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Artificial neural network based epileptic detection using time-domain and frequency-domain features

Srinivasan V, Eswaran C, Sriraam N

J Med Syst, 2005 Dec;29(6):647-60.
PMID: 16235818

Electroencephalogram (EEG) signal plays an important role in the diagnosis of epilepsy. The long-term EEG recordings of an epileptic patient obtained from the ambulatory recording systems contain a large volume of EEG data. Detection of the epileptic activity requires a time consuming analysis of the entire length of the EEG data by an expert. The traditional methods of analysis being tedious, many automated diagnostic systems for epilepsy have emerged in recent years. This paper discusses an automated diagnostic method for epileptic detection using a special type of recurrent neural network known as Elman network. The experiments are carried out by using time-domain as well as frequency-domain features of the EEG signal. Experimental results show that Elman network yields epileptic detection accuracy rates as high as 99.6% with a single input feature which is better than the results obtained by using other types of neural networks with two and more input features.

Matched MeSH terms: Epilepsy/diagnosis*
Fulltext Successful epilepsy surgery for tuberous sclerosis complex evaluated by stereoelectroencephalography

Fong CY, Bleasel A, Dexter MA, Lawson JA, Wong CH

Epileptic Disord, 2020 Oct 01;22(5):633-641.
PMID: 33146141 DOI: 10.1684/epd.2020.1211

Evaluating the candidacy for epilepsy surgery in patients with tuberous sclerosis can be challenging, particularly when non-invasive investigations do not show a clear epileptogenic zone. Stereoencephalography may be useful in such cases. We present a case in which the primary epileptogenic tuber was successfully identified by stereoencephalography, which resulted in seizure freedom following epilepsy surgery. [Published with video sequences].

Matched MeSH terms: Epilepsy/diagnosis
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/diagnosis*
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/diagnosis
Malay public attitudes toward epilepsy (PATE) scale: translation and psychometric evaluation

Lim KS, Choo WY, Wu C, Tan CT

Epilepsy Behav, 2013 Nov;29(2):395-9.
PMID: 24090773 DOI: 10.1016/j.yebeh.2013.08.027

INTRODUCTION: None of the quantitative scales for public attitudes toward epilepsy had been translated to Malay language. This study aimed to translate and test the validity and reliability of a Malay version of the Public Attitudes Toward Epilepsy (PATE) scale.
METHOD: The translation was performed according to standard principles and tested in 140 Malay-speaking adults aged more than 18 years for psychometric validation.
RESULTS: The items in each domain had similar standard deviations (equal item variance), ranging from 0.90 to 1.00 in the personal domain and from 0.87 to 1.23 in the general domain. The correlation between an item and its domain was 0.4 and above for all items and was higher than the correlation with the other domain. Multitrait analysis showed that the Malay PATE had a similar variance, floor and ceiling effects, and relative relationship between the domains as the original PATE. The Malay PATE scale showed a similar correlation with almost all demographic variables except age. Item means were generally clustered in the factor analysis as the hypothesized domains, except those for items 1 and 2. The Cronbach's α values were within acceptable range (0.757 and 0.716 for the general and personal domains, respectively).
CONCLUSION: The Malay PATE scale is a validated and reliable translated version for measuring public attitudes toward epilepsy.

Matched MeSH terms: Epilepsy/diagnosis*
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/diagnosis
MR imaging of cerebral and cerebellar hypervascularity associated with status epilepticus: case report

Mukhtar AA, Ibrahim LS, Khairil AO

Nepal Med Coll J, 2007 Dec;9(4):289-91.
PMID: 18298025

A 20 year old male presented to the emergency department with generalized tonic clonic convulsions and up rolling of eye balls. He had history of seizure disorder for three years and on regular medical treatment and is compliant to medication. A non-contrast CT scan of the head was only done on 14th day of admission which showed hypodense areas in the right and left cerebellar hemisphere. MR imaging was performed four days later revealed high signal intensity in the both cerebellar hemispheres, both external capsules, both occipital and right parietal regions on fluid-attenuated inversion recovery (FLAIR). The post contrast MR imaging revealed diffuse cerebral and cerebellar hypervascularity in the similar region. This change of diffuse hypervascularity of both cerebral and cerebellar associated with seizure activity on post-contrast magnetic resonance imaging (MRI) has not been reported in any literature.

