A scalable platform for acquisition of high-fidelity human intracranial EEG with minimal clinical burden.

Human neuroscience research has been significantly advanced by neuroelectrophysiological studies from people with refractory epilepsy-the only routine clinical intervention that acquires multi-day, multi-electrode human intracranial electroencephalography (iEEG). While a sampling rate below 2 kHz is sufficient for manual iEEG review by epileptologists, computational methods and research studies may benefit from higher resolution, which requires significant technical development. At adult and pediatric Stanford hospitals, research ports of commercial clinical acquisition systems were configured to collect 10 kHz iEEG of up to 256 electrodes simultaneously with the clinical data. The research digital stream was designed to be acquired post-digitization, resulting in no loss in clinical signal quality. This novel framework implements a near-invisible research platform to facilitate the secure, routine collection of high-resolution iEEG that minimizes research hardware footprint and clinical workflow interference. The addition of a pocket-sized router in the patient room enabled an encrypted tunnel to securely transmit research-quality iEEG across hospital networks to a research computer within the hospital server room, where data was coded, de-identified, and uploaded to cloud storage. Every eligible patient undergoing iEEG clinical evaluation at both hospitals since September 2017 has been recruited; participant recruitment is ongoing. Over 350+ terabytes (representing 1000+ days) of neuroelectrophysiology were recorded across 200+ participants of diverse demographics. To our knowledge, this is the first report of such a research integration within a hospital setting. It is a promising approach to promoting equitable participant enrollment and building comprehensive data repositories with consistent, high-fidelity specifications towards new discoveries in human neuroscience.

Electroencephalogram synchronization measure as a predictive biomarker of Vagus nerve stimulation response in refractory epilepsy: A retrospective study.

There are currently no established biomarkers for predicting the therapeutic effectiveness of Vagus Nerve Stimulation (VNS). Given that neural desynchronization is a pivotal mechanism underlying VNS action, EEG synchronization measures could potentially serve as predictive biomarkers of VNS response. Notably, an increased brain synchronization in delta band has been observed during sleep-potentially due to an activation of thalamocortical circuitry, and interictal epileptiform discharges are more frequently observed during sleep. Therefore, investigation of EEG synchronization metrics during sleep could provide a valuable insight into the excitatory-inhibitory balance in a pro-epileptogenic state, that could be pathological in patients exhibiting a poor response to VNS. A 19-channel-standard EEG system was used to collect data from 38 individuals with Drug-Resistant Epilepsy (DRE) who were candidates for VNS implantation. An EEG synchronization metric-the Weighted Phase Lag Index (wPLI)-was extracted before VNS implantation and compared between sleep and wakefulness, and between responders (R) and non-responders (NR). In the delta band, a higher wPLI was found during wakefulness compared to sleep in NR only. However, in this band, no synchronization difference in any state was found between R and NR. During sleep and within the alpha band, a negative correlation was found between wPLI and the percentage of seizure reduction after VNS implantation. Overall, our results suggest that patients exhibiting a poor VNS efficacy may present a more pathological thalamocortical circuitry before VNS implantation. EEG synchronization measures could provide interesting insights into the prerequisites for responding to VNS, in order to avoid unnecessary implantations in patients showing a poor therapeutic efficacy.

Feasibility, Safety, and Performance of Full-Head Subscalp EEG Using Minimally Invasive Electrode Implantation.

