Ictal Central Apnea Is Predictive of Mesial Temporal Seizure Onset: An Intracranial Investigation.

OBJECTIVE: Ictal central apnea (ICA) is a semiological sign of focal epilepsy, associated with temporal and frontal lobe seizures. In this study, using qualitative and quantitative approaches, we aimed to assess the localizational value of ICA. We also aimed to compare ICA clinical utility in relation to other seizure semiological features of focal epilepsy. METHODS: We analyzed seizures in patients with medically refractory focal epilepsy undergoing intracranial stereotactic electroencephalographic (SEEG) evaluations with simultaneous multimodal cardiorespiratory monitoring. A total of 179 seizures in 72 patients with reliable artifact-free respiratory signal were analyzed. RESULTS: ICA was seen in 55 of 179 (30.7%) seizures. Presence of ICA predicted a mesial temporal seizure onset compared to those without ICA (odds ratio = 3.8, 95% confidence interval = 1.3-11.6, p = 0.01). ICA specificity was 0.82. ICA onset was correlated with increased high-frequency broadband gamma (60-150Hz) activity in specific mesial or basal temporal regions, including amygdala, hippocampus, and fusiform and lingual gyri. Based on our results, ICA has an almost 4-fold greater association with mesial temporal seizure onset zones compared to those without ICA and is highly specific for mesial temporal seizure onset zones. As evidence of symptomatogenic areas, onset-synchronous increase in high gamma activity in mesial or basal temporal structures was seen in early onset ICA, likely representing anatomical substrates for ICA generation. INTERPRETATION: ICA recognition may help anatomoelectroclinical localization of clinical seizure onset to specific mesial and basal temporal brain regions, and the inclusion of these regions in SEEG evaluations may help accurately pinpoint seizure onset zones for resection. ANN NEUROL 2024;95:998-1008.

Reliable detection of generalized convulsive seizures using an off-the-shelf digital watch: A multisite phase 2 study.

OBJECTIVE: The aim of this study was to develop a machine learning algorithm using an off-the-shelf digital watch, the Samsung watch (SM-R800), and evaluate its effectiveness for the detection of generalized convulsive seizures (GCS) in persons with epilepsy. METHODS: This multisite epilepsy monitoring unit (EMU) phase 2 study included 36 adult patients. Each patient wore a Samsung watch that contained accelerometer, gyroscope, and photoplethysmographic sensors. Sixty-eight time and frequency domain features were extracted from the sensor data and were used to train a random forest algorithm. A testing framework was developed that would better reflect the EMU setting, consisting of (1) leave-one-patient-out cross-validation (LOPO CV) on GCS patients, (2) false alarm rate (FAR) testing on nonseizure patients, and (3) "fixed-and-frozen" prospective testing on a prospective patient cohort. Balanced accuracy, precision, sensitivity, and FAR were used to quantify the performance of the algorithm. Seizure onsets and offsets were determined by using video-electroencephalographic (EEG) monitoring. Feature importance was calculated as the mean decrease in Gini impurity during the LOPO CV testing. RESULTS: LOPO CV results showed balanced accuracy of .93 (95% confidence interval [CI] = .8-.98), precision of .68 (95% CI = .46-.85), sensitivity of .87 (95% CI = .62-.96), and FAR of .21/24 h (interquartile range [IQR] = 0-.90). Testing the algorithm on patients without seizure resulted in an FAR of .28/24 h (IQR = 0-.61). During the "fixed-and-frozen" prospective testing, two patients had three GCS, which were detected by the algorithm, while generating an FAR of .25/24 h (IQR = 0-.89). Feature importance showed that heart rate-based features outperformed accelerometer/gyroscope-based features. SIGNIFICANCE: Commercially available wearable digital watches that reliably detect GCS, with minimum false alarm rates, may overcome usage adoption and other limitations of custom-built devices. Contingent on the outcomes of a prospective phase 3 study, such devices have the potential to provide non-EEG-based seizure surveillance and forecasting in the clinical setting.

Brainstorm-DUNEuro: An integrated and user-friendly Finite Element Method for modeling electromagnetic brain activity.

