Temporal Lobe Epilepsy Patients Research Articles

Quantitative analysis of visually normal EEG reveals spectral power abnormalities in temporal lobe epilepsy

ObjectiveTo compare quantitative spectral parameters of visually-normal EEG between Mesial Temporal Lobe Epilepsy (MTLE) patients and healthy controls (HC). MethodWe enrolled 26 MTLE patients and 26 HC. From each recording we calculated total power of all frequency bands and determined alpha-theta (ATR) and alpha-delta (ADR) power ratios in different brain regions. Group-wise differences between spectral parameters were investigated (p < 0.05). To test for associations between spectral-power and cognitive status, we evaluated correlations between neuropsychological tests and quantitative EEG (qEEG) metrics. ResultsIn all comparisons, ATR and ADR were significantly decreased in MTLE patients compared to HC, particularly over the hemisphere ipsilateral to epileptic activity. A positive correlation was seen in MTLE patients between ATR in ipsilateral temporal lobe, and results of neuropsychological tests of auditory verbal learning (RAVLT and RAVLT-D), short term verbal memory (Digit span backwards), and executive function (Weigl's sorting test). ADR values in the contralateral posterior region correlated positively with RAVLT-D and Digit span backwards tests. DiscussionResults confirmed that the power spectrum of qEEG is shifted towards lower frequencies in MTLE patients compared to HC. ConclusionOf note, our results were found in visually-normal recordings, providing further evidence of the value of qEEG for longitudinal monitoring of MTLE patients over time. Exploratory analysis of associations between qEEG and neuropsychological data suggest this could be useful for investigating effects of antiseizure medications on cognitive integrity in patients.

Abnormalities of regional brain activity and executive function in patients with temporal lobe epilepsy: A cross-sectional and longitudinal resting-state functional MRI study.

We decided to track changes in regional brain activity and executive function in temporal lobe epilepsy (TLE) patients based on cross-sectional and longitudinal designs and sought potential imaging features for follow-up observation. Thirty-two TLE patients and thirty-three healthy controls (HCs) were recruited to detect changes in fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) and to evaluate executive function both at baseline and at two-year (23.3 ± 8.3months) follow-up. Moreover, multivariate pattern analysis (MVPA) was used for follow-up observation. TLE patients displayed lower fALFF values in the right superior frontal gyrus (SFG) and higher ReHo values in the left putamen (PUT) relative to the HCs. Longitudinal analysis revealed that TLE patients at follow-up exhibited higher fALFF values in the left postcentral gyrus (PoCG), higher ReHo values in the left PoCG and the right middle frontal gyrus (MFG), lower ReHo values in the bilateral PUT and the right fusiform gyrus (FFG) compared with these patients at baseline. The executive function was impaired in TLE patients but didn't deteriorate over time. No correlations were discovered between regional brain activity and executive function. The MVPA based on ReHo performed well in differentiating the follow-up group from the baseline group. We revealed the abnormalities in regional brain activity and executive function as well as their longitudinal trends in TLE patients. The ReHo might be a good imaging feature for follow-up observation.

Machine learning techniques based on 18F-FDG PET radiomics features of temporal regions for the classification of temporal lobe epilepsy patients from healthy controls.