BACKGROUND AND OBJECTIVES: Current practice in clinical neurophysiology is limited to short recordings with conventional EEG (days) that fail to capture a range of brain (dys)functions at longer timescales (months). The future ability to optimally manage chronic brain disorders, such as epilepsy, hinges upon finding methods to monitor electrical brain activity in daily life. We developed a device for full-head subscalp EEG (Epios) and tested here the feasibility to safely insert the electrode leads beneath the scalp by a minimally invasive technique (primary outcome). As secondary outcome, we verified the noninferiority of subscalp EEG in measuring physiologic brain oscillations and pathologic discharges compared with scalp EEG, the established standard of care. METHODS: Eight participants with pharmacoresistant epilepsy undergoing intracranial EEG received in the same surgery subscalp electrodes tunneled between the scalp and the skull with custom-made tools. Postoperative safety was monitored on an inpatient ward for up to 9 days. Sleep-wake, ictal, and interictal EEG signals from subscalp, scalp, and intracranial electrodes were compared quantitatively using windowed multitaper transforms and spectral coherence. Noninferiority was tested for pairs of neighboring subscalp and scalp electrodes with a Bland-Altman analysis for measurement bias and calculation of the interclass correlation coefficient (ICC). RESULTS: As primary outcome, up to 28 subscalp electrodes could be safely placed over the entire head through 1-cm scalp incisions in a ∼1-hour procedure. Five of 10 observed perioperative adverse events were linked to the investigational procedure, but none were serious, and all resolved. As a secondary outcome, subscalp electrodes advantageously recorded EEG percutaneously without requiring any maintenance and were noninferior to scalp electrodes for measuring (1) variably strong, stage-specific brain oscillations (alpha in wake, delta, sigma, and beta in sleep) and (2) interictal spikes peak-potentials and ictal signals coherent with seizure propagation in different brain regions (ICC >0.8 and absence of bias). DISCUSSION: Recording full-head subscalp EEG for localization and monitoring purposes is feasible up to 9 days in humans using minimally invasive techniques and noninferior to the current standard of care. A longer prospective ambulatory study of the full system will be necessary to establish the safety and utility of this innovative approach. TRIAL REGISTRATION INFORMATION: clinicaltrials.gov/study/NCT04796597.

Intracortical mechanisms of single pulse electrical stimulation (SPES) evoked excitations and inhibitions in humans.

Cortico-cortical evoked potentials (CCEPs) elicited by single-pulse electric stimulation (SPES) are widely used to assess effective connectivity between cortical areas and are also implemented in the presurgical evaluation of epileptic patients. Nevertheless, the cortical generators underlying the various components of CCEPs in humans have not yet been elucidated. Our aim was to describe the laminar pattern arising under SPES evoked CCEP components (P1, N1, P2, N2, P3) and to evaluate the similarities between N2 and the downstate of sleep slow waves. We used intra-cortical laminar microelectrodes (LMEs) to record CCEPs evoked by 10 mA bipolar 0.5 Hz electric pulses in seven patients with medically intractable epilepsy implanted with subdural grids. Based on the laminar profile of CCEPs, the latency of components is not layer-dependent, however their rate of appearance varies across cortical depth and stimulation distance, while the seizure onset zone does not seem to affect the emergence of components. Early neural excitation primarily engages middle and deep layers, propagating to the superficial layers, followed by mainly superficial inhibition, concluding in a sleep slow wave-like inhibition and excitation sequence.

Identifying epileptogenic abnormality by decomposing intracranial EEG and MEG power spectra.

BACKGROUND: Accurate identification of abnormal electroencephalographic (EEG) activity is pivotal for diagnosing and treating epilepsy. Recent studies indicate that decomposing brain activity into periodic (oscillatory) and aperiodic (trend across all frequencies) components can illuminate the drivers of spectral activity changes. NEW METHODS: We analysed intracranial EEG (iEEG) data from 234 subjects, creating a normative map. This map was compared to a cohort of 63 patients with refractory focal epilepsy under consideration for neurosurgery. The normative map was computed using three approaches: (i) relative complete band power, (ii) relative band power with the aperiodic component removed, and (iii) the aperiodic exponent. Abnormalities were calculated for each approach in the patient cohort. We evaluated the spatial profiles, assessed their ability to localize abnormalities, and replicated the findings using magnetoencephalography (MEG). RESULTS: Normative maps of relative complete band power and relative periodic band power exhibited similar spatial profiles, while the aperiodic normative map revealed higher exponent values in the temporal lobe. Abnormalities estimated through complete band power effectively distinguished between good and bad outcome patients. Combining periodic and aperiodic abnormalities enhanced performance, like the complete band power approach. COMPARISON WITH EXISTING METHODS AND CONCLUSIONS: Sparing cerebral tissue with abnormalities in both periodic and aperiodic activity may result in poor surgical outcomes. Both periodic and aperiodic components do not carry sufficient information in isolation. The relative complete band power solution proved to be the most reliable method for this purpose. Future studies could investigate how cerebral location or pathology influences periodic or aperiodic abnormalities.

Quantitative EEG analysis of brivaracetam in drug-resistant epilepsy: A pharmaco-EEG study.

