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.

Photonic convolution accelerator based on a hybrid integrated multi-wavelength laser array by photonic wire bonding for real-time image classification.

We propose and experimentally demonstrate a compact and efficient photonic convolution accelerator based on a hybrid integrated multi-wavelength DFB laser array by photonic wire bonding. The photonic convolution accelerator operates at 60.12 GOPS for one 3 × 3 kernel with a convolution window vertical sliding stride of 1 and generates 500 images of real-time image classification. Furthermore, real-time image classification on the MNIST database of handwritten digits with a prediction accuracy of 93.86% is achieved. This work provides a novel, to the best of our knowledge, compact hybrid integration platform to realize the optical convolutional neural networks.

Optimizing peripheral blood chromosome analysis: effects of refrigeration time and blood volume.

OBJECTIVE: This study aims to investigate the impact of refrigeration time and blood volume on the success rate of peripheral blood chromosomal analysis using response surface methodology (RSM). METHODS: Peripheral blood samples from 30 volunteers were subjected to chromosomal analysis under different refrigeration duration periods (≤7 days, 8 days, 9 days, 10 days, 11 days, 12 days, 13 days, 14 days) along with different blood volumes (0.2 mL, 0.3 mL, 0.4 mL, 0.5 mL, 0.6 mL, 0.7 mL, and 0.8 mL). The effects of refrigeration time and blood volume on the success rate of peripheral blood chromosomal analysis were determined using the Chi-square test for trend, followed with Spearman's rank correlation coefficient, and RSM analysis to identify the optimal combination of refrigeration time and blood volume. RESULTS: The refrigeration time within 10 days had a minor impact on the success rate, while refrigeration time more than 11 days significantly decreased the success rate. An increase in blood volume slightly improved the success rate. The success rate showed both linear and nonlinear changes with refrigeration time, while the effect of blood volume was primarily linear. The highest success rate was observed at a refrigeration time of ≤7 days and a blood volume of 0.8 mL. The interaction between refrigeration time and blood volume had a significant impact on the success rate. CONCLUSION: It is recommended to keep the refrigeration time of blood samples within 7 days and control the blood volume at 0.8 mL to maximize the success rate of chromosomal analysis.

Oxidation Behavior of Pre-Strained Polycrystalline Ni3Al-Based Superalloy.

The harsh service environment of aeroengine hot-end components requires superalloys possessing excellent antioxidant properties. This study investigated the effect of pre-strain on the oxidation behavior of polycrystalline Ni3Al-based superalloys. The growth behaviors of oxidation products were analyzed by scanning electron microscope, transmission electron microscope, X-ray Photoelectron Spectroscopy and Raman spectroscopy. The results indicated that the 5% pre-strained alloys exhibited lower mass gain, shallower oxidation depth and more compact oxide film structures compared to the original alloy. This is mainly attributed to the formation of rapid diffusion paths for Al atoms diffusing to the surface under 5% pre-strain, which promotes the faster formation of protective Al2O3 film while continuing to increase the pre-strain to 25% results in less protective transient oxidation behavior being aggravated due to the increase in dislocation density within the alloy, which prevents the timely formation of the protective Al2O3 film, resulting in uneven oxidation behavior on the alloy.

Poly (Vinylidene Fluoride-Hexafluoropropylene)-Lithium Titanium Aluminum Phosphate-Based Gel Polymer Electrolytes Synthesized by Immersion Precipitation for High-Performance Lithium Metal Batteries.

Gel polymer electrolytes (GPEs) have high safety and excellent electrochemical performance, so applying GPEs in lithium batteries has received much attention. However, their poor lithium ion transfer number, cycling stability, and low room temperature ionic conductivity seriously affect the utilization of gel polymer electrolytes. This paper successfully synthesized flexible poly (vinylidene fluoride-hexafluoropropylene)-lithium titanium aluminum phosphate (PVDF-HFP-LATP) gel polymer electrolytes using the immersion precipitation method. The resulting GPE has a porous honeycomb structure, which ensures that the GPE has sufficient space to store the liquid electrolyte. The GPE has a high ionic conductivity of 1.03 ×10-3 S cm-1 at room temperature (25 °C). The GPE was applied to LiFePO4/GPE/Li batteries with good rate performance at room temperature. The discharge specific capacity of 1C was as high as 121.5 mAh/g, and the capacity retention rate was 94.0% after 300 cycles. These results indicate that PVDF-HFP-LATP-based GPEs have the advantage of simplifying the production process and can improve the utility of gel polymer lithium metal batteries.