Matched MeSH terms: Epilepsy/diagnosis*
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/diagnosis*
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/diagnosis
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/diagnosis
Validation of Malay brief screening instrument for ascertainment of epilepsy

Fong SL, Lim KS, Tan L, Aris T, Khalid RA, Ali RA, et al.

Epilepsy Behav, 2019 08;97:206-211.
PMID: 31252280 DOI: 10.1016/j.yebeh.2019.05.033

INTRODUCTION: Prevalence studies of epilepsy in Asia revealed a prevalence ranging from 1.5 to 14.0 per 1000 among Asian populations. However, the prevalence of epilepsy in Malaysia is not available for comparison with other countries. This study aimed to translate and validate a Malay brief screening instruments for ascertainment of epilepsy.
METHOD: We translated into Malay a brief screening instrument for ascertainment of epilepsy designed and validated by Ottman et al., using the three-stage cross-cultural adaptation process developed by the International Quality of Life Assessment (IQOLA) project. We then administered the translated questionnaire via online survey to 162 cases (patients with epilepsy under follow-up care at the neurology clinic in University of Malaya Medical Centre, Kuala Lumpur) and 146 controls with no known history of epilepsy for validation.
RESULTS: Applying the most liberal definition for a positive screen, we obtained a sensitivity of 96.3% (95% confidence interval [CI]: 91.8-98.5%), with a specificity of 66.4% (95% CI: 58.1-73.0%) and positive predictive value (PPV) of 2.0%. The most stringent definition for a positive screen (only epilepsy) resulted in a sensitivity of 97.4% (95% CI: 62.0-72.6%), specificity of 98.6% (95% CI: 94.6-99.7%), and PPV of 26.6%. Narrowing the definition of a positive screen decreased sensitivity but improved PPVs. When compared to the original English questionnaire, the sensitivities were similar for all four definitions of a positive screen.
CONCLUSION: This is the first validated epilepsy screening questionnaire in the Malay language and represents a useful tool for the ascertainment of epilepsy in population-based studies.

Matched MeSH terms: Epilepsy/diagnosis*
SPTAN1 encephalopathy: distinct phenotypes and genotypes

Tohyama J, Nakashima M, Nabatame S, Gaik-Siew C, Miyata R, Rener-Primec Z, et al.

J Hum Genet, 2015 Apr;60(4):167-73.
PMID: 25631096 DOI: 10.1038/jhg.2015.5

Recent progress in genetic analysis reveals that a significant proportion of cryptogenic epileptic encephalopathies are single-gene disorders. Mutations in numerous genes for early-onset epileptic encephalopathies have been rapidly identified, including in SPTAN1, which encodes α-II spectrin. The aim of this review is to delineate SPTAN1 encephalopathy as a distinct clinical syndrome. To date, a total of seven epileptic patients with four different in-frame SPTAN1 mutations have been identified. The major clinical features of SPTAN1 mutations include epileptic encephalopathy with hypsarrhythmia, no visual attention, acquired microcephaly, spastic quadriplegia and severe intellectual disability. Brainstem and cerebellar atrophy and cerebral hypomyelination, as observed by magnetic resonance imaging, are specific hallmarks of this condition. A milder variant is characterized by generalized epilepsy with pontocerebellar atrophy. Only in-frame SPTAN1 mutations in the last two spectrin repeats in the C-terminal region lead to dominant negative effects and these specific phenotypes. The last two spectrin repeats are required for α/β spectrin heterodimer associations and the mutations can alter heterodimer formation between the two spectrins. From these data we suggest that SPTAN1 encephalopathy is a distinct clinical syndrome owing to specific SPTAN1 mutations. It is important that this syndrome is recognized by pediatric neurologists to enable proper diagnostic work-up for patients.

Matched MeSH terms: Epilepsy/diagnosis*
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/diagnosis*
Referral of epileptic patients in North East Coast of West Malaysia an area with poor MRI coverage: an analysis

Mohamed Y, Alias NN, Shuaib IL, Tharakan J, Abdullah J, Munawir AH, et al.