Human brain activity generates scalp potentials (electroencephalography - EEG), intracranial potentials (iEEG), and external magnetic fields (magnetoencephalography - MEG). These electrophysiology (e-phys) signals can often be measured simultaneously for research and clinical applications. The forward problem involves modeling these signals at their sensors for a given equivalent current dipole configuration within the brain. While earlier researchers modeled the head as a simple set of isotropic spheres, today's magnetic resonance imaging (MRI) data allow for a detailed anatomic description of brain structures and anisotropic characterization of tissue conductivities. We present a complete pipeline, integrated into the Brainstorm software, that allows users to automatically generate an individual and accurate head model based on the subject's MRI and calculate the electromagnetic forward solution using the finite element method (FEM). The head model generation is performed by integrating the latest tools for MRI segmentation and FEM mesh generation. The final head model comprises the five main compartments: white-matter, gray-matter, CSF, skull, and scalp. The anisotropic brain conductivity model is based on the effective medium approach (EMA), which estimates anisotropic conductivity tensors from diffusion-weighted imaging (DWI) data. The FEM electromagnetic forward solution is obtained through the DUNEuro library, integrated into Brainstorm, and accessible with either a user-friendly graphical interface or scripting. With tutorials and example data sets available in an open-source format on the Brainstorm website, this integrated pipeline provides access to advanced FEM tools for electromagnetic modeling to a broader neuroscience community.

Stereoelectroencephalography-guided laser ablation in neocortical epilepsy: Electrophysiological correlations and outcome.

OBJECTIVE: We aimed to study the correlation between seizure outcomes in patients with drug-resistant epilepsy (DRE) who underwent laser interstitial thermal therapy (LITT) and stereoelectroencephalographic electrophysiologic patterns with respect to the extent of laser ablation. METHODS: We retrospectively analyzed 16 consecutive DRE patients who underwent LITT. A seizure onset zone (SOZ) was obtained from multidisciplinary patient management conferences and again was confirmed independently by two epileptologists based on conventional analysis. SOZs were retrospectively divided into localized, lobar and multilobar, and nonlocalized onset types. A posteriori-predicted epileptogenic zone (PEZ) was identified using the previously developed "EZ fingerprint" pipeline. The completeness of the SOZ and PEZ ablation was compared and correlated with the duration of seizure freedom (SF). RESULTS: Of 16 patients, 11 had an a posteriori-identified PEZ. Three patients underwent complete ablation of SOZ with curative intent, and the other 13 with palliative intent. Of three patients with complete ablation of the SOZ, two had concordant PEZ and SOZ and achieved 40- and 46-month SF without seizure recurrence. The remaining patient, without any PEZ identified, had seizure recurrence within 1 month. Six of 13 patients with partial ablation of the SOZ and PEZ achieved mean seizure freedom of 19.8 months (range = 1-44) with subsequent seizure recurrence. The remaining seven patients had partial ablation of the SOZ without the PEZ identified or ablation outside the PEZ with seizure recurrence within 1-2 months, except one patient who had 40-month seizure freedom after ablation of periventricular heterotopia. SIGNIFICANCE: Only complete ablation of the well-restricted SOZ concordant with the PEZ was associated with long-term SF, whereas partial ablation of the PEZ might lead to SF with eventual seizure recurrence. Failure to identify PEZ and ablation limited to the SOZ often led to 1-2 months of SF.

Stimulation-induced respiratory enhancement in corticothalamic regions.