Synthesis and Properties of Polyvinylidene Fluoride-Hexafluoropropylene Copolymer/Li6PS5Cl Gel Composite Electrolyte for Lithium Solid-State Batteries.

Gel electrolytes for lithium-ion batteries continue to replace the organic liquid electrolytes in conventional batteries due to their advantages of being less prone to leakage and non-explosive and possessing a high modulus of elasticity. However, the development of gel electrolytes has been hindered by their generally low ionic conductivity at room temperature and high interfacial impedance with electrodes. In this paper, a poly (vinylidene fluoride)-hexafluoropropylene copolymer (PVdF-HFP) with a flexible structure, Li6PS5Cl (LPSCl) powder of the sulfur-silver-germanium ore type, and lithium perchlorate salt (LiClO4) were prepared into sulfide gel composite electrolyte films (GCEs) via a thermosetting process. The experimental results showed that the gel composite electrolyte with 1% LPSCl in the PVdF-HFP matrix exhibited an ionic conductivity as high as 1.27 × 10-3 S·cm-1 at 25 °C and a lithium ion transference number of 0.63. The assembled LiFePO4||GCEs||Li batteries have excellent rate (130 mAh·g-1 at 1 C and 54 mAh·g-1 at 5 C) and cycling (capacity retention was 93% after 100 cycles at 0.1 C and 80% after 150 cycles at 0.2 C) performance. This work provides new methods and strategies for the design and fabrication of solid-state batteries with high ionic conductivity and high specific energy.

Preparation and Properties of Gel Polymer Electrolytes with Li1.5Al0.5Ge1.5(PO4)3 and Li6.46La3Zr1.46Ta0.54O12 by UV Curing Process.

Poly (vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP)-based gel polymer electrolytes (GPEs) are considered a promising electrolyte candidate for polymer lithium-ion batteries (LIBs) because of their free-standing shape, versatility, security, flexibility, lightweight, reliability, and so on. However, due to problems such as low ionic conductivity, PVDF-HFP can only be used on a small scale when used as a substrate alone. To overcome the above shortcomings, GPEs were designed and synthesized by a UV curing process by adding NASICON-type Li1.5Al0.5Ge1.5(PO4)3 (LAGP) and garnet-type Li6.46La3Zr1.46Ta0.54O12 (LLZTO) to PVDF-HFP. Experimentally, GPEs with 10% weight LLZTO in a PVDF-HFP matrix had an ionic conductivity of up to 3 × 10-4 S cm-1 at 25 °C. When assembled into LiFePO4/GPEs/Li batteries, a discharge-specific capacity of 81.5 mAh g-1 at a current density of 1 C and a capacity retention rate of 98.1% after 100 cycles at a current density of 0.2 C occurred. Therefore, GPEs added to LLZTO have a broad application prospect regarding rechargeable lithium-ion batteries.

Data encoding for healthcare data democratization and information leakage prevention.

The lack of data democratization and information leakage from trained models hinder the development and acceptance of robust deep learning-based healthcare solutions. This paper argues that irreversible data encoding can provide an effective solution to achieve data democratization without violating the privacy constraints imposed on healthcare data and clinical models. An ideal encoding framework transforms the data into a new space where it is imperceptible to a manual or computational inspection. However, encoded data should preserve the semantics of the original data such that deep learning models can be trained effectively. This paper hypothesizes the characteristics of the desired encoding framework and then exploits random projections and random quantum encoding to realize this framework for dense and longitudinal or time-series data. Experimental evaluation highlights that models trained on encoded time-series data effectively uphold the information bottleneck principle and hence, exhibit lesser information leakage from trained models.

Epileptogenic networks in extra temporal lobe epilepsy.

Extra temporal lobe epilepsy (eTLE) may involve heterogenous widespread cerebral networks. We investigated the structural network of an eTLE cohort, at the postulated epileptogenic zone later surgically removed, as a network node: the resection zone (RZ). We hypothesized patients with an abnormal connection to/from the RZ to have proportionally increased abnormalities based on topological proximity to the RZ, in addition to poorer post-operative seizure outcome. Structural and diffusion MRI were collected for 22 eTLE patients pre- and post-surgery, and for 29 healthy controls. The structural connectivity of the RZ prior to surgery, measured via generalized fractional anisotropy (gFA), was compared with healthy controls. Abnormal connections were identified as those with substantially reduced gFA (z < -1.96). For patients with one or more abnormal connections to/from the RZ, connections with closer topological distance to the RZ had higher proportion of abnormalities. The minority of the seizure-free patients (3/11) had one or more abnormal connections, while most non-seizure-free patients (8/11) had abnormal connections to the RZ. Our data suggest that eTLE patients with one or more abnormal structural connections to/from the RZ had more proportional abnormal connections based on topological distance to the RZ and associated with reduced chance of seizure freedom post-surgery.

