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EEG features of focal malformations of cortical development

Raymond AA, Fish DR

J Clin Neurophysiol, 1996 Nov;13(6):495-506.
PMID: 8978621

Recent advances in neuroimaging have allowed the detection and characterization of focal malformations of cortical developmental in a significant proportion of patients with epilepsy, many of whom were previously labelled as cryptogenic, allowing a better description of the associated electroencephalogram (EEG) features. Alpha activity is usually preserved, although superficial gyral abnormalities are often associated with overlying localized polymorphic delta activity, and occasionally abnormal fast activity. Most affected patients with epilepsy show interictal spikes. These are often broadly concordant with the structural abnormality but may show a wider anatomic distribution and be multifocal, or occasionally appear only in anatomically distant sites. In many patients the spikes are frequent and sometimes they occur continuously or in long trains. EEG findings are often stable over time, but some patients only show the development of slow wave changes or interictal spikes when followed serially for several years. A small proportion of patients with focal malformations of cortical development have EEG features mimicking idiopathic generalized epilepsy, and occasionally patients exhibit continuous generalized spike and slow wave activity in sleep. Electrocorticography studies confirm the often widespread nature of interictal spiking, but may also show highly epileptogenic patterns recorded directly from dysplastic cortex. The intrinsic epileptogenicity of areas of cortical developmental abnormalities has also been demonstrated by chronic intracranial studies and in vitro recordings of slices obtained from resected human dysplastic cortex. In this regard such developmental abnormalities are fundamentally different from acquired lesions such as tumors/vascular anomalies that usually exert their effects through changes in adjacent cortex.

Matched MeSH terms: Epilepsy/physiopathology
Fulltext A study of newly diagnosed epilepsy in Malaysia

Manonmani V, Tan CT

Singapore Med J, 1999 Jan;40(1):32-5.
PMID: 10361483

To determine the characteristics of newly diagnosed epilepsy in the multiracial population of Malaysia.

Matched MeSH terms: Epilepsy/physiopathology
Fulltext Lamotrigine as an add-on therapy in intractable paediatric epilepsy--the Kuala Lumpur Hospital experience

Vigneswari G, Sofiah A, Hussain IHMI

Med J Malaysia, 2001 Sep;56(3):359-64.
PMID: 11732083

An observational study of all children with intractable epilepsy at the Paediatric Institute prescribed Lamotrigine as an add-on therapy between January 1994 and November 1998 was conducted. A total of 30 children were recruited. Three had adverse effects to the drug and it was withdrawn. Of the remaining 27, there were 20 boys and 7 girls, ranging from 2 to 17 years. Fifteen children had generalised epilepsy, 6 had partial epilepsy, 2 had West syndrome and 4 had Lennox Gastaut syndrome. Six children (20%) became seizure free, and 14 (54%) had a greater than 50% reduction in seizure frequency. However 7 children (23%) did not respond and 3 experienced a deterioration in seizure severity. Nine children were noted to have an improvement in alertness and behaviour. Our small series suggests that Lamotrigine is useful as add-on therapy in childhood intractable epilepsy.

Matched MeSH terms: Epilepsy/physiopathology*
Clinical predictors of intractable childhood epilepsy

Gururaj A, Sztriha L, Hertecant J, Eapen V

J Psychosom Res, 2006 Sep;61(3):343-7.
PMID: 16938512

This study aimed to determine the clinical, electroencephalographic, and radiological factors associated with medically intractable seizures in children in the Al Ain Medical District in the United Arab Emirates.

Matched MeSH terms: Epilepsy/physiopathology*
Fulltext Short QTc in epilepsy patients without cardiac symptoms