This study aimed to investigate the clinical application of 18F-FDG PET radiomics features for temporal lobe epilepsy and to create PET radiomics-based machine learning models for differentiating temporal lobe epilepsy (TLE) patients from healthy controls. A total of 347 subjects who underwent 18F-FDG PET scans from March 2014 to January 2020 (234 TLE patients: 25.50 ± 8.89 years, 141 male patients and 93 female patients; and 113 controls: 27.59 ± 6.94 years, 48 male individuals and 65 female individuals) were allocated to the training (n = 248) and test (n = 99) sets. All 3D PET images were registered to the Montreal Neurological Institute template. PyRadiomics was used to extract radiomics features from the temporal regions segmented according to the Automated Anatomical Labeling (AAL) atlas. The least absolute shrinkage and selection operator (LASSO) and Boruta algorithms were applied to select the radiomics features significantly associated with TLE. Eleven machine-learning algorithms were used to establish models and to select the best model in the training set. The final radiomics features (n = 7) used for model training were selected through the combinations of the LASSO and the Boruta algorithms with cross-validation. All data were randomly divided into a training set (n = 248) and a testing set (n = 99). Among 11 machine-learning algorithms, the logistic regression (AUC 0.984, F1-Score 0.959) model performed the best in the training set. Then, we deployed the corresponding online website version (https://wane199.shinyapps.io/TLE_Classification/), showing the details of the LR model for convenience. The AUCs of the tuned logistic regression model in the training and test sets were 0.981 and 0.957, respectively. Furthermore, the calibration curves demonstrated satisfactory alignment (visually assessed) for identifying the TLE patients. The radiomics model from temporal regions can be a potential method for distinguishing TLE. Machine learning-based diagnosis of TLE from preoperative FDG PET images could serve as a useful preoperative diagnostic tool.

A PET-based radiomics nomogram for individualized predictions of seizure outcomes after temporal lobe epilepsy surgery

PurposeTo establish and validate a novel nomogram based on clinical characteristics and [18F]FDG PET radiomics for the prediction of postsurgical seizure freedom in patients with temporal lobe epilepsy (TLE). Patients and Methods234 patients with drug-refractory TLE patients were included with a median follow-up time of 24 months after surgery. The correlation coefficient redundancy analysis and LASSO Cox regression were used to characterize risk factors. The Cox model was conducted to develop a Clinic-PET nomogram to predict the relapse status in the training set (n = 171). The nomogram's performance was estimated through discrimination, calibration, and clinical utility. The prognostic prediction model was validated in the test set (n = 63). ResultsEight radiomics features were selected to assess the radiomics score (radscore) of the operation side (Lat_radscore) and the asymmetric index (AI) of the radiomics score (AI_radscore). AI_radscor, Lat_radscor, secondarily generalized seizures (SGS), and duration between seizure onset and surgery (Durmon) were significant predictors of seizure-free outcomes. The final model had a C-index of 0.68 (95%CI: 0.59-0.77) for complete freedom from seizures and time-dependent AUROC was 0.65 at 12 months, 0.65 at 36 months, and 0.59 at 60 months in the test set. A web application derived from the primary predictive model was displayed for economic and efficient use. ConclusionsA PET-based radiomics nomogram is clinically promising for predicting seizure outcomes after temporal lobe epilepsy surgery.

Sorbs2 regulates seizure activity by influencing AMPAR-mediated excitatory synaptic transmission in temporal lobe epilepsy

Temporal lobe epilepsy (TLE), the most common type of drug-resistant epilepsy, severely affects quality of life. However, the underlying mechanism of TLE remains unclear and deserves further exploration. Sorbs2, a key synaptic regulatory protein, plays an important role in the regulation of synaptic transmission in the mammalian brain. In this study, we aimed to investigate the expression pattern of Sorbs2 in a kainic acid (KA)-induced TLE mouse model and in patients with TLE to further determine whether Sorbs2 is involved in seizure activity and to explore the potential mechanism by which Sorbs2 affects seizures in this TLE mouse model. First, we found that the expression of Sorbs2 was obviously increased in the hippocampus and cortex of a TLE mouse model and in the temporal cortex of TLE patients, indicating an abnormal expression pattern of Sorbs2 in TLE. Importantly, subsequent behavioral analyses and local field potential (LFP) analyses of a TLE mouse model demonstrated that the downregulation of hippocampal Sorbs2 could prolong the latency to spontaneous recurrent seizures (SRSs) and protect against SRSs. We also found that the knockdown of Sorbs2 in the hippocampus could decrease excitatory synaptic transmission in pyramidal neurons (PNs) in the hippocampal CA1 region and reduce the expression levels of the AMPAR subunits GluA1 and GluA2. Thus, we speculated that Sorbs2 may promote epileptogenesis and the development of TLE by affecting AMPAR-mediated excitatory synaptic transmission in PNs in the CA1 region. Therefore, reducing the expression of hippocampal Sorbs2 could restrain epileptogenesis and the development of TLE.