Interictal magnetoencephalography abnormalities to guide intracranial electrode implantation and predict surgical outcome.

Intracranial EEG is the gold standard technique for epileptogenic zone localization but requires a preconceived hypothesis of the location of the epileptogenic tissue. This placement is guided by qualitative interpretations of seizure semiology, MRI, EEG and other imaging modalities, such as magnetoencephalography. Quantitative abnormality mapping using magnetoencephalography has recently been shown to have potential clinical value. We hypothesized that if quantifiable magnetoencephalography abnormalities were sampled by intracranial EEG, then patients' post-resection seizure outcome may be better. Thirty-two individuals with refractory neocortical epilepsy underwent magnetoencephalography and subsequent intracranial EEG recordings as part of presurgical evaluation. Eyes-closed resting-state interictal magnetoencephalography band power abnormality maps were derived from 70 healthy controls as a normative baseline. Magnetoencephalography abnormality maps were compared to intracranial EEG electrode implantation, with the spatial overlap of intracranial EEG electrode placement and cerebral magnetoencephalography abnormalities recorded. Finally, we assessed if the implantation of electrodes in abnormal tissue and subsequent resection of the strongest abnormalities determined by magnetoencephalography and intracranial EEG corresponded to surgical success. We used the area under the receiver operating characteristic curve as a measure of effect size. Intracranial electrodes were implanted in brain tissue with the most abnormal magnetoencephalography findings-in individuals that were seizure-free postoperatively (T = 3.9, P = 0.001) but not in those who did not become seizure-free. The overlap between magnetoencephalography abnormalities and electrode placement distinguished surgical outcome groups moderately well (area under the receiver operating characteristic curve = 0.68). In isolation, the resection of the strongest abnormalities as defined by magnetoencephalography and intracranial EEG separated surgical outcome groups well, area under the receiver operating characteristic curve = 0.71 and area under the receiver operating characteristic curve = 0.74, respectively. A model incorporating all three features separated surgical outcome groups best (area under the receiver operating characteristic curve = 0.80). Intracranial EEG is a key tool to delineate the epileptogenic zone and help render individuals seizure-free postoperatively. We showed that data-driven abnormality maps derived from resting-state magnetoencephalography recordings demonstrate clinical value and may help guide electrode placement in individuals with neocortical epilepsy. Additionally, our predictive model of postoperative seizure freedom, which leverages both magnetoencephalography and intracranial EEG recordings, could aid patient counselling of expected outcome.

Complementary structural and functional abnormalities to localise epileptogenic tissue.

BACKGROUND: When investigating suitability for epilepsy surgery, people with drug-refractory focal epilepsy may have intracranial EEG (iEEG) electrodes implanted to localise seizure onset. Diffusion-weighted magnetic resonance imaging (dMRI) may be acquired to identify key white matter tracts for surgical avoidance. Here, we investigate whether structural connectivity abnormalities, inferred from dMRI, may be used in conjunction with functional iEEG abnormalities to aid localisation of the epileptogenic zone (EZ), improving surgical outcomes in epilepsy. METHODS: We retrospectively investigated data from 43 patients (42% female) with epilepsy who had surgery following iEEG. Twenty-five patients (58%) were free from disabling seizures (ILAE 1 or 2) at one year. Interictal iEEG functional, and dMRI structural connectivity abnormalities were quantified by comparison to a normative map and healthy controls. We explored whether the resection of maximal abnormalities related to improved surgical outcomes, in both modalities individually and concurrently. Additionally, we suggest how connectivity abnormalities may inform the placement of iEEG electrodes pre-surgically using a patient case study. FINDINGS: Seizure freedom was 15 times more likely in patients with resection of maximal connectivity and iEEG abnormalities (p = 0.008). Both modalities separately distinguished patient surgical outcome groups and when used simultaneously, a decision tree correctly separated 36 of 43 (84%) patients. INTERPRETATION: Our results suggest that both connectivity and iEEG abnormalities may localise epileptogenic tissue, and that these two modalities may provide complementary information in pre-surgical evaluations. FUNDING: This research was funded by UKRI, CDT in Cloud Computing for Big Data, NIH, MRC, Wellcome Trust and Epilepsy Research UK.