OBJECTIVE: Brivaracetam (BRV) is a recent antiseizure medication (ASM) approved as an add-on therapy for people with focal epilepsy. BRV has a good efficacy and safety profile compared to other ASMs. However, its specific effects on resting-state EEG activity and connectivity are unknown. The aim of this study is to evaluate quantitative EEG changes induced by BRV therapy in a population of adult people with drug-resistant epilepsy (PwE) compared to healthy controls (HC). METHODS: We performed a longitudinal, retrospective, pharmaco-EEG study on a population of 23 PwE and a group of 25 HC. Clinical outcome was dichotomized into drug-responders (i.e., >50% reduction in seizures' frequency; RES) and non-responders (N-RES) after two years of BRV. EEG parameters were compared between PwE and HC at baseline (pre-BRV) and after three months of BRV therapy (post-BRV). We investigated BRV-related variations in EEG connectivity using the phase locking value (PLV). RESULTS: BRV therapy did not induce modifications in power spectrum density across different frequency bands. PwE presented lower PLV connectivity values compared to HC in all frequency bands. RES exhibited lower theta PLV connectivity compared to HC before initiating BRV and experienced an increase after BRV, eliminating the significant difference from HC. CONCLUSIONS: This study shows that BRV does not alter the EEG power spectrum in PwE, supporting its favourable neuropsychiatric side-effect profile, and induces the disappearance of EEG connectivity differences between PwE and HC. SIGNIFICANCE: The integration of EEG quantitative analysis in epilepsy can provide insights into the efficacy, mechanism of action, and side effects of ASMs.

Verbal memory network mapping in individual patients predicts postoperative functional impairments.

Verbal memory decline is a significant concern following temporal lobe surgeries in patients with epilepsy, emphasizing the need for precision presurgical verbal memory mapping to optimize functional outcomes. However, the inter-individual variability in functional networks and brain function-structural dissociations pose challenges when relying solely on group-level atlases or anatomical landmarks for surgical guidance. Here, we aimed to develop and validate a personalized functional mapping technique for verbal memory using precision resting-state functional MRI (rs-fMRI) and neurosurgery. A total of 38 patients with refractory epilepsy scheduled for surgical interventions were enrolled and 28 patients were analyzed in the study. Baseline 30-min rs-fMRI scanning, verbal memory and language assessments were collected for each patient before surgery. Personalized verbal memory networks (PVMN) were delineated based on preoperative rs-fMRI data for each patient. The accuracy of PVMN was assessed by comparing post-operative functional impairments and the overlapping extent between PVMN and surgical lesions. A total of 14 out of 28 patients experienced clinically meaningful declines in verbal memory after surgery. The personalized network and the group-level atlas exhibited 100% and 75.0% accuracy in predicting postoperative verbal memory declines, respectively. Moreover, six patients with extra-temporal lesions that overlapped with PVMN showed selective impairments in verbal memory. Furthermore, the lesioned ratio of the personalized network rather than the group-level atlas was significantly correlated with postoperative declines in verbal memory (personalized networks: r = -0.39, p = .038; group-level atlas: r = -0.19, p = .332). In conclusion, our personalized functional mapping technique, using precision rs-fMRI, offers valuable insights into individual variability in the verbal memory network and holds promise in precision verbal memory network mapping in individuals.

EEG Ictal Power Dynamics, Function-Structure Associations, and Epilepsy Surgical Outcomes.

BACKGROUND AND OBJECTIVES: Postoperative seizure control in drug-resistant temporal lobe epilepsy (TLE) remains variable, and the causes for this variability are not well understood. One contributing factor could be the extensive spread of synchronized ictal activity across networks. Our study used novel quantifiable assessments from intracranial EEG (iEEG) to test this hypothesis and investigated how the spread of seizures is determined by underlying structural network topological properties. METHODS: We evaluated iEEG data from 157 seizures in 27 patients with TLE: 100 seizures from 17 patients with postoperative seizure control (Engel score I) vs 57 seizures from 10 patients with unfavorable surgical outcomes (Engel score II-IV). We introduced a quantifiable method to measure seizure power dynamics within anatomical regions, refining existing seizure imaging frameworks and minimizing reliance on subjective human decision-making. Time-frequency power representations were obtained in 6 frequency bands ranging from theta to gamma. Ictal power spectrums were normalized against a baseline clip taken at least 6 hours away from ictal events. Electrodes' time-frequency power spectrums were then mapped onto individual T1-weighted MRIs and grouped based on a standard brain atlas. We compared spatiotemporal dynamics for seizures between groups with favorable and unfavorable surgical outcomes. This comparison included examining the range of activated brain regions and the spreading rate of ictal activities. We then evaluated whether regional iEEG power values were a function of fractional anisotropy (FA) from diffusion tensor imaging across regions over time. RESULTS: Seizures from patients with unfavorable outcomes exhibited significantly higher maximum activation sizes in various frequency bands. Notably, we provided quantifiable evidence that in seizures associated with unfavorable surgical outcomes, the spread of beta-band power across brain regions is significantly faster, detectable as early as the first second after seizure onset. There was a significant correlation between beta power during seizures and FA in the corresponding areas, particularly in the unfavorable outcome group. Our findings further suggest that integrating structural and functional features could improve the prediction of epilepsy surgical outcomes. DISCUSSION: Our findings suggest that ictal iEEG power dynamics and the structural-functional relationship are mechanistic factors associated with surgical outcomes in TLE.