OBJECTIVE: We aimed to identify corticothalamic areas and electrical stimulation paradigms that optimally enhance breathing. METHODS: Twenty-nine patients with medically intractable epilepsy were prospectively recruited in an epilepsy monitoring unit while undergoing stereoelectroencephalographic evaluation. Direct electrical stimulation in cortical and thalamic regions was carried out using low (<1 Hz) and high (≥10 Hz) frequencies, and low (<5 mA) and high (≥5 mA) current intensities, with pulse width of .1 ms. Electrocardiography, arterial oxygen saturation (SpO2 ), end-tidal carbon dioxide (ETCO2 ), oronasal airflow, and abdominal and thoracic plethysmography were monitored continuously during stimulations. Airflow signal was used to estimate breathing rate, tidal volume, and minute ventilation (MV) changes during stimulation, compared to baseline. RESULTS: Electrical stimulation increased MV in the amygdala, anterior cingulate, anterior insula, temporal pole, and thalamus, with an average increase in MV of 20.8% ± 28.9% (range = 0.2%-165.6%) in 19 patients. MV changes were associated with SpO2 and ETCO2 changes (p < .001). Effects on respiration were parameter and site dependent. Within amygdala, low-frequency stimulation of the medial region produced 78.49% greater MV change (p < .001) compared to high-frequency stimulation. Longer stimulation produced greater MV changes (an increase of 4.47% in MV for every additional 10 s, p = .04). SIGNIFICANCE: Stimulation of amygdala, anterior cingulate gyrus, anterior insula, temporal pole, and thalamus, using certain stimulation paradigms, enhances respiration. Among tested paradigms, low-frequency, low-intensity, long-duration stimulation of the medial amygdala is the most effective breathing enhancement stimulation strategy. Such approaches may pave the way for the future development of neuromodulatory techniques that aid rescue from seizure-related apnea, potentially as a targeted sudden unexpected death in epilepsy prevention method.

A unified view on beamformers for M/EEG source reconstruction.

Beamforming is a popular method for functional source reconstruction using magnetoencephalography (MEG) and electroencephalography (EEG) data. Beamformers, which were first proposed for MEG more than two decades ago, have since been applied in hundreds of studies, demonstrating that they are a versatile and robust tool for neuroscience. However, certain characteristics of beamformers remain somewhat elusive and there currently does not exist a unified documentation of the mathematical underpinnings and computational subtleties of beamformers as implemented in the most widely used academic open source software packages for MEG analysis (Brainstorm, FieldTrip, MNE, and SPM). Here, we provide such documentation that aims at providing the mathematical background of beamforming and unifying the terminology. Beamformer implementations are compared across toolboxes and pitfalls of beamforming analyses are discussed. Specifically, we provide details on handling rank deficient covariance matrices, prewhitening, the rank reduction of forward fields, and on the combination of heterogeneous sensor types, such as magnetometers and gradiometers. The overall aim of this paper is to contribute to contemporary efforts towards higher levels of computational transparency in functional neuroimaging.

Good scientific practice in EEG and MEG research: Progress and perspectives.

Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.

Limbic and paralimbic respiratory modulation: From inhibition to enhancement.

OBJECTIVE: Increased understanding of the role of cortical structures in respiratory control may help the understanding of seizure-induced respiratory dysfunction that leads to sudden unexpected death in epilepsy (SUDEP). The aim of this study was to characterize respiratory responses to electrical stimulation (ES), including inhibition and enhancement of respiration. METHODS: We prospectively recruited 19 consecutive patients with intractable epilepsy undergoing stereotactic electroencephalography (EEG) evaluation from June 2015 to June 2018. Inclusion criteria were patients ≥18 years in whom ES was indicated for clinical mapping of ictal onset or eloquent cortex as part of the presurgical evaluation. ES was carried out at 50 Hz, 0.2 msec, and 1-10 mA current intensity. Common brain regions sampled across all patients were amygdala (AMY), hippocampus (HG), anterior cingulate gyrus (CING), orbitofrontal cortex (OrbF), temporal neocortex (TNC), temporal pole (TP), and entorhinal cortex (ERC). Seven hundred fifty-five stimulations were conducted. Quantitative analysis of breathing signal, that is, changes in breathing rate (BR), depth (TV), and minute ventilation (MV), was carried out during ES using the BreathMetrics breathing waveform analysis toolbox. Electrocardiography, arterial oxygen saturation, end-tidal and transcutaneous carbon dioxide, nasal airflow, and abdominal and thoracic plethysmography were monitored continuously during stimulations. RESULTS: Electrical stimulation of TP and CING (at lower current strengths <3 mA) increased TV and MV. At >7-10 mA, CING decreased TV and MV. On the other hand, decreased TV and MV occurred with stimulation of mesial temporal structures such as AMY and HG. Breathing changes were dependent on stimulation intensity. Lateral temporal, entorhinal, and orbitofrontal cortices did not affect breathing either way. SIGNIFICANCE: These findings suggest that breathing responses other than apnea can be induced by ES. Identification of two regions-the temporal pole and anterior cingulate gyrus-for enhancement of breathing may be important in paving the way to future development of strategies for prevention of SUDEP.