Teh HS, Tan HJ, Loo CY, Raymond AA

Med J Malaysia, 2007 Jun;62(2):104-8.
PMID: 18705439

Epilepsy patients have a higher mortality rate than the general population. Sudden unexpected death in epilepsy (SUDEP) is a major cause of mortality for these patients. The possibility of cardiac involvement in the pathogenesis of SUDEP has been suggested by many previous studies. This study compared the QT interval in epilepsy patients and normal controls, and identified the factors that affected the QT interval. Standard 12-lead ECGs were recorded from 70 consecutive epilepsy patients from the neurology clinic of HUKM and 70 age, race and gender matched controls. The mean QT interval corrected for heart rate (QTc) was calculated and compared. The mean QTc among the epilepsy patients was 0.401 +/- 0.027s. It was significantly shorter than the QTc (0.420 +/- 0.027s) in the control group (p<0.0005). Thirty five epilepsy patients (50%) and 17 matched controls (24.3%) had a mean QTc shorter than 0.40s (p=0.001). Among the epilepsy patients, the mean QTc did not significantly differ between patients in the duration (F=0.836, p=0.438) of the epilepsy, frequency (F=0.273, p=0.845) and types of seizures (p=0.633). There was no significant difference in the mean QTc between the epilepsy patients on different number of antiepileptic agents (F=0.444, p=0.643). Patients with cryptogenic epilepsy had a mean QTc of 0.392 +/- 0.029s, which was significantly shorter than patients with symptomatic epilepsy (QTc = 0.410 +/- 0.027s, p = 0.015). The mean QTc of the same subjects showed no significant interobserver difference (p=0.661). This study, for the first time, demonstrates that epilepsy patients have a significantly shorter QTc than controls, particularly in the subgroup of patients with cryptogenic epilepsy.
Study site: Neurology clinic, Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM), Kuala Lumpur, Malaysia

Matched MeSH terms: Epilepsy/physiopathology*
Fulltext 9th Workshop on the Neurobiology of Epilepsy (WONOEP IX): the transition from the interictal to the ictal state (Teluk Nibong, Langkawi Island, Malaysia, July 4-7, 2007)

de Curtis M, Murashima Y, Sankar R

Epilepsia, 2008 Aug;49(8):1475-9.
PMID: 18754944 DOI: 10.1111/j.1528-1167.2008.01618_1.x
Matched MeSH terms: Epilepsy/physiopathology*
A study on discrete wavelet-based noise removal from EEG signals

Asaduzzaman K, Reaz MB, Mohd-Yasin F, Sim KS, Hussain MS

Adv Exp Med Biol, 2010;680:593-9.
PMID: 20865544 DOI: 10.1007/978-1-4419-5913-3_65

Electroencephalogram (EEG) serves as an extremely valuable tool for clinicians and researchers to study the activity of the brain in a non-invasive manner. It has long been used for the diagnosis of various central nervous system disorders like seizures, epilepsy, and brain damage and for categorizing sleep stages in patients. The artifacts caused by various factors such as Electrooculogram (EOG), eye blink, and Electromyogram (EMG) in EEG signal increases the difficulty in analyzing them. Discrete wavelet transform has been applied in this research for removing noise from the EEG signal. The effectiveness of the noise removal is quantitatively measured using Root Mean Square (RMS) Difference. This paper reports on the effectiveness of wavelet transform applied to the EEG signal as a means of removing noise to retrieve important information related to both healthy and epileptic patients. Wavelet-based noise removal on the EEG signal of both healthy and epileptic subjects was performed using four discrete wavelet functions. With the appropriate choice of the wavelet function (WF), it is possible to remove noise effectively to analyze EEG significantly. Result of this study shows that WF Daubechies 8 (db8) provides the best noise removal from the raw EEG signal of healthy patients, while WF orthogonal Meyer does the same for epileptic patients. This algorithm is intended for FPGA implementation of portable biomedical equipments to detect different brain state in different circumstances.

Matched MeSH terms: Epilepsy/physiopathology
The interactive animated epilepsy education programme (IAEEP): how feasible, acceptable and practical is the technology to children?

Lua PL, Neni WS, Lee JK, Abd Aziz Z

Technol Health Care, 2013;21(6):547-56.
PMID: 24284547 DOI: 10.3233/THC-130758

Being well-informed and knowledgeable about their illnesses would be a great advantage to children with epilepsy (CWE). Subsequently, an effective education programme which could secure interest and simultaneously improve their awareness, knowledge and attitudes (AKA) is essential in enhancing well-being and health outcomes.

Matched MeSH terms: Epilepsy/physiopathology
Jeavons syndrome in China

Wang XL, Bao JX, Liang-Shi, Tie-Ma, Deng YC, Zhao G, et al.