Ictal kissing: Review of literature and report of 5 cases.

Ictal kissing (IK) is a rare type of automatism observed during epileptic seizures. Despite its uncommon occurrence, understanding the underlying mechanisms, the role of emotions, and the level of consciousness during seizures with IK is essential in providing a comprehensive understanding of epilepsy. We describe five cases (.13%) of IK after performing a retrospective analysis of 3794 long-term, ictal video-EEGs from an epilepsy monitoring unit in Mumbai, India. Our patients with drug-resistant epilepsy showed IK had a wide epileptogenic zone. We discuss the current hypotheses on the mechanisms behind IK, the involvement of temporal lobe structures, and the implications of awareness during seizures. The review concludes by suggesting future directions for research to elucidate the complex phenomenon of IK further.

New stimulation procedures for language mapping in stereo-EEG.

OBJECTIVE: Cortical intracerebral electrical stimulation is an important tool for language mapping in the presurgical work-up of patients with drug-resistant focal epilepsy. Language mapping with stereo-electroencephalography (EEG) is usually performed by high-frequency stimulations (HFS: 50 Hz), whereas low-frequency stimulations (LFS: 1 Hz) are usually considered useful for primary cortices mapping. Little is known in literature about "intermediate" frequencies (IFS: 6-15 Hz). Our objective is to explore the clinical usefulness of IFS in language mapping and identify factors, beyond the electrical parameters, that impact the mapping. METHODS: We studied 23 patients submitted to stereo-EEG for presurgical evaluation. Language mapping was performed in the anterior, posterior and/or basal language region of the dominant hemisphere for language. We included all contact positions within these regions stimulated by HFS (50 Hz, 5 s, 1-3 mA) and IFS (6-15 Hz, 15 s, 5 mA). We compared the capability of both stimulation methods to induce a language deficit without afterdischarges (ADs), and we analyzed factors related to clinical examination, region, and stimulation technique by multivariate analysis. RESULTS: A total of 211 stimulations (98 HFS, 113 IFS) in 70 cortical sites within the anterior (84 stimulations), posterior (137), and basal language region (60) were included. IFS induced more frequently language deficits not associated to AD compared to HFS (37.1% vs 25.7%, p = .0043), whereas HFS provoked more diffuse AD (34.7% vs 15.0%, p = .001). Investigating multiple language functions increased the probability of revealing a deficit (odds ratio [OR] 3.16, p = .0016), independently of the stimulation method. SIGNIFICANCE: IFS are valuable for language mapping, thereby improving the probability of inducing a clinical deficit not accompanied by an AD. The completeness of the clinical examination independently affects the sensitivity of the mapping. IFS are a new tool with potential usefulness for the cortical mapping of other associative cortical regions.

Thalamic stereoelectroencephalography for neuromodulation target selection: Proof of concept and review of literature of pulvinar direct electrical stimulation.

In patients with drug-resistant epilepsy (DRE) who are not candidates for resective surgery, various thalamic nuclei, including the anterior, centromedian, and pulvinar nuclei, have been extensively investigated as targets for neuromodulation. However, the therapeutic effects of different targets for thalamic neuromodulation on various types of epilepsy are not well understood. Here, we present a 32-year-old patient with multifocal bilateral temporoparieto-occipital epilepsy and bilateral malformations of cortical development (MCDs) who underwent bilateral stereoelectroencephalographic (SEEG) recordings of the aforementioned three thalamic nuclei bilaterally. The change in the rate of interictal epileptiform discharges (IEDs) from baseline were compared in temporal, central, parietal, and occipital regions after direct electrical stimulation (DES) of each thalamic nucleus. A significant decrease in the rate of IEDs (33% from baseline) in the posterior quadrant regions was noted in the ipsilateral as well as contralateral hemisphere following DES of the pulvinar. A scoping review was also performed to better understand the current standpoint of pulvinar thalamic stimulation in the treatment of DRE. The therapeutic effect of neuromodulation can differ among thalamic nuclei targets and epileptogenic zones (EZs). In patients with multifocal EZs with extensive MCDs, personalized thalamic targeting could be achieved through DES with thalamic SEEG electrodes.