Association between serum apolipoprotein E and cognitive function in Chinese patients with temporal lobe epilepsy

ObjectiveTo investigate the effect of serum apolipoprotein E (APOE) levels on cognitive function in patients with temporal lobe epilepsy (TLE). MethodsClinical data were collected from 190 subjects including 110 TLE patients and 80 healthy people. Cognitive function was assessed using the Addenbrooke’s Cognitive Examination Revised (ACE-R) scale. Serum levels of APOE were measured using ELISA kits. Genotyping of APOE in peripheral blood was detected by microarray hybridization. ResultsPatients with TLE had significantly lower ACE-R total score, memory and verbal fluency scores compared to the healthy group. Serum levels of APOE were significantly higher in TLE patients than in the healthy subjects. Serum APOE levels were significantly negatively correlated with ACE-R total score, memory and verbal fluency scores. The cognitive function score of TLE with APOE ε4 allele was lower than that of TLE without APOE ε4 allele. SignificanceOur study showed that serum APOE levels were higher in TLE patients than in the healthy population. And serum APOE levels were associated with cognitive dysfunction in TLE patients. APOE ε4 allele carriers have poor cognitive function in TLE patients.

PETSurfer-Based Brain Segmentation in Patients with Temporal Lobe Epilepsy and Associated Hippocampal Sclerosis

PurposeIn a homogeneous cohort of mesial temporal lobe epilepsy (mTLE) patients with hippocampal sclerosis (HS), this study utilizes the PETSurfer method to quantify and localize areas of cerebral hypometabolism. MethodsWe selected patients from the University Clinical Center of Serbia who all underwent anterior temporal lobectomy with amygdalohippocampectomy and achieved seizure freedom (Engel class I). Our analysis involved integrating FDG-PET and MRI imaging to compare glucose metabolism between the hemispheres ipsilateral and contralateral to HS. ResultsThe quantitative PETSurfer approach identified significant hypometabolism restricted to the ipsilateral temporal lobe structures—the amygdala, hippocampus, temporal pole, superior and middle temporal gyrus—and the ipsilateral thalamus. The lack of significant hypometabolism in extratemporal regions indicates that these 'pure' mTLE cases may not involve the broader network disruptions typically associated with more extensive epileptic pathologies. The effect sizes ranged from small to medium, indicating variable degrees of metabolic reduction across different structures. ConclusionThese findings highlight the localized nature of the epileptogenic focus in HS-related mTLE with good surgical outcome. However, the small sample size and potential cohort bias, necessitate caution in generalizing these results. Future research would benefit from a comparative approach incorporating a control group, providing a broader context for interpreting these hypometabolic patterns.

Circulating miRNAs as Novel Clinical Biomarkers in Temporal Lobe Epilepsy.

Temporal lobe epilepsy (TLE) represents the most common form of refractory focal epilepsy. The identification of innovative clinical biomarkers capable of categorizing patients with TLE, allowing for improved treatment and outcomes, still represents an unmet need. Circulating microRNAs (c-miRNAs) are short non-coding RNAs detectable in body fluids, which play crucial roles in the regulation of gene expression. Their characteristics, including extracellular stability, detectability through non-invasive methods, and responsiveness to pathological changes and/or therapeutic interventions, make them promising candidate biomarkers in various disease settings. Recent research has investigated c-miRNAs in various bodily fluids, including serum, plasma, and cerebrospinal fluid, of TLE patients. Despite some discrepancies in methodologies, cohort composition, and normalization strategies, a common dysregulated signature of c-miRNAs has emerged across different studies, providing the basis for using c-miRNAs as novel biomarkers for TLE patient management.