Epilepsy Behav, 2014 Mar;32:64-71.
PMID: 24495864 DOI: 10.1016/j.yebeh.2013.12.016

Jeavons syndrome (JS) is one of the underreported epileptic syndromes and is characterized by eyelid myoclonia (EM), eye closure-induced seizures or electroencephalography (EEG) paroxysms, and photosensitivity. In the Western populations, it has been reported to be characterized by focal posterior, occipital predominant epileptiform discharges (OPEDs) or frontal predominant epileptiform discharges (FPEDs) followed by generalized EDs in both interictal and ictal EEG recordings. However, it is not clear if there are different clinical manifestations between OPEDs and FPEDs. The clinical and electrographic presentations in the Chinese population are largely unknown. Here, we report the clinical and electroencephalographic features of 50 Chinese patients with JS and evaluate for the presence of different clinical features between patients with OPEDs and patients with FPEDs.

Matched MeSH terms: Epilepsy/physiopathology
Neuroimaging in refractory epilepsy. Current practice and evolving trends

Ramli N, Rahmat K, Lim KS, Tan CT

Eur J Radiol, 2015 Sep;84(9):1791-800.
PMID: 26187861 DOI: 10.1016/j.ejrad.2015.03.024

Identification of the epileptogenic zone is of paramount importance in refractory epilepsy as the success of surgical treatment depends on complete resection of the epileptogenic zone. Imaging plays an important role in the locating and defining anatomic epileptogenic abnormalities in patients with medically refractory epilepsy. The aim of this article is to present an overview of the current MRI sequences used in epilepsy imaging with special emphasis of lesion seen in our practices. Optimisation of epilepsy imaging protocols are addressed and current trends in functional MRI sequences including MR spectroscopy, diffusion tensor imaging and fusion MR with PET and SPECT are discussed.

Matched MeSH terms: Epilepsy/physiopathology
Fulltext Ensemble classifier for epileptic seizure detection for imperfect EEG data

Abualsaud K, Mahmuddin M, Saleh M, Mohamed A

ScientificWorldJournal, 2015;2015:945689.
PMID: 25759863 DOI: 10.1155/2015/945689

Brain status information is captured by physiological electroencephalogram (EEG) signals, which are extensively used to study different brain activities. This study investigates the use of a new ensemble classifier to detect an epileptic seizure from compressed and noisy EEG signals. This noise-aware signal combination (NSC) ensemble classifier combines four classification models based on their individual performance. The main objective of the proposed classifier is to enhance the classification accuracy in the presence of noisy and incomplete information while preserving a reasonable amount of complexity. The experimental results show the effectiveness of the NSC technique, which yields higher accuracies of 90% for noiseless data compared with 85%, 85.9%, and 89.5% in other experiments. The accuracy for the proposed method is 80% when SNR=1 dB, 84% when SNR=5 dB, and 88% when SNR=10 dB, while the compression ratio (CR) is 85.35% for all of the datasets mentioned.

Matched MeSH terms: Epilepsy/physiopathology*
Fulltext A signal processing based analysis and prediction of seizure onset in patients with epilepsy

Namazi H, Kulish VV, Hussaini J, Hussaini J, Delaviz A, Delaviz F, et al.

Oncotarget, 2016 Jan 5;7(1):342-50.
PMID: 26586477 DOI: 10.18632/oncotarget.6341

One of the main areas of behavioural neuroscience is forecasting the human behaviour. Epilepsy is a central nervous system disorder in which nerve cell activity in the brain becomes disrupted, causing seizures or periods of unusual behaviour, sensations and sometimes loss of consciousness. An estimated 5% of the world population has epileptic seizure but there is not any method to cure it. More than 30% of people with epilepsy cannot control seizure. Epileptic seizure prediction, refers to forecasting the occurrence of epileptic seizures, is one of the most important but challenging problems in biomedical sciences, across the world. In this research we propose a new methodology which is based on studying the EEG signals using two measures, the Hurst exponent and fractal dimension. In order to validate the proposed method, it is applied to epileptic EEG signals of patients by computing the Hurst exponent and fractal dimension, and then the results are validated versus the reference data. The results of these analyses show that we are able to forecast the onset of a seizure on average of 25.76 seconds before the time of occurrence.

Matched MeSH terms: Epilepsy/physiopathology*
Bone loss with antiepileptic drug therapy: a twin and sibling study

Shiek Ahmad B, Petty SJ, Gorelik A, O'Brien TJ, Hill KD, Christie JJ, et al.