An automated algorithm for stereoelectroencephalography electrode localization and labelling.

PURPOSE: Stereoelectroencephalography (sEEG) is increasingly utilized for localization of seizure foci, functional mapping, and neurocognitive research due to its ability to target deep and difficult to reach anatomical locations and to study in vivo brain function with a high signal-to-noise ratio. The research potential of sEEG is constrained by the need for accurate localization of the implanted electrodes in a common template space for group analyses. METHODS: We present an algorithm to automate the grouping of sEEG electrodes by trajectories, labelled by target and insertion point. This algorithm forms the core of a pipeline that fully automates the entire process of electrode localization in standard space, using raw CT and MRI images to produce atlas labelled MNI coordinates. RESULTS: Across 196 trajectories from 20 patients, the pipeline successfully processed 190 trajectories with localizations within 0.25±0.55 mm of the manual annotation by two reviewers. Six electrode trajectories were not directly identified due to metal artifacts and locations were interpolated based on the first and last contact location and the number of contacts in that electrode as listed in the surgical record. CONCLUSION: We introduce our algorithm and pipeline for automatically localizing, grouping, and classifying sEEG electrodes from raw CT and MRI. Our algorithm adds to existing pipelines and toolboxes for electrode localization by automating the manual step of marking and grouping electrodes, thereby expedites the analyses of sEEG data, particularly in large datasets.

Responsive neurostimulation as a therapy for epilepsy following new-onset refractory status epilepticus: Case series and review of the literature.

OBJECTIVE: To report clinical outcomes of patients who presented with new-onset refractory status epilepticus (NORSE), developed drug-resistant epilepsy (DRE), and were treated with responsive neurostimulation (RNS). METHODS: We performed a retrospective review of patients implanted with RNS at our institution and identified three who originally presented with NORSE. Through chart review, we retrieved objective and subjective information related to their presentation, workup, and outcomes including patient-reported seizure frequency. We reviewed electrocorticography (ECoG) data to estimate seizure burden at 3, 6, 12, and 24 months following RNS implantation. We performed a review of literature concerning neurostimulation in NORSE. RESULTS: Use of RNS to treat DRE following NORSE was associated with reduced seizure burden and informed care by differentiating epileptic from non-epileptic events. CONCLUSIONS: Our single-center experience of three cases suggests that RNS is a safe and potentially effective treatment for DRE following NORSE. SIGNIFICANCE: This article reports outcomes of the largest case series of NORSE patients treated with RNS. Since patients with NORSE are at high risk of adverse neuropsychiatric and cognitive sequelae beyond seizures, a unique strength of RNS over other surgical options is the ability to distinguish ictal or peri-ictal from non-epileptic events.

ATP1A2-related epileptic encephalopathy and movement disorder: Clinical features of three novel patients.