A Study of Hippocampal T2 Relaxometry Value in Temporal Lobe Epilepsy Patient

In the advancement of the current imaging technique for detection of mesial temporal sclerosis in temporal lobe epilepsy patient, there are multiple Magnetic resonance imaging (MRI) quantitative techniques. One of the long known to be valuable quantitative technique is T2 relaxometry where it has overall better accuracy for detection of mesial temporal sclerosis compared with the qualitative assessment only. A comparative cross-sectional study was conducted in Hospital Universiti Sains Malaysia from August 2021 to January 2023 which include 51 participants, 19 (36.5%) were temporal lobe epilepsy patient and 33 (63.5%) were control. The hippocampal T2 relaxometry was calculated for temporal lobe epilepsy patient and control. The mean T2 relaxometry reading for these groups were compared using Independent T-test.  The correlation of T2 relaxometry value  with age, duration of epilepsy and seizure frequency were analysed using Pearson correlation. Cohen Kappa inter-rater reliability was done for MR qualitative assessment. The participant age range was from 15 to 65 years old. Total of 23 samples were male (44.2%). The mean T2 relaxometry for epilepsy patient was higher than control. For correlation, moderate to good positive correlation was seen between the duration of epilepsy with T2 relaxometry of right hippocampus. Whereas poor positive correlation between the right hippocampus T2 relaxometry with age (P&gt;0.01), as well poor positive correlation between both hippocampus T2 relaxometry with seizure frequency (P&gt;0.01). There was one patient (5.2%) reported to be negative for mesial temporal sclerosis by qualitative assessment, but the T2 relaxometry reading however was raised.  As a conclusion, T2 relaxometry sequence can be use as adjunct to the current qualitative assessment to increase sensitivity and specificity in detecting mesial temporal sclerosis.&#x0D; Keywords: Temporal lobe epilepsy, Mesial temporal sclerosis, T2 relaxometry, MRI epilepsy protocol

May anti-seizure medications alter brain structure in temporal lobe epilepsy? A prospective study.

Mild mesial temporal lobe epilepsy (MTLE) patients may remain untreated for a considerable time after disease onset or achieve seizure control with a single anti-seizures medication (ASM). Thus, they represent an optimal population to investigate whether ASMs might have influence on brain structure. We consecutively enrolled 56 mild MTLE patients (22/56 untreated, 34/56 on-monotherapy) and 58 healthy controls, matched for age and gender. All subjects underwent 3T-brain MRI, using FreeSurfer for automated morphometry. Differences in gray matter were assessed using one-way Analysis of Covariance (ANCOVA), adjusting for age, disease duration and intracranial volume. No significant change was observed between treated and untreated patients. We observed a significant reduction in cortical thickness of left inferior parietal, inferior temporal, middle temporal gyri, and right inferior parietal gyrus, temporal pole in monotherapy patients compared to healthy controls, as well as an increase in left isthmus of cingulate gyrus in untreated MTLE subjects compared to controls. Surface and subcortical volumes analysis revealed no differences among groups. Our study demonstrated no substantial morphological abnormalities between untreated mild MTLE patients and those undergoing monotherapy. Although exploratory, these results may reassure about safety of commonly used drugs and their marginal role in influencing neuroimaging results. PLAIN LANGUAGE SUMMARY: This study investigated the following question: can medications against epileptic seizures have an effect on brain structure in mild mesial temporal lobe? Preliminary results from our analyses suggest not, as we did not find any difference in brain gray matter between untreated patients and those treated with a single anti-seizures medication. On the other hand, epilepsy patients presented cortical thinning compared to healthy controls in several regions of the temporal and parietal lobes, in line with previous studies investigating the disease.

Decomposed FDG PET-based phenotypic heterogeneity predicting clinical prognosis and decision-making in temporal lobe epilepsy patients.