Effective connectivity differs between focal cortical dysplasia types I and II.

OBJECTIVE: To determine whether brain connectivity differs between focal cortical dysplasia (FCD) types I and II. METHODS: We compared cortico-cortical evoked potentials (CCEPs) as measures of effective brain connectivity in 25 FCD patients with drug-resistant focal epilepsy who underwent intracranial evaluation with stereo-electroencephalography (SEEG). We analyzed the amplitude and latency of CCEP responses following ictal-onset single-pulse electrical stimulation (iSPES). RESULTS: In comparison to FCD type II, patients with type I demonstrated significantly larger responses in the electrodes near the ictal-onset zone (<50 mm). These findings persisted when controlling for the location of the epileptogenic zone, as noted in patients with temporal lobe epilepsies, as well as controlling for seizure type, as noted in patients with focal to bilateral tonic-clonic seizures (FBTCS). In type II, the root mean square (RMS) of CCEP responses dropped substantially from the early segment (10-60 ms) to the middle and late segments (60-600 ms). The middle and late CCEP latency segments showed the largest differences between FCD types I and II. SIGNIFICANCE: Focal cortical dysplasia type I may have a greater degree of cortical hyperexcitability as compared with FCD type II. In addition, FCD type II displays a more restrictive area of hyperexcitability in both temporal and spatial domains. In patients with FBTCS and type I FCD, the increased amplitudes of RMS in the middle and late CCEP periods appear consistent with the cortico-thalamo-cortical network involvement of FBTCS. The notable differences in degree and extent of hyperexcitability may contribute to the different postsurgical seizure outcomes noted between these two pathological substrates.

Comparison of beamformer implementations for MEG source localization.

Beamformers are applied for estimating spatiotemporal characteristics of neuronal sources underlying measured MEG/EEG signals. Several MEG analysis toolboxes include an implementation of a linearly constrained minimum-variance (LCMV) beamformer. However, differences in implementations and in their results complicate the selection and application of beamformers and may hinder their wider adoption in research and clinical use. Additionally, combinations of different MEG sensor types (such as magnetometers and planar gradiometers) and application of preprocessing methods for interference suppression, such as signal space separation (SSS), can affect the results in different ways for different implementations. So far, a systematic evaluation of the different implementations has not been performed. Here, we compared the localization performance of the LCMV beamformer pipelines in four widely used open-source toolboxes (MNE-Python, FieldTrip, DAiSS (SPM12), and Brainstorm) using datasets both with and without SSS interference suppression. We analyzed MEG data that were i) simulated, ii) recorded from a static and moving phantom, and iii) recorded from a healthy volunteer receiving auditory, visual, and somatosensory stimulation. We also investigated the effects of SSS and the combination of the magnetometer and gradiometer signals. We quantified how localization error and point-spread volume vary with the signal-to-noise ratio (SNR) in all four toolboxes. When applied carefully to MEG data with a typical SNR (3-15 â€‹dB), all four toolboxes localized the sources reliably; however, they differed in their sensitivity to preprocessing parameters. As expected, localizations were highly unreliable at very low SNR, but we found high localization error also at very high SNRs for the first three toolboxes while Brainstorm showed greater robustness but with lower spatial resolution. We also found that the SNR improvement offered by SSS led to more accurate localization.

Learning to define an electrical biomarker of the epileptogenic zone.