OBJECTIVE: Variants in the ATP1A2 gene exhibit a wide clinical spectrum, ranging from familial hemiplegic migraine to childhood epilepsies and early infantile developmental epileptic encephalopathy (EIDEE) with movement disorders. This study aims to describe the epileptology of three unpublished cases and summarize epilepsy features of the other 17 published cases with ATP1A2 variants and EIDEE. METHODS: Medical records of three novel patients with pathogenic ATP1A2 variants were retrospectively reviewed. Additionally, the PUBMED, EMBASE, and Cochrane databases were searched until December 2023 for articles on EIDEE with ATP1A2 variants, without language or publication year restrictions. RESULTS: Three female patients, aged 6 months-10 years, were investigated. Epilepsy onset occurred between 5 days and 2 years, accompanied by severe developmental delay, intellectual disability, drug-resistant epilepsy, severe movement disorder, and recurrent status epilepticus. All individuals had pathogenic variants of the ATP1A2 gene (ATP1A2 c.720_721del (p.Ile240MetfsTer9), ATP1A2c.3022C > T (p.Arg1008Trp), ATP1A2 c.1096G > T (p.Gly366Cys), according to ACMG criteria. Memantine was p) rescribed to three patients, one with a reduction in ictal frequency, one with improvement in gait pattern, coordination, and attention span, and another one in alertness without significant side effects. SIGNIFICANCE: This study reinforces the association between ATP1A2 variants and a severe phenotype. All patients had de novo variants, focal motor seizures with impaired awareness as the primary type of seizure; of the 11 EEGs recorded, 10 presented a slow background rhythm, 7 multifocal interictal epileptiform discharges (IED), predominantly temporal IEDs, followed by frontal IED, as well as ten ictal recordings, which showed ictal onset from the same regions mentioned above. Treatment with antiseizure medication was generally ineffective, but memantine showed moderate improvement. Prospective studies are needed to enlarge the phenotype and assess the efficacy of NMDA receptor antagonist therapies in reducing seizure frequency and improving quality of life.

Modification of brain conductivity in human focal epilepsy: A model-based estimation from stereoelectroencephalography.

OBJECTIVE: We have developed a novel method for estimating brain tissue electrical conductivity using low-intensity pulse stereoelectroencephalography (SEEG) stimulation coupled with biophysical modeling. We evaluated the hypothesis that brain conductivity is correlated with the degree of epileptogenicity in patients with drug-resistant focal epilepsy. METHODS: We used bipolar low-intensity biphasic pulse stimulation (.2 mA) followed by a postprocessing pipeline for estimating brain conductivity. This processing is based on biophysical modeling of the electrical potential induced in brain tissue between the stimulated contacts in response to pulse stimulation. We estimated the degree of epileptogenicity using a semi-automatic method quantifying the dynamic of fast discharge at seizure onset: the epileptogenicity index (EI). We also investigated how the location of stimulation within specific anatomical brain regions or within lesional tissue impacts brain conductivity. RESULTS: We performed 1034 stimulations of 511 bipolar channels in 16 patients. We found that brain conductivity was lower in the epileptogenic zone (EZ; unpaired median difference = .064, p < .001) and inversely correlated with the epileptogenic index value (p < .001, Spearman rho = -.32). Conductivity values were also influenced by anatomical site, location within lesion, and delay between SEEG electrode implantation and stimulation, and had significant interpatient variability. Mixed model multivariate analysis showed that conductivity is significantly associated with EI (F = 13.45, p < .001), anatomical regions (F = 5.586, p < .001), delay since implantation (F = 14.71, p = .003), and age at SEEG (F = 6.591, p = .027), but not with the type of lesion (F = .372, p = .773) or the delay since last seizure (F = 1.592, p = .235). SIGNIFICANCE: We provide a novel model-based method for estimating brain conductivity from SEEG low-intensity pulse stimulations. The brain tissue conductivity is lower in EZ as compared to non-EZ. Conductivity also varies significantly across anatomical brain regions. Involved pathophysiological processes may include changes in the extracellular space (especially volume or tortuosity) in epileptic tissue.

Measurable transitions during seizures in intracranial EEG: A stereoelectroencephalography and SPECT study.

OBJECTIVE: Ictal Single Photon Emission Computed Tomography (SPECT) and stereo-electroencephalography (SEEG) are diagnostic techniques used for the management of patients with drug-resistant focal epilepsies. While hyperperfusion patterns in ictal SPECT studies reveal seizure onset and propagation pathways, the role of ictal hypoperfusion remains poorly understood. The goal of this study was to systematically characterize the spatio-temporal information flow dynamics between differently perfused brain regions using stereo-EEG recordings. METHODS: We identified seizure-free patients after resective epilepsy surgery who had prior ictal SPECT and SEEG investigations. We estimated directional connectivity between the epileptogenic-zone (EZ), non-resected areas of hyperperfusion, hypoperfusion, and baseline perfusion during the interictal, preictal, ictal, and postictal periods. RESULTS: Compared to the background, we noted significant information flow (1) during the preictal period from the EZ to the baseline and hyperperfused regions, (2) during the ictal onset from the EZ to all three regions, and (3) during the period of seizure evolution from the area of hypoperfusion to all three regions. CONCLUSIONS: Hypoperfused brain regions were found to indirectly interact with the EZ during the ictal period. SIGNIFICANCE: Our unique study, combining intracranial electrophysiology and perfusion imaging, presents compelling evidence of dynamic changes in directional connectivity between brain regions during the transition from interictal to ictal states.