Chronic intracranial EEG recordings and interictal spike rate reveal multiscale temporal modulations in seizure states.

Many biological processes are modulated by rhythms on circadian and multidien timescales. In focal epilepsy, various seizure features, such as spread and duration, can change from one seizure to the next within the same patient. However, the specific timescales of this variability, as well as the specific seizure characteristics that change over time, are unclear. Here, in a cross-sectional observational study, we analysed within-patient seizure variability in 10 patients with chronic intracranial EEG recordings (185-767 days of recording time, 57-452 analysed seizures/patient). We characterized the seizure evolutions as sequences of a finite number of patient-specific functional seizure network states. We then compared seizure network state occurrence and duration to (1) time since implantation and (2) patient-specific circadian and multidien cycles in interictal spike rate. In most patients, the occurrence or duration of at least one seizure network state was associated with the time since implantation. Some patients had one or more seizure network states that were associated with phases of circadian and/or multidien spike rate cycles. A given seizure network state's occurrence and duration were usually not associated with the same timescale. Our results suggest that different time-varying factors modulate within-patient seizure evolutions over multiple timescales, with separate processes modulating a seizure network state's occurrence and duration. These findings imply that the development of time-adaptive treatments in epilepsy must account for several separate properties of epileptic seizures and similar principles likely apply to other neurological conditions.

Normative brain mapping using scalp EEG and potential clinical application.

A normative electrographic activity map could be a powerful resource to understand normal brain function and identify abnormal activity. Here, we present a normative brain map using scalp EEG in terms of relative band power. In this exploratory study we investigate its temporal stability, its similarity to other imaging modalities, and explore a potential clinical application. We constructed scalp EEG normative maps of brain dynamics from 17 healthy controls using source-localised resting-state scalp recordings. We then correlated these maps with those acquired from MEG and intracranial EEG to investigate their similarity. Lastly, we use the normative maps to lateralise abnormal regions in epilepsy. Spatial patterns of band powers were broadly consistent with previous literature and stable across recordings. Scalp EEG normative maps were most similar to other modalities in the alpha band, and relatively similar across most bands. Towards a clinical application in epilepsy, we found abnormal temporal regions ipsilateral to the epileptogenic hemisphere. Scalp EEG relative band power normative maps are spatially stable across time, in keeping with MEG and intracranial EEG results. Normative mapping is feasible and may be potentially clinically useful in epilepsy. Future studies with larger sample sizes and high-density EEG are now required for validation.

Intracranial EEG Structure-Function Coupling and Seizure Outcomes After Epilepsy Surgery.

BACKGROUND AND OBJECTIVES: Surgery is an effective treatment for drug-resistant epilepsy, which modifies the brain's structure and networks to regulate seizure activity. Our objective was to examine the relationship between brain structure and function to determine the extent to which this relationship affects the success of the surgery in controlling seizures. We hypothesized that a stronger association between brain structure and function would lead to improved seizure control after surgery. METHODS: We constructed functional and structural brain networks in patients with drug-resistant focal epilepsy by using presurgery functional data from intracranial EEG (iEEG) recordings, presurgery and postsurgery structural data from T1-weighted MRI, and presurgery diffusion-weighted MRI. We quantified the relationship (coupling) between structural and functional connectivity by using the Spearman rank correlation and analyzed this structure-function coupling at 2 spatial scales: (1) global iEEG network level and (2) individual iEEG electrode contacts using virtual surgeries. We retrospectively predicted postoperative seizure freedom by incorporating the structure-function connectivity coupling metrics and routine clinical variables into a cross-validated predictive model. RESULTS: We conducted a retrospective analysis on data from 39 patients who met our inclusion criteria. Brain areas implanted with iEEG electrodes had stronger structure-function coupling in seizure-free patients compared with those with seizure recurrence (p = 0.002, d = 0.76, area under the receiver operating characteristic curve [AUC] = 0.78 [95% CI 0.62-0.93]). Virtual surgeries on brain areas that resulted in stronger structure-function coupling of the remaining network were associated with seizure-free outcomes (p = 0.007, d = 0.96, AUC = 0.73 [95% CI 0.58-0.89]). The combination of global and local structure-function coupling measures accurately predicted seizure outcomes with a cross-validated AUC of 0.81 (95% CI 0.67-0.94). These measures were complementary to other clinical variables and, when included for prediction, resulted in a cross-validated AUC of 0.91 (95% CI 0.82-1.0), accuracy of 92%, sensitivity of 93%, and specificity of 91%. DISCUSSION: Our study showed that the strength of structure-function connectivity coupling may play a crucial role in determining the success of epilepsy surgery. By quantitatively incorporating structure-function coupling measures and standard-of-care clinical variables into presurgical evaluations, we may be able to better localize epileptogenic tissue and select patients for epilepsy surgery. CLASSIFICATION OF EVIDENCE: This is a Class IV retrospective case series showing that structure-function mapping may help determine the outcome from surgical resection for treatment-resistant focal epilepsy.