The role of fast activity as a potential biomarker in localization of the epileptogenic zone (EZ) remains controversial due to recently reported unsatisfactory performance. We recently identified a "fingerprint" of the EZ as a time-frequency pattern that is defined by a combination of preictal spike(s), fast oscillatory activity, and concurrent suppression of lower frequencies. Here we examine the generalizability of the fingerprint in application to an independent series of patients (11 seizure-free and 13 non-seizure-free after surgery) and show that the fingerprint can also be identified in seizures with lower frequency (such as beta) oscillatory activity. In the seizure-free group, only 5 of 47 identified EZ contacts were outside the resection. In contrast, in the non-seizure-free group, 104 of 142 identified EZ contacts were outside the resection. We integrated the fingerprint prediction with the subject's MR images, thus providing individualized anatomical estimates of the EZ. We show that these fingerprint-based estimates in seizure-free patients are almost always inside the resection. On the other hand, for a large fraction of the nonseizure-free patients the estimated EZ was not well localized and was partially or completely outside the resection, which may explain surgical failure in such cases. We also show that when mapping fast activity alone onto MR images, the EZ was often over-estimated, indicating a reduced discriminative ability for fast activity relative to the full fingerprint for localization of the EZ.

A fingerprint of the epileptogenic zone in human epilepsies.

Defining a bio-electrical marker for the brain area responsible for initiating a seizure remains an unsolved problem. Fast gamma activity has been identified as the most specific marker for seizure onset, but conflicting results have been reported. In this study, we describe an alternative marker, based on an objective description of interictal to ictal transition, with the aim of identifying a time-frequency pattern or 'fingerprint' that can differentiate the epileptogenic zone from areas of propagation. Seventeen patients who underwent stereoelectroencephalography were included in the study. Each had seizure onset characterized by sustained gamma activity and were seizure-free after tailored resection or laser ablation. We postulated that the epileptogenic zone was always located inside the resection region based on seizure freedom following surgery. To characterize the ictal frequency pattern, we applied the Morlet wavelet transform to data from each pair of adjacent intracerebral electrode contacts. Based on a visual assessment of the time-frequency plots, we hypothesized that a specific time-frequency pattern in the epileptogenic zone should include a combination of (i) sharp transients or spikes; preceding (ii) multiband fast activity concurrent; with (iii) suppression of lower frequencies. To test this hypothesis, we developed software that automatically extracted each of these features from the time-frequency data. We then used a support vector machine to classify each contact-pair as being within epileptogenic zone or not, based on these features. Our machine learning system identified this pattern in 15 of 17 patients. The total number of identified contacts across all patients was 64, with 58 localized inside the resected area. Subsequent quantitative analysis showed strong correlation between maximum frequency of fast activity and suppression inside the resection but not outside. We did not observe significant discrimination power using only the maximum frequency or the timing of fast activity to differentiate contacts either between resected and non-resected regions or between contacts identified as epileptogenic versus non-epileptogenic. Instead of identifying a single frequency or a single timing trait, we observed the more complex pattern described above that distinguishes the epileptogenic zone. This pattern encompasses interictal to ictal transition and may extend until seizure end. Its time-frequency characteristics can be explained in light of recent models emphasizing the role of fast inhibitory interneurons acting on pyramidal cells as a prominent mechanism in seizure triggering. The pattern clearly differentiates the epileptogenic zone from areas of propagation and, as such, represents an epileptogenic zone 'fingerprint'.awx306media15687076823001.

Connectivity in ictal single photon emission computed tomography perfusion: a cortico-cortical evoked potential study.

Subtraction ictal and interictal single photon emission computed tomography can demonstrate complex ictal perfusion patterns. Regions with ictal hyperperfusion are suggested to reflect seizure onset and propagation pathways. The significance of ictal hypoperfusion is not well understood. The aim of this study was to verify whether ictal perfusion changes, both hyper- and hypoperfusion, correspond to electrically connected brain networks. A total of 36 subtraction ictal and interictal perfusion studies were analysed in 31 consecutive medically refractory focal epilepsy patients, evaluated by stereo-electroencephalography that demonstrated a single focal onset. Cortico-cortical evoked potential studies were performed after repetitive electrical stimulation of the ictal onset zone. Evoked responses at electrode contacts outside the stimulation site were used as a measure of connectivity. The evoked responses at these electrodes were compared to ictal perfusion values noted at these locations. In 67% of studies, evoked responses were significantly larger in hyperperfused compared to baseline-perfused areas. The majority of hyperperfused contacts also had significantly increased evoked responses relative to pre-stimulus electroencephalogram. In contrast, baseline-perfused and hypoperfused contacts mainly demonstrated non-significant evoked responses. Finally, positive significant correlations (P < 0.05) were found between perfusion scores and evoked responses in 61% of studies. When the stimulated ictal onset area was hyperperfused, 82% of studies demonstrated positive significant correlations. Following stimulation of hyperperfused areas outside seizure onset, positive significant correlations between perfusion changes and evoked responses could be seen, suggesting bidirectional connectivity. We conclude that strong connectivity was demonstrated between the ictal onset zone and hyperperfused regions, while connectivity was weaker in the direction of baseline-perfused or hypoperfused areas. In trying to understand a patient's epilepsy, one should consider the contribution of all hyperperfused regions, as these are likely not random, but represent an electrically connected epileptic network.