Distributed source modeling of stereoencephalographic measurements of ictal activity.

OBJECTIVES: Stereoelectroencephalography (SEEG) can define the epileptogenic zone (EZ). However, SEEG is susceptible to the sampling bias, where no SEEG recording is taken within a circumscribed EZ. METHODS: Nine patients with medically refractory epilepsy underwent SEEG recording, and brain resection got positive outcomes. Ictal neuronal currents were estimated by distributed source modeling using the SEEG data and individual's anatomical magnetic resonance imaging. Using a retrospective leave-one-out data sub-sampling, we evaluated the sensitivity and specificity of the current estimates using MRI after surgical resection or radio-frequency ablation. RESULTS: The sensitivity and specificity in detecting the EZ were indistinguishable from either the data from all electrodes or the sub-sampled data (rank sum test: rank sum = 23719, p = 0.13) when at least one remaining electrode contact was no more than 20 mm away. CONCLUSIONS: The distributed neuronal current estimates of ictal SEEG data can mitigate the challenge of delineating the boundary of the EZ in cases of missing an electrode implanted within the EZ and a required second SEEG exploration. SIGNIFICANCE: Distributed source modeling can be a tool for clinicians to infer the EZ by allowing for more flexible planning of the electrode implantation route and minimizing the number of electrodes.

Drug-resistant generalized epilepsies: Revisiting the frontiers of idiopathic generalized epilepsies.

The 2017 International League Against Epilepsy (ILAE) classification suggested that the term "genetic generalized epilepsies" (GGEs) should be used for the broad group of epilepsies with so-called "generalized" seizure types and "generalized" spike-wave activity on EEG, based on a presumed genetic etiology. Within this framework, idiopathic generalized epilepsies (IGEs) are described as a subset of GGEs and include only four epileptic syndromes: childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy, and epilepsy with generalized tonic-clonic seizures alone. The recent 2022 ILAE definition of IGEs is based on the current state of knowledge and reflects a community consensus and is designed to evolve as knowledge advances. The term "frontiers of IGEs" refers to the actual limits of our understanding of these four syndromes. Indeed, among patients presenting with a syndrome compatible with the 2022 definition of IGEs, we still observe a significant proportion of patients presenting with specific clinical features, refractory seizures, or drug-resistant epilepsies. This leads to the discussion of the boundaries of IGEs and GGEs, or what is accepted within a clinical spectrum of a definite IGE. Here, we discuss several entities that have been described in the literature for many years and that may either constitute rare features of IGEs or a distinct differential diagnosis. Their recognition by clinicians may allow a more individualized approach and improve the management of patients presenting with such entities.

Multiscale neuro-inspired models for interpretation of EEG signals in patients with epilepsy.

OBJECTIVE: The aim is to gain insight into the pathophysiological mechanisms underlying interictal epileptiform discharges observed in electroencephalographic (EEG) and stereo-EEG (SEEG, depth electrodes) recordings performed during pre-surgical evaluation of patients with drug-resistant epilepsy. METHODS: We developed novel neuro-inspired computational models of the human cerebral cortex at three different levels of description: i) microscale (detailed neuron models), ii) mesoscale (neuronal mass models) and iii) macroscale (whole brain models). Although conceptually different, micro- and mesoscale models share some similar features, such as the typology of neurons (pyramidal cells and three types of interneurons), their spatial arrangement in cortical layers, and their synaptic connectivity (excitatory and inhibitory). The whole brain model consists of a large-scale network of interconnected neuronal masses, with connectivity based on the human connectome. RESULTS: For these three levels of description, the fine-tuning of free parameters and the quantitative comparison with real data allowed us to reproduce interictal epileptiform discharges with a high degree of fidelity and to formulate hypotheses about the cell- and network-related mechanisms underlying the generation of fast ripples and SEEG-recorded epileptic spikes and spike-waves. CONCLUSIONS: The proposed models provide valuable insights into the pathophysiological mechanisms underlying the generation of epileptic events. The knowledge gained from these models effectively complements the clinical analysis of SEEG data collected during the evaluation of patients with epilepsy. SIGNIFICANCE: These models are likely to play a key role in the mechanistic interpretation of epileptiform activity.