This study utilized a data-driven Bayesian model to automatically identify distinct latent disease factors represented by overlapping glucose metabolism patterns from 18F-Fluorodeoxyglucose PET (18F-FDG PET) to analyze heterogeneity among patients with TLE. We employed unsupervised machine learning to estimate latent disease factors from 18F-FDG PET scans, representing whole-brain glucose metabolism patterns in seventy patients with TLE. We estimated the extent to which multiple distinct factors were expressed within each participant and analyzed their relevance to epilepsy burden, including seizure onset, duration, and frequency. Additionally, we established a predictive model for clinical prognosis and decision-making. We identified three latent disease factors: hypometabolism in the unilateral temporal lobe and hippocampus (factor 1), hypometabolism in bilateral prefrontal lobes (factor 2), and hypometabolism in bilateral temporal lobes (factor 3), variably co-expressed within each patient. Factor 3 demonstrated the strongest negative correlation with the age of onset and duration (r =  - 0.33, - 0.38 respectively, P < 0.05). The supervised classifier, trained on latent disease factors for predicting patient-specific antiepileptic drug (AED) responses, achieved an area under the curve (AUC) of 0.655. For post-surgical seizure outcomes, the AUC was 0.857, and for clinical decision-making, it was 0.965. Decomposing 18F-FDG PET-based phenotypic heterogeneity facilitates individual-level predictions relevant to disease monitoring and personalized therapeutic strategies.

Membranes and Synaptosomes Used to Investigate Synaptic GABAergic Currents in Epileptic Patients.

Among the most prevalent neurological disorders, epilepsy affects about 1% of the population worldwide. We previously found, using human epileptic tissues, that GABAergic neurotransmission impairment is a key mechanism that drives the pathological phenomena that ultimately lead to generation and recurrence of seizures. Using both a "microtransplantation technique" and synaptosomes preparations from drug-resistant temporal lobe epilepsies (TLEs), we used the technique of two-electrode voltage clamp to record GABA-evoked currents, focusing selectively on the synaptic "fast inhibition" mediated by low-affinity GABAA receptors. Here, we report that the use-dependent GABA current desensitization (i.e., GABA rundown, which is evoked by applying to the cells consecutive pulses of GABA, at high concentration), which is a distinguishing mark of TLE, is mainly dependent on a dysfunction that affects synaptic GABAA receptors. In addition, using the same approaches, we recorded a depolarized GABA reversal potential in synaptosomes samples from the human epileptic subicula of TLE patients. These results, which confirm previous experiments using total membranes, suggest an altered chloride homeostasis in the synaptic area. Finally, the lack of a Zn2+ block of GABA-evoked currents using the synaptosomes supports the enrichment of "synaptic fast inhibitory" GABAA receptors in this preparation. Altogether, our findings suggest a pathophysiological role of low-affinity GABAA receptors at the synapse, especially during the fast and repetitive GABA release underlying recurrent seizures.

Preoperative structural-functional coupling at the default mode network predicts surgical outcomes of temporal lobe epilepsy.

Structural-functional coupling (SFC) has shown great promise in predicting postsurgical seizure recurrence in patients with temporal lobe epilepsy (TLE). In this study, we aimed to clarify the global alterations in SFC in TLE patients and predict their surgical outcomes using SFC features. This study analyzed presurgical diffusion and functional magnetic resonance imaging data from 71 TLE patients and 48 healthy controls (HCs). TLE patients were categorized into seizure-free (SF) and non-seizure-free (nSF) groups based on postsurgical recurrence. Individual functional connectivity (FC), structural connectivity (SC), and SFC were quantified at the regional and modular levels. The data were compared between the TLE and HC groups as well as among the TLE, SF, and nSF groups. The features of SFC, SC, and FC were categorized into three datasets: the modular SFC dataset, regional SFC dataset, and SC/FC dataset. Each dataset was independently integrated into a cross-validated machine learning model to classify surgical outcomes. Compared with HCs, the visual and subcortical modules exhibited decoupling in TLE patients (p < .05). Multiple default mode network (DMN)-related SFCs were significantly higher in the nSF group than in the SF group (p < .05). Models trained using the modular SFC dataset demonstrated the highest predictive performance. The final prediction model achieved an area under the receiver operating characteristic curve of .893 with an overall accuracy of .887. Presurgical hyper-SFC in the DMN was strongly associated with postoperative seizure recurrence. Furthermore, our results introduce a novel SFC-based machine learning model to precisely classify the surgical outcomes of TLE.