A magnetoencephalography study of visual processing of pain anticipation.

Anticipating pain is important for avoiding injury; however, in chronic pain patients, anticipatory behavior can become maladaptive, leading to sensitization and limiting function. Knowledge of networks involved in pain anticipation and conditioning over time could help devise novel, better-targeted therapies. With the use of magnetoencephalography, we evaluated in 10 healthy subjects the neural processing of pain anticipation. Anticipatory cortical activity elicited by consecutive visual cues that signified imminent painful stimulus was compared with cues signifying nonpainful and no stimulus. We found that the neural processing of visually evoked pain anticipation involves the primary visual cortex along with cingulate and frontal regions. Visual cortex could quickly and independently encode and discriminate between visual cues associated with pain anticipation and no pain during preconscious phases following object presentation. When evaluating the effect of task repetition on participating cortical areas, we found that activity of prefrontal and cingulate regions was mostly prominent early on when subjects were still naive to a cue's contextual meaning. Visual cortical activity was significant throughout later phases. Although visual cortex may precisely and time efficiently decode cues anticipating pain or no pain, prefrontal areas establish the context associated with each cue. These findings have important implications toward processes involved in pain anticipation and maladaptive pain conditioning.

Hyperbolic graph embedding of MEG brain networks to study brain alterations in individuals with subjective cognitive decline.

An expansive area of research focuses on discerning patterns of alterations in functional brain networks from the early stages of Alzheimer's disease, even at the subjective cognitive decline (SCD) stage. Here, we developed a novel hyperbolic MEG brain network embedding framework for transforming high-dimensional complex MEG brain networks into lower-dimensional hyperbolic representations. Using this model, we computed hyperbolic embeddings of the MEG brain networks of two distinct participant groups: individuals with SCD and healthy controls. We demonstrated that these embeddings preserve both local and global geometric information, presenting reduced distortion compared to rival models, even when brain networks are mapped into low-dimensional spaces. In addition, our findings showed that the hyperbolic embeddings encompass unique SCD-related information that improves the discriminatory power above and beyond that of connectivity features alone. Notably, we introduced a unique metric-the radius of the node embeddings-which effectively proxies the hierarchical organization of the brain. Using this metric, we identified subtle hierarchy organizational differences between the two participant groups, suggesting increased hierarchy in the dorsal attention, frontoparietal, and ventral attention subnetworks among the SCD group. Last, we assessed the correlation between these hierarchical variations and cognitive assessment scores, revealing associations with diminished performance across multiple cognitive evaluations in the SCD group. Overall, this study presents the first evaluation of hyperbolic embeddings of MEG brain networks, offering novel insights into brain organization, cognitive decline, and potential diagnostic avenues of Alzheimer's disease.

Comparison of 2 Robotic Systems for Pediatric Stereoelectroencephalography Implantation.