Effects of MEA Type and Curing Temperature on the Autogenous Deformation, Mechanical Properties, and Microstructure of Cement-Based Materials.

MgO expansive agent (MEA) has the potential to meet the shrinkage compensation demands for concrete in different types of structures due to its designable reactivity and expansion properties. This study investigated the impact of three types of MEAs with different reactivities as well as curing temperature on the autogenous deformation, mechanical properties, and the microstructure of cement-based materials. The results showed that MEA type R exhibits a faster and larger hydration degree and expansion in cement mortars than MEA type M or type S in early ages under 20 °C, while when the curing temperature increases to 40 °C and 60 °C, MEA type M and type S present with significant accelerations in the hydration degree, leading to accelerated expansion rates and significantly increased expansion values compared to MEA type R. Under 40 °C, 5% MEA type M and type S present with 2.2 times and 1.1 times higher expansion in mortars than 5% MEA type R, respectively, and 8% MEA type M and type S present with 7.1 times and 5.6 times higher expansion in mortars than 8% MEA type R, respectively. Under 60 °C, 5% MEA type M and type S present 4.0 times and 3.1 times higher expansion in mortars than 5% MEA type R, respectively, and 8% MEA type M and type S present 7.0 times and 6.6 times higher expansion in mortars than 8% MEA type R, respectively. However, the increase in porosity, especially for large pores with pore size greater than 50 nm as well as the microcracks induced by the 8% dosage of MEA type M, type S, and high curing temperature of 60 °C, result in a decrease in strength of about 30% for the cement mortars. The results indicate that MEA type R is more suitable for shrinkage compensation of cement-based materials with lower temperatures, while MEA type M and type S are more suitable for shrinkage compensation of cement-based materials with higher temperatures. Under high-temperature and low-constraint conditions, the dosage of MEA needs to be strictly controlled to prevent negative effects on the microstructure and strength of cement-based materials.

Effects of anterior temporal lobe resection on cortical morphology.

Neuroimaging can capture brain restructuring after anterior temporal lobe resection (ATLR), a surgical procedure to treat drug-resistant temporal lobe epilepsy (TLE). Here, we examine the effects of this surgery on brain morphology measured in recently-proposed independent variables. We studied 101 individuals with TLE (55 left, 46 right onset) who underwent ATLR. For each individual we considered one pre-surgical MRI and one follow-up MRI 2-13 months after surgery. We used a surface-based method to locally compute traditional morphological variables, and the independent measures K, I, and S, where K measures white matter tension, I captures isometric scaling, and S contains the remaining information about cortical shape. A normative model trained on data from 924 healthy controls was used to debias the data and account for healthy ageing effects occurring during scans. A SurfStat random field theory clustering approach assessed changes across the cortex caused by ATLR. Compared to preoperative data, surgery had marked effects on all morphological measures. Ipsilateral effects were located in the orbitofrontal and inferior frontal gyri, the pre- and postcentral gyri and supramarginal gyrus, and the lateral occipital gyrus and lingual cortex. Contralateral effects were in the lateral occipital gyrus, and inferior frontal gyrus and frontal pole. The restructuring following ATLR is reflected in widespread morphological changes, mainly in regions near the resection, but also remotely in regions that are structurally connected to the anterior temporal lobe. The causes could include mechanical effects, Wallerian degeneration, or compensatory plasticity. The study of independent measures revealed additional effects compared to traditional measures.

ACG-EmoCluster: A Novel Framework to Capture Spatial and Temporal Information from Emotional Speech Enhanced by DeepCluster.