Cortical Thickness Patterns of Cognitive Impairment Phenotypes in Drug-Resistant Temporal Lobe Epilepsy.

In temporal lobe epilepsy (TLE), a taxonomy classifying patients into 3 cognitive phenotypes has been adopted: minimally, focally, or multidomain cognitively impaired (CI). We examined gray matter (GM) thickness patterns of cognitive phenotypes in drug-resistant TLE and assessed potential use for predicting postsurgical cognitive outcomes. TLE patients undergoing presurgical evaluation were categorized into cognitive phenotypes. Network edge weights and distances were calculated using type III analysis of variance F-statistics from comparisons of GM regions within each TLE cognitive phenotype and age- and sex-matched healthy participants. In resected patients, logistic regression models (LRMs) based on network analysis results were used for prediction of postsurgical cognitive outcome. A total of 124 patients (63 females, mean age ± standard deviation [SD] = 36.0 ± 12.0 years) and 117 healthy controls (63 females, mean age ± SD = 36.1 ± 12.0 years) were analyzed. In the multidomain CI group (n = 66, 53.2%), 28 GM regions were significantly thinner compared to healthy controls. Focally impaired patients (n = 37, 29.8%) showed 13 regions, whereas minimally impaired patients (n = 21, 16.9%) had 2 significantly thinner GM regions. Regions affected in both multidomain and focally impaired patients included the anterior cingulate cortex, medial prefrontal cortex, medial temporal, and lateral temporal regions. In 69 (35 females, mean age ± SD = 33.6 ± 18.0 years) patients who underwent surgery, LRMs based on network-identified GM regions predicted postsurgical verbal memory worsening with a receiver operating curve area under the curve of 0.70 ± 0.15. A differential pattern of GM thickness can be found across different cognitive phenotypes in TLE. Including magnetic resonance imaging with clinical measures associated with cognitive profiles has potential in predicting postsurgical cognitive outcomes in drug-resistant TLE. ANN NEUROL 2024.

Dynamic facial emotion recognition and affective prosody recognition are associated in patients with temporal lobe epilepsy

Deficits in facial emotion recognition have frequently been established in temporal lobe epilepsy (TLE). However, static, rather than dynamic emotion recognition paradigms have been applied. Affective prosody has been insufficiently studied in TLE, and there is a lack of studies investigating associations between auditory and visual emotion recognition. We wished to investigate potential deficits in a dynamic morph task of facial emotion recognition and in an affective prosody recognition task, as well as associations between both tasks. 25 patients with TLE and 24 healthy controls (CG) performed a morph task with faces continuously changing in their emotional intensity. They had to press a button, as soon as they were able to recognize the emotion expressed, and label it accordingly. In the auditory task, subjects listened to neutral sentences spoken in varying emotional tones, and labeled the emotions. Correlation analyses were conducted across both tasks. TLE patients showed significantly reduced prosody recognition compared to CG, and in the morph task, there was a statistical trend towards significantly reduced performance for TLE. Recognition rates in both tasks were significantly associated. TLE patients show deficits in affective prosody recognition, and they may also be impaired in a morph task with dynamically changing facial expressions. Impairments in basic social-cognitive tasks in TLE seem to be modality-independent.

Mass Spectrometric Imaging of Anionic Phospholipids Desorbed from Human Hippocampal Sections: Discrimination between Temporal and Nontemporal Lobe Epilepsies.