BACKGROUND: Stereoelectroencephalography (SEEG) remains critical in guiding epilepsy surgery. Robot-assisted techniques have shown promise in improving SEEG implantation outcomes but have not been directly compared. In this single-institution series, we compared ROSA and Stealth AutoGuide robots in pediatric SEEG implantation. METHODS: We retrospectively reviewed 21 sequential pediatric SEEG implantations consisting of 6 ROSA and 15 AutoGuide procedures. We determined mean operative time, time per electrode, root mean square (RMS) registration error, and surgical complications. Three-dimensional radial distances were calculated between each electrode's measured entry and target points with respective errors from the planned trajectory line. RESULTS: Mean overall/per electrode operating time was 73.5/7.5 minutes for ROSA and 126.1/10.9 minutes for AutoGuide (P = 0.030 overall, P = 0.082 per electrode). Mean RMS registration error was 0.77 mm (0.55-0.93 mm) for ROSA and 0.6 mm (0.2-1.0 mm) for AutoGuide (P = 0.26). No procedures experienced complications. The mean radial (entry point error was 1.23 ± 0.11 mm for ROSA and 2.65 ± 0.12 mm for AutoGuide (P < 0.001), while the mean radial target point error was 1.86 ± 0.15 mm for ROSA and 3.25 ± 0.16 mm for AutoGuide (P < 0.001). CONCLUSIONS: Overall operative time was greater for AutoGuide procedures, although there was no statistically significant difference in time per electrode. Both systems are highly accurate with no significant RMS error difference. While the ROSA robot yielded significantly lower entry and target point errors, both robots are safe and reliable for deep electrode insertion in pediatric epilepsy.

Ripple classification helps to localize the seizure-onset zone in neocortical epilepsy.

PURPOSE: Fast ripples are reported to be highly localizing to the epileptogenic or seizure-onset zone (SOZ) but may not be readily found in neocortical epilepsy, whereas ripples are insufficiently localizing. Herein we classified interictal neocortical ripples by associated characteristics to identify a subtype that may help to localize the SOZ in neocortical epilepsy. We hypothesize that ripples associated with an interictal epileptiform discharge (IED) are more pathologic, since the IED is not a normal physiologic event. METHODS: We studied 35 patients with epilepsy with neocortical epilepsy who underwent invasive electroencephalography (EEG) evaluation by stereotactic EEG (SEEG) or subdural grid electrodes. Interictal fast ripples and ripples were visually marked during slow-wave sleep lasting 10-30 min. Neocortical ripples were classified as type I when superimposed on epileptiform discharges such as paroxysmal fast, spike, or sharp wave, and as type II when independent of epileptiform discharges. KEY FINDINGS: In 21 patients with a defined SOZ, neocortical fast ripples were detected in the SOZ of only four patients. Type I ripples were detected in 14 cases almost exclusively in the SOZ or primary propagation area (PP) and marked the SOZ with higher specificity than interictal spikes. In contrast, type II ripples were not correlated with the SOZ. In 14 patients with two or more presumed SOZs or nonlocalizable onset pattern, type I but not type II ripples also occurred in the SOZs. We found the areas with only type II ripples outside of the SOZ (type II-O ripples) in SEEG that localized to the primary motor cortex and primary visual cortex. SIGNIFICANCE: Neocortical fast ripples and type I ripples are specific markers of the SOZ, whereas type II ripples are not. Type I ripples are found more readily than fast ripples in human neocortical epilepsy. Type II-O ripples may represent spontaneous physiologic ripples in the human neocortex.

Magnetic source imaging and ictal SPECT in MRI-negative neocortical epilepsies: additional value and comparison with intracranial EEG.