Osteoporos Int, 2017 Sep;28(9):2591-2600.
PMID: 28589417 DOI: 10.1007/s00198-017-4098-9

Changes in areal bone mineral density (aBMD) and other predictors of bone loss were evaluated in 48 same-sex twin/age-matched sibling pairs discordant for antiepileptic drug (AED) use. AED users had reduced BMD at the hip regions. Prolonged AED users had greater aBMD loss, predicting a higher risk of bone fragility.
INTRODUCTION: To investigate the longitudinal associations of bone mineral measures with antiepileptic drug (AED) use, including enzyme-inducing (EIAED) and non-enzyme-inducing (NEIAED) types, and other predictors of bone loss in a study of 48 same-sex twin/age-matched sibling pairs (40 female, 8 male) discordant for AED use.
METHODS: Using dual-energy X-ray absorptiometry (DXA), areal bone mineral density (aBMD) and content (BMC) at the hip regions, forearm, lumbar spine, and whole body were measured twice, at least 2 years apart. The mean within-pair difference (MWPD), MWPD%, and mean annual rate of aBMD change were adjusted for age, weight, and height. Predictors of bone loss were evaluated.
RESULTS: AED users, compared to non-users, at baseline and follow-up, respectively, had reduced aBMD at the total hip (MWPD% 3.8, 4.4%), femoral neck (4.7, 4.5%), and trochanter regions (4.1, 4.6%) (p 0.05) regions did not differ within pairs. Nevertheless, EIAED users had greater aBMD loss than non-users (n = 20 pairs) at the total hip (1.7 vs. 0.3%, p = 0.013) and whole body regions (0.7% loss vs. 0.1% BMD gain, p = 0.019), which was not found in NEIAED-discordant pairs (n = 16). AED use >20 years predicted higher aBMD loss at the forearm (p = 0.028), whole body (p = 0.010), and whole body BMC (p = 0.031).
CONCLUSIONS: AED users had reduced aBMD at the hip regions. Prolonged users and EIAED users had greater aBMD loss, predicting a higher risk of bone fragility. Further prospective studies of AED effects on bone microarchitecture are needed.

Matched MeSH terms: Epilepsy/physiopathology
Determinants of low bone mineral density in children with epilepsy

Fong CY, Kong AN, Noordin M, Poh BK, Ong LC, Ng CC

Eur. J. Paediatr. Neurol., 2018 Jan;22(1):155-163.
PMID: 29122496 DOI: 10.1016/j.ejpn.2017.10.007

INTRODUCTION: Children with epilepsy on long-term antiepileptic drugs (AEDs) are at risk of low bone mineral density (BMD). The aims of our study were to evaluate the prevalence and determinants of low BMD among Malaysian children with epilepsy.
METHOD: Cross-sectional study of ambulant children with epilepsy on long-term AEDs for >1 year seen in a tertiary hospital in Malaysia from 2014 to 2015. Detailed assessment of anthropometric measurements; environmental lifestyle risk factors; serum vitamin D, calcium and parathyroid hormone levels; genotyping of single nucleotide polymorphisms of genes in vitamin D and calcium metabolism; and lumbar spine BMD were obtained. Low BMD was defined as BMD Z-score ≤ -2.0 SD.
RESULTS: Eighty-seven children with mean age of 11.9 years (56 males) participated in the study. The prevalence of low lumbar BMD was 21.8% (19 patients). Multivariate logistic regression analysis identified polytherapy >2 AEDs (OR: 7.86; 95% CI 1.03-59.96), small frame size with wrist breadth of <15th centile (OR 14.73; 95% CI 2.21-98.40), and body mass index Z-score 2 AEDs, underweight or with small frame size as they are at higher risk of having low BMD.

Matched MeSH terms: Epilepsy/physiopathology
Fulltext Treatment, Therapy and Management of Metabolic Epilepsy: A Systematic Review