Temporal lobe epilepsy (TLE) is one of the most common neurological disorders, often accompanied by hippocampal sclerosis. The molecular processes underlying this epileptogenesis are poorly understood. To examine the lipid profile, 39 fresh frozen sections of the human hippocampus obtained from epilepsy surgery for TLE (n = 14) and non-TLE (control group; n = 25) patients were subjected to desorption electrospray ionization mass spectrometry imaging in the negative ion mode. In contrast to our earlier report that showed striking downregulation of positively charged phospholipids (e.g., phosphatidylcholine and phosphatidylethanolamine, etc.) in the TLE hippocampus, this study finds complementary upregulation of negatively charged phospholipids, notably, phosphatidylserine and phosphatidylglycerol. This result may point to an active metabolic pool in the TLE hippocampus that produces these anionic phospholipids at the expense of the cationic phospholipids. This metabolic shift could be due to the dysregulation of the Kennedy and CDP-DG pathways responsible for biosynthesizing these lipids. Thus, this study further opens up opportunities to investigate the molecular hallmarks and potential therapeutic targets for TLE.

Automated detection of MRI-negative temporal lobe epilepsy with ROI-based morphometric features and machine learning.

Temporal lobe epilepsy (TLE) predominantly originates from the anteromedial basal region of the temporal lobe, and its prognosis is generally favorable following surgical intervention. However, TLE often appears negative in magnetic resonance imaging (MRI), making it difficult to quantitatively diagnose the condition solely based on clinical symptoms. There is a pressing need for a quantitative, automated method for detecting TLE. This study employed MRI scans and clinical data from 51 retrospective epilepsy cases, dividing them into two groups: 34 patients in TLE group and 17 patients in non-TLE group. The criteria for defining the TLE group were successful surgical removal of the epileptogenic zone in the temporal lobe and a favorable postoperative prognosis. A standard procedure was used for normalization, brain extraction, tissue segmentation, regional brain partitioning, and cortical reconstruction of T1 structural MRI images. Morphometric features such as gray matter volume, cortical thickness, and surface area were extracted from a total of 20 temporal lobe regions in both hemispheres. Support vector machine (SVM), extreme learning machine (ELM), and cmcRVFL+ classifiers were employed for model training and validated using 10-fold cross-validation. The results demonstrated that employing ELM classifiers in conjunction with specific temporal lobe gray matter volume features led to a better identification of TLE. The classification accuracy was 92.79%, with an area under the curve (AUC) value of 0.8019. The method proposed in this study can significantly assist in the preoperative identification of TLE patients. By employing this method, TLE can be included in surgical criteria, which could alleviate patient symptoms and improve prognosis, thereby bearing substantial clinical significance.

Changes in the Dentate Gyrus Gene Expression Profile Induced by Levetiracetam Treatment in Rats with Mesial Temporal Lobe Epilepsy.

Temporal lobe epilepsy (TLE) is one of the most common forms of focal epilepsy. Levetiracetam (LEV) is an antiepileptic drug whose mechanism of action at the genetic level has not been fully described. Therefore, the aim of the present work was to evaluate the relevant gene expression changes in the dentate gyrus (DG) of LEV-treated rats with pilocarpine-induced TLE. Whole-transcriptome microarrays were used to obtain the differential genetic profiles of control (CTRL), epileptic (EPI), and EPI rats treated for one week with LEV (EPI + LEV). Quantitative RT-qPCR was used to evaluate the RNA levels of the genes of interest. According to the results of the EPI vs. CTRL analysis, 685 genes were differentially expressed, 355 of which were underexpressed and 330 of which were overexpressed. According to the analysis of the EPI + LEV vs. EPI groups, 675 genes were differentially expressed, 477 of which were downregulated and 198 of which were upregulated. A total of 94 genes whose expression was altered by epilepsy and modified by LEV were identified. The RT-qPCR confirmed that LEV treatment reversed the increased expression of Hgf mRNA and decreased the expression of the Efcab1, Adam8, Slc24a1, and Serpinb1a genes in the DG. These results indicate that LEV could be involved in nonclassical mechanisms involved in Ca2+ homeostasis and the regulation of the mTOR pathway through Efcab1, Hgf, SLC24a1, Adam8, and Serpinb1a, contributing to reduced hyperexcitability in TLE patients.

