of functional connectivity with those of dipoles. Finally, we tested the reliability of virtual sensor measures via Spearman's correlation with intracranial EEG at population- and patient-level. We observed higher functional connectivity inside than outside resection (P < 0.05, Wilcoxon signed-rank test) for good-outcome patients, on data with and without spikes across different bands for intracranial EEG and electric/magnetic source imaging and few differences for poor-outcome patients. These functional connectivity measures were predictive of both the epileptogenic zone and outcome (positive and negative predictive values ≥55%, validated using leave-one-out cross-validation) outperforming dipoles on spikes. Significant correlations were found between source imaging and intracranial EEG measures (0.4 ≤ rho ≤ 0.9, P < 0.05). Our findings suggest that virtual implantation of sensors through source imaging can non-invasively identify highly connected hubs in patients with drug-resistant epilepsy, even in the absence of frank epileptiform activity. Surgical resection of these hubs predicts outcome better than dipoles.

Cross-task specificity and within-task invariance of cognitive control processes.

Cognitive control involves flexibly combining multiple sensory inputs with task-dependent goals during decision making. Several tasks involving conflicting sensory inputs and motor outputs have been proposed to examine cognitive control, including the Stroop, Flanker, and multi-source interference task. Because these tasks have been studied independently, it remains unclear whether the neural signatures of cognitive control reflect abstract control mechanisms or specific combinations of sensory and behavioral aspects of each task. To address these questions, we record invasive neurophysiological signals from 16 patients with pharmacologically intractable epilepsy and compare neural responses within and between tasks. Neural signals differ between incongruent and congruent conditions, showing strong modulation by conflicting task demands. These neural signals are mostly specific to each task, generalizing within a task but not across tasks. These results highlight the complex interplay between sensory inputs, motor outputs, and task demands underlying cognitive control processes.

Stereoelectroencephalography followed by combined electrode removal and MRI-guided laser interstitial thermal therapy or open resection: a single-center series in pediatric patients with medically refractory epilepsy.

OBJECTIVE: Stereoelectroencephalography (SEEG) and MRI-guided laser interstitial thermal therapy (MRgLITT) have emerged as safe, effective, and less invasive alternatives to subdural grid placement and open resection, respectively, for the localization and treatment of medically refractory epilepsy (MRE) in children. Reported pediatric experience combining these complementary techniques is limited, with traditional workflows separating electrode removal and ablation/resection. The authors describe the largest reported series of pediatric epilepsy patients who underwent MRgLITT following SEEG contrasted with a cohort that underwent craniotomy following SEEG, combining ablation/resection with electrode explantation as standard practice. METHODS: The medical records of all patients with MRE who had undergone SEEG followed by MRgLITT or open resection/disconnection at Boston Children's Hospital between November 2015 and December 2020 were retrospectively reviewed. Primary outcome variables included surgical complication rates, length of hospital stay following treatment, and Engel classification at the last follow-up. RESULTS: Of 74 SEEG patients, 27 (median age 12.1 years, 63% female) underwent MRgLITT and 47 (median age 12.1 years, 49% female) underwent craniotomy. Seventy patients (95%) underwent SEEG followed by combined electrode removal and treatment. Eight MRgLITT cases (30%) and no open cases targeted the insula (p < 0.001). Complication rates did not differ, although trends toward more subdural/epidural hematomas, infarcts, and permanent unanticipated neurological deficits were evident following craniotomy, whereas a trend toward more temporary unanticipated neurological deficits was seen following MRgLITT. The median duration of hospitalization after treatment was 3 and 5 days for MRgLITT and open cases, respectively (p = 0.078). Seizure outcomes were similar between the cohorts, with 74% of MRgLITT and craniotomy patients attaining Engel class I or II outcomes (p = 0.386) at the last follow-up (median 1.1 and 1.9 years, respectively). CONCLUSIONS: MRgLITT and open resection following SEEG can both effectively treat MRE in pediatric patients and generally can be performed in a two-surgery workflow during a single hospitalization. In appropriately selected patients, MRgLITT tended to be associated with shorter hospitalizations and fewer complications following treatment and may be best suited for focal deep-seated targets associated with relatively challenging open surgical approaches.