Speech emotion recognition (SER) is a task that tailors a matching function between the speech features and the emotion labels. Speech data have higher information saturation than images and stronger temporal coherence than text. This makes entirely and effectively learning speech features challenging when using feature extractors designed for images or texts. In this paper, we propose a novel semi-supervised framework for extracting spatial and temporal features from speech, called the ACG-EmoCluster. This framework is equipped with a feature extractor for simultaneously extracting the spatial and temporal features, as well as a clustering classifier for enhancing the speech representations through unsupervised learning. Specifically, the feature extractor combines an Attn-Convolution neural network and a Bidirectional Gated Recurrent Unit (BiGRU). The Attn-Convolution network enjoys a global spatial receptive field and can be generalized to the convolution block of any neural networks according to the data scale. The BiGRU is conducive to learning temporal information on a small-scale dataset, thereby alleviating data dependence. The experimental results on the MSP-Podcast demonstrate that our ACG-EmoCluster can capture effective speech representation and outperform all baselines in both supervised and semi-supervised SER tasks.

Novel Preparation of Graphene Foam with Adjustable Dielectric Properties for Efficient Microwave Absorption.

Graphene foams (GFs) prepared via a hydrothermal method can be vacuum-dried directly without the need for freezing by adding naphthalene to the graphene hydrogels. By optimizing the GF preparation process, it is also possible to adjust the GF's dielectric properties by varying the amount of naphthalene added. Based on the comparison results, it was observed that controlling the addition of naphthalene could also modify the internal structure of GF and effectively regulate its dielectric properties. GF-80, synthesized with 80 g of naphthalene, exhibited exceptional microwave absorption (MA) performance. At a mass content of only 2% and a matching thickness of 3.38 mm, a minimum reflection loss (RLmin) of -55.89 dB was achieved. Moreover, GF-80, with a thickness of 2.31 mm, was shown to achieve a bandwidth of RL less than -10 dB across 6.88 GHz.

An update on the seizures beget seizures theory.

Seizures beget seizures is a longstanding theory that proposed that seizure activity can impact the structural and functional properties of the brain circuits in ways that contribute to epilepsy progression and the future occurrence of seizures. Originally proposed by Gowers, this theory continues to be quoted in the pathophysiology of epilepsy. We critically review the existing data and observations on the consequences of recurrent seizures on brain networks and highlight a range of factors that speak for and against the theory. The existing literature demonstrates clearly that ictal activity, especially if recurrent, induces molecular, structural, and functional changes including cell loss, connectivity reorganization, changes in neuronal behavior, and metabolic alterations. These changes have the potential to modify the seizure threshold, contribute to disease progression, and recruit wider areas of the epileptic network into epileptic activity. Repeated seizure activity may, thus, act as a pathological positive-feedback mechanism that increases seizure likelihood. On the other hand, the time course of self-limited epilepsies and the presence of seizure remission in two thirds of epilepsy cases and various chronic epilepsy models oppose the theory. Experimental work showed that seizures could induce neural changes that increase the seizure threshold and decrease the risk of a subsequent seizure. Due to the complex nature of epilepsies, it is wrong to consider only seizures as the key factor responsible for disease progression. Epilepsy worsening can be attributed to the various forms of interictal epileptiform activity or underlying disease mechanisms. Although seizure activity can negatively impact brain structure and function, the "seizures beget seizures" theory should not be used dogmatically but with extreme caution.

Identifying epileptogenic abnormalities through spatial clustering of MEG interictal band power.

Successful epilepsy surgery depends on localizing and resecting cerebral abnormalities and networks that generate seizures. Abnormalities, however, may be widely distributed across multiple discontiguous areas. We propose spatially constrained clusters as candidate areas for further investigation and potential resection. We quantified the spatial overlap between the abnormality cluster and subsequent resection, hypothesizing a greater overlap in seizure-free patients. Thirty-four individuals with refractory focal epilepsy underwent pre-surgical resting-state interictal magnetoencephalography (MEG) recording. Fourteen individuals were totally seizure-free (ILAE 1) after surgery and 20 continued to have some seizures post-operatively (ILAE 2+). Band power abnormality maps were derived using controls as a baseline. Patient abnormalities were spatially clustered using the k-means algorithm. The tissue within the cluster containing the most abnormal region was compared with the resection volume using the dice score. The proposed abnormality cluster overlapped with the resection in 71% of ILAE 1 patients. Conversely, an overlap only occurred in 15% of ILAE 2+ patients. This effect discriminated outcome groups well (AUC = 0.82). Our novel approach identifies clusters of spatially similar tissue with high abnormality. This is clinically valuable, providing (a) a data-driven framework to validate current hypotheses of the epileptogenic zone localization or (b) to guide further investigation.