Lin Lin Lee V, Kar Meng Choo B, Chung YS, P Kundap U, Kumari Y, Shaikh MF

Int J Mol Sci, 2018 Mar 15;19(3).
PMID: 29543761 DOI: 10.3390/ijms19030871

Metabolic epilepsy is a metabolic abnormality which is associated with an increased risk of epilepsy development in affected individuals. Commonly used antiepileptic drugs are typically ineffective against metabolic epilepsy as they do not address its root cause. Presently, there is no review available which summarizes all the treatment options for metabolic epilepsy. Thus, we systematically reviewed literature which reported on the treatment, therapy and management of metabolic epilepsy from four databases, namely PubMed, Springer, Scopus and ScienceDirect. After applying our inclusion and exclusion criteria as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we reviewed a total of 43 articles. Based on the reviewed articles, we summarized the methods used for the treatment, therapy and management of metabolic epilepsy. These methods were tailored to address the root causes of the metabolic disturbances rather than targeting the epilepsy phenotype alone. Diet modification and dietary supplementation, alone or in combination with antiepileptic drugs, are used in tackling the different types of metabolic epilepsy. Identification, treatment, therapy and management of the underlying metabolic derangements can improve behavior, cognitive function and reduce seizure frequency and/or severity in patients.

Matched MeSH terms: Epilepsy/physiopathology
Automated seizure prediction

Acharya UR, Hagiwara Y, Adeli H

Epilepsy Behav, 2018 11;88:251-261.
PMID: 30317059 DOI: 10.1016/j.yebeh.2018.09.030

In the past two decades, significant advances have been made on automated electroencephalogram (EEG)-based diagnosis of epilepsy and seizure detection. A number of innovative algorithms have been introduced that can aid in epilepsy diagnosis with a high degree of accuracy. In recent years, the frontiers of computational epilepsy research have moved to seizure prediction, a more challenging problem. While antiepileptic medication can result in complete seizure freedom in many patients with epilepsy, up to one-third of patients living with epilepsy will have medically intractable epilepsy, where medications reduce seizure frequency but do not completely control seizures. If a seizure can be predicted prior to its clinical manifestation, then there is potential for abortive treatment to be given, either self-administered or via an implanted device administering medication or electrical stimulation. This will have a far-reaching impact on the treatment of epilepsy and patient's quality of life. This paper presents a state-of-the-art review of recent efforts and journal articles on seizure prediction. The technologies developed for epilepsy diagnosis and seizure detection are being adapted and extended for seizure prediction. The paper ends with some novel ideas for seizure prediction using the increasingly ubiquitous machine learning technology, particularly deep neural network machine learning.

Matched MeSH terms: Epilepsy/physiopathology
Incremental benefits of EEG informed fMRI in the study of disorders related to meso-corticolimbic dopamine pathway dysfunction: A systematic review of recent literature

Syed Nasser N, Ibrahim B, Sharifat H, Abdul Rashid A, Suppiah S

J Clin Neurosci, 2019 Jul;65:87-99.
PMID: 30955950 DOI: 10.1016/j.jocn.2019.03.054

Functional magnetic resonance imaging (fMRI) is a non-invasive imaging modality that enables the assessment of neural connectivity and oxygen utility of the brain using blood oxygen level dependent (BOLD) imaging sequence. Electroencephalography (EEG), on the other hands, looks at cortical electrical impulses of the brain thus detecting brainwave patterns during rest and thought processing. The combination of these two modalities is called fMRI with simultaneous EEG (fMRI-EEG), which has emerged as a new tool for experimental neuroscience assessments and has been applied clinically in many settings, most commonly in epilepsy cases. Recent advances in imaging has led to fMRI-EEG being utilized in behavioural studies which can help in giving an objective assessment of ambiguous cases and help in the assessment of response to treatment by providing a non-invasive biomarker of the disease processes. We aim to review the role and interpretation of fMRI-EEG in studies pertaining to psychiatric disorders and behavioral abnormalities.

Matched MeSH terms: Epilepsy/physiopathology
Fulltext Epileptic seizure detection: a comparative study between deep and traditional machine learning techniques

Sahu R, Dash SR, Cacha LA, Poznanski RR, Parida S

J Integr Neurosci, 2020 Mar 30;19(1):1-9.
PMID: 32259881 DOI: 10.31083/j.jin.2020.01.24