Semiautomated electric source imaging determines epileptogenicity of encephaloceles in temporal lobe epilepsy.

We aimed to assess the ability of semiautomated electric source imaging (ESI) from long-term video-electroencephalographic (EEG) monitoring (LTM) to determine the epileptogenicity of temporopolar encephaloceles (TEs) in patients with temporal lobe epilepsy. We conducted a retrospective study involving 32 temporal lobe epilepsy patients with TEs as potentially epileptogenic lesions in structural magnetic resonance imaging scans. Findings were validated through invasive intracerebral stereo-EEG in six of 32 patients and postsurgical outcome after tailored resection of the TE in 17 of 32 patients. LTM (mean duration = 6 days) was performed using the 10/20 system with additional T1/T2 for all patients and sphenoidal electrodes in 23 of 32 patients. Semiautomated detection and clustering of interictal epileptiform discharges (IEDs) were carried out to create IED types. ESI was performed on the averages of the two most frequent IED types per patient, utilizing individual head models, and two independent inverse methods (sLORETA [standardized low-resolution brain electromagnetic tomography], MUSIC [multiple signal classification]). ESI maxima concordance and propagation in spatial relation to TEs were quantified for sources with good signal quality (signal-to-noise ratio > 2, explained signal > 60%). ESI maxima correctly colocalized with a TE in 20 of 32 patients (62.5%) either at the onset or half-rising flank of at least one IED type per patient. ESI maxima showed propagation from the temporal pole to other temporal or extratemporal regions in 14 of 32 patients (44%), confirming propagation originating in the area of the TE. The findings from both inverse methods validated each other in 14 of 20 patients (70%), and sphenoidal electrodes exhibited the highest signal amplitudes in 17 of 23 patients (74%). The concordance of ESI with the TE predicted a seizure-free postsurgical outcome (Engel I vs. >I) with a diagnostic odds ratio of 2.1. Semiautomated ESI from LTM often successfully identifies the epileptogenicity of TEs and the IED onset zone within the area of the TEs. Additionally, it shows potential predictive power for postsurgical outcomes in these patients.

Disruption of TLE epileptiform activity retarded the seizure and reduced pathological HFOs

In temporal lobe epilepsy (TLE), the epileptogenic zones, such as the temporal lobe structure, could generate pathological high-frequency oscillations (pHFOs, 250–500 Hz) before the ictal period. These pHFOs have also been observed during the process of seizures in both TLE patients and animals, exhibiting a critical role as promising biomarkers for TLE seizures. TLE seizures could be modulated via regulating the neural excitability in epileptogenic zones, for that TLE is primarily associated with the excitation-inhibition imbalance. However, whether these kinds of modulations could also impact the pHFOs characteristics during TLE seizures is still unclear. For this purpose, we pharmaco-genetically inhibited the principal cells (PCs) in the mouse CA3 region and tracked the difference in the behavioral and electrophysiological features during LiCl-pilocarpine-induced TLE seizure between the hM4Di+CNO (experimental) mice and mCherry+CNO (control) mice. Delayed latency, decreased averaged duration, and reduced counts of the generalized seizure were observed in the experimental mice. Besides, the electrophysiological characteristics, such as the firing rate of PCs and the count of pHFO, exhibited significant decline in the CA3 and CA1 regions. During TLE seizure, there existed strong phase-coupling between pHFO and PCs spike timing in the control mice, while it was abolished in the experimental mice. In addition, we also found that the counts of pHFO were significantly associated with the behavioral features, indicating the close relationships within them. Collectively, our findings suggested that alterations in pHFO and the retardation of seizures may be attributed to disruptions in neuronal excitability, and the variations of electrophysiological features were related to seizure severity during TLE seizures. These results provide valuable insights into the role of pHFOs in TLE and shed light on the underlying mechanisms involved.