PURPOSE: To investigate the utility of magnetic source imaging (MSI) and ictal single photon emission computed tomography (SPECT), each compared with intracranial electroencephalography (EEG) (ICEEG), to localize the epileptogenic zone (EZ) and predict epilepsy surgery outcome in patients with nonlesional neocortical focal epilepsy. METHODS: Studied were 14 consecutive patients with nonlesional neocortical epilepsy who underwent presurgical evaluation including ICEEG, positive MSI, and localizing subtraction Ictal SPECT coregistered to MRI (SISCOM) analysis. Follow-up after epilepsy surgery was ≥ 24 months. ICEEG, MSI, and SPECT results were classified using a sublobar classification. KEY FINDINGS: Of 14 patients, 6 (42.9%) became seizure-free after surgery. Sublobar ICEEG focus was completely resected in 11 patients; 5 (45.5%) of them became seizure- free. Concordance of ICEEG and MSI and complete focus resection was found in 5 (35.7%) patients; 80% of them became seizure-free. Sublobar ICEEG-MSI concordance and complete focus resection significantly increased the chance of seizure freedom after epilepsy surgery (p = 0.038). In contrast, of the 6 patients (42.9%) with concordant ICEEG and SISCOM and complete focus resection, only 66.7% became seizure-free (p = 0.138). Assuming concordant results, the additive value to ICEEG alone for localizing the EZ is higher with ICEEG-MSI (odds ratio 14) compared to ICEEG-SISCOM (odds ratio 6). SIGNIFICANCE: This study shows that combination of MSI and/or SISCOM with ICEEG is useful in the presurgical evaluation of patients with nonlesional neocortical epilepsy. Concordant test results of either MSI or SISCOM with ICEEG provide useful additive information for that provided by ICEEG alone to localize the EZ in this most challenging group of patients. When sublobar concordance with ICEEG is observed, MSI is more advantageous compared to SISCOM in predicting seizure-free epilepsy surgery outcome.

Sensitivity of scalp 10-20 EEG and magnetoencephalography.

Although previous studies have investigated the sensitivity of electroencephalography (EEG) and magnetoencephalography (MEG) to detect spikes by comparing simultaneous recordings, there are no published reports that focus on the relationship between spike dipole orientation or sensitivity of scalp EEG/MEG and the "gold standard" of intracranial recording (stereotactic EEG). We evaluated two patients with focal epilepsy; one with lateral temporal focus and the other with insular focus. Two MEG recordings were performed for both patients, each recorded simultaneously with initially scalp EEG, based on international 10-20 electrode placement with additional electrodes for anterior temporal regions, and subsequently stereotactic EEG. Localisation of MEG spike dipoles from both studies was concordant and all MEG spikes were detected by stereotactic EEG. For the patient with lateral temporal epilepsy, spike sensitivity of MEG and scalp EEG (relative to stereotactic EEG) was 55 and 0%, respectively. Of note, in this case, MEG spike dipoles were oriented tangentially to scalp surface in a tight cluster; the angle of the spike dipole to the vertical line was 3.6 degrees. For the patient with insular epilepsy, spike sensitivity of MEG and scalp EEG (relative to stereotactic EEG) was 83 and 44%, respectively; the angle of the spike dipole to the vertical line was 45.3 degrees. For the patient with lateral temporal epilepsy, tangential spikes from the lateral temporal cortex were difficult to detect based on scalp 10-20 EEG and for the patient with insular epilepsy, it was possible to evaluate operculum insular sources using MEG. We believe that these findings may be important for the interpretation of clinical EEG and MEG.

Magnetoencephalography reveals a unique neurophysiological profile of focal-onset epileptic spasms.

Epilepsy is defined as a disorder of the brain characterized by an enduring predisposition to experience epileptic seizures and the neurobiological, cognitive, psychological, and social difficulties relating to the condition. An epileptic spasm (ES) is a type of seizure characterized by clusters of short contractions involving axial muscles and proximal segments. However, the precise mechanism of ESs remains unknown. Despite the potential of magnetoencephalography (MEG) as a tool for investigating the neurophysiological mechanism of ESs, it has been difficult to use this methodology due to magnetic artifacts attributable to patient movement. We report on an 8-year-old girl suffering from intractable epileptic spasms from the age of 7 months. She was diagnosed with possible Aicardi syndrome [corrected] (AGS), characterized by the triad of callosal agenesis, infantile spasms, and chorioretinal lacunae. She is now intellectually delayed and suffers from intractable ES. We used both MEG and electroencephalography to investigate her epilepsy. The recording captured two series of spasm clusters. Spikes were clearly identified with MEG in about four-fifths of all spasms but were identified poorly or not at all in the remainder. MEG findings support previous studies that used intracranial electrodes to analyze patients with ESs and that showed variability in ES-associated spikes in terms of manner of cortical involvement and magnitude. Given the limitations of intracranial electrodes, such as sampling restrictions and invasiveness, MEG may be a helpful tool for non-invasively investigating the unique pathophysiological profile of focal-onset ESs.