Electroencephalography is the recording of brain electrical activities that can be used to diagnose brain seizure disorders. By identifying brain activity patterns and their correspondence between symptoms and diseases, it is possible to give an accurate diagnosis and appropriate drug therapy to patients. This work aims to categorize electroencephalography signals on different channels' recordings for classifying and predicting epileptic seizures. The collection of the electroencephalography recordings contained in the dataset attributes 179 information and 11,500 instances. Instances are of five categories, where one is the symptoms of epilepsy seizure. We have used traditional, ensemble methods and deep machine learning techniques highlighting their performance for the epilepsy seizure detection task. One dimensional convolutional neural network, ensemble machine learning techniques like bagging, boosting (AdaBoost, gradient boosting, and XG boosting), and stacking is implemented. Traditional machine learning techniques such as decision tree, random forest, extra tree, ridge classifier, logistic regression, K-Nearest Neighbor, Naive Bayes (gaussian), and Kernel Support Vector Machine (polynomial, gaussian) are used for classifying and predicting epilepsy seizure. Before using ensemble and traditional techniques, we have preprocessed the data set using the Karl Pearson coefficient of correlation to eliminate irrelevant attributes. Further accuracy of classification and prediction of the classifiers are manipulated using k-fold cross-validation methods and represent the Receiver Operating Characteristic Area Under the Curve for each classifier. After sorting and comparing algorithms, we have found the convolutional neural network and extra tree bagging classifiers to have better performance than all other ensemble and traditional classifiers.

Matched MeSH terms: Epilepsy/physiopathology
48-hour video-EEG monitoring for epilepsy presurgical evaluation is cost-effective and safe in resource-limited setting

Lim KS, Fong SL, Thuy Le MA, Ahmad Bazir S, Narayanan V, Ismail N, et al.

Epilepsy Res, 2020 05;162:106298.
PMID: 32172144 DOI: 10.1016/j.eplepsyres.2020.106298

INTRODUCTION: Video-EEG monitoring is one of the key investigations in epilepsy pre-surgical evaluation but limited by cost. This study aimed to determine the efficacy and safety of a 48-hour (3-day) video EEG monitoring, with rapid pre-monitoring antiepileptic drugs withdrawal.
MATERIAL AND METHODS: This is a retrospective study of epilepsy cases with VEM performed in University Malaya Medical Center (UMMC), Kuala Lumpur, from January 2012 till August 2016.
RESULTS: A total of 137 cases were included. The mean age was 34.5 years old (range 15-62) and 76 (55.8 %) were male. On the first 24 -h of recording (D1), 81 cases (59.1 %) had seizure occurrence, and 109 (79.6 %) by day 2 (D2). One-hundred and nine VEMs (79.6 %) were diagnostic, in guiding surgical decision or further investigations. Of these, 21 had less than 2 seizures recorded in the first 48 h but were considered as diagnostic because of concordant interictal ± ictal activities, or a diagnosis such as psychogenic non-epileptic seizure was made. Twenty-eight patients had extension of VEM for another 24-48 h, and 11 developed seizures during the extension period. Extra-temporal lobe epilepsy and seizure frequency were significant predictors for diagnostic 48 -h VEM. Three patients developed complications, including status epilepticus required anaesthetic agents (1), seizure clusters (2) with postictal psychosis or dysphasia, and all recovered subsequently.
CONCLUSIONS: 48-h video EEG monitoring is cost-effective in resource limited setting.

Matched MeSH terms: Epilepsy/physiopathology
Role of Innate Immune Receptor TLR4 and its endogenous ligands in epileptogenesis

Paudel YN, Angelopoulou E, Akyuz E, Piperi C, Othman I, Shaikh MF

Pharmacol Res, 2020 10;160:105172.
PMID: 32871246 DOI: 10.1016/j.phrs.2020.105172

Understanding the interplay between the innate immune system, neuroinflammation, and epilepsy might offer a novel perspective in the quest of exploring new treatment strategies. Due to the complex pathology underlying epileptogenesis, no disease-modifying treatment is currently available that might prevent epilepsy after a plausible epileptogenic insult despite the advances in pre-clinical and clinical research. Neuroinflammation underlies the etiopathogenesis of epilepsy and convulsive disorders with Toll-like receptor (TLR) signal transduction being highly involved. Among TLR family members, TLR4 is an innate immune system receptor and lipopolysaccharide (LPS) sensor that has been reported to contribute to epileptogenesis by regulating neuronal excitability. Herein, we discuss available evidence on the role of TLR4 and its endogenous ligands, the high mobility group box 1 (HMGB1) protein, the heat shock proteins (HSPs) and the myeloid related protein 8 (MRP8), in epileptogenesis and post-traumatic epilepsy (PTE). Moreover, we provide an account of the promising findings of TLR4 modulation/inhibition in experimental animal models with therapeutic impact on seizures.

Matched MeSH terms: Epilepsy/physiopathology*

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