Southeast Asian J. Trop. Med. Public Health, 2006 Nov;37(6):1199-208.
PMID: 17333778

Advances in neuroimaging techniques, particularly Magnetic Resonance Imaging (MRI), have proved invaluable in detecting structural brain lesions in patients with epilepsy in developed countries. In Malaysia, a few electroencephalography facilities available in rural district hospitals run by trained physician assistants have Internet connections to a government neurological center in Kuala Lumpur. These facilities are more commonly available than MRI machines, which require radiological expertise and helium replacement, which may problematic in Southeast Asian countries where radiologists are found in mainly big cities or towns. We conducted a cross-sectional study over a two year period begining January 2001 on rural patients, correlating EEG reports and MRI images with a clinical diagnosis of epilepsy to set guidelines for which rural patients need to be referred to a hospital with MRI facilities. The patients referred by different hospitals without neurological services were classified as having generalized, partial or unclassified seizures based on the International Classification of Epileptic Seizures proposed by the International League Against Epilepsy (ILAE). The clinical parameters studied were seizure type, seizure frequency, status epilepticus and duration of seizure. EEG reports were reviewed for localized and generalized abnormalities and epileptiform changes. Statistical analysis was performed using logistic regression and area under the curve. The association between clinical and radiological abnormalities was evaluated for sensitivity and specificity. Twenty-six males and 18 females were evaluated. The mean age was 20.7 +/- 13.3 years. Nineteen (43.2%) had generalized seizures, 22 (50.0%) had partial seizures and 3 (6.8%) presented with unclassified seizures. The EEG was abnormal in 30 patients (20 with generalized abnormalities and 10 localized abnormalities). The MRI was abnormal in 17 patients (38.6%); the abnormalities observed were cerebral atrophy (5), hippocampal sclerosis (4), infarct/gliosis (3), cortical dysgenesis (2) and tumors (2). One patient had an arachnoid cyst in the right occipital region. Of the 17 patients with an abnormal MRI, 14 had an abnormal EEG, this difference was not statistically significant. There was no significant associaton between epileptographic changes and MRI findings (p = 0.078). EEG findings were associated with MRI findings (p = 0.004). The association between an abnormal EEG and an abnormal MRI had a specificity of 82.4%, while epileptogenic changes had a specificity of 64.7% in relation to abnormal MRI findings. This meants that those patients in rural hospitals with abnormal EEGs should be referred to a neurology center for further workup and an MRI to detect causes with an epileptic focus.

Matched MeSH terms: Epilepsy/diagnosis*
Ictal EEG Source Imaging for Presurgical Evaluation of Refractory Focal Epilepsy

Habib MA, Ibrahim F, Mohktar MS, Kamaruzzaman SB, Rahmat K, Lim KS

World Neurosurg, 2016 Apr;88:576-585.
PMID: 26548833 DOI: 10.1016/j.wneu.2015.10.096

BACKGROUND: Electroencephalography source imaging (ESI) is a promising tool for localizing the cortical sources of both ictal and interictal epileptic activities. Many studies have shown the clinical usefulness of interictal ESI, but very few have investigated the utility of ictal ESI. The aim of this article is to examine the clinical usefulness of ictal ESI for epileptic focus localization in patients with refractory focal epilepsy, especially extratemporal lobe epilepsy.
METHODS: Both ictal and interictal ESI were performed by the use of patient-specific realistic forward models and 3 different linear distributed inverse models. Lateralization as well as concordance between ESI-estimated focuses and single-photon emission computed tomography (SPECT) focuses were assessed.
RESULTS: All the ESI focuses (both ictal and interictal) were found lateralized to the same hemisphere as ictal SPECT focuses. Lateralization results also were in agreement with the lesion sides as visualized on magnetic resonance imaging. Ictal ESI results, obtained from the best-performing inverse model, were fully concordant with the same cortical lobe as SPECT focuses, whereas the corresponding concordance rate is 87.50% in case of interictal ESI.
CONCLUSIONS: Our findings show that ictal ESI gives fully lateralized and highly concordant results with ictal SPECT and may provide a cost-effective substitute for ictal SPECT.

Matched MeSH terms: Drug Resistant Epilepsy/diagnosis*
Video-EEG telemetry: apparent manifestation of both epileptic and non-epileptic attacks causing potential diagnostic pitfalls

Raymond AA, Gilmore WV, Scott CA, Fish DR, Smith SJ

Epileptic Disord, 1999 Jun;1(2):101-6.
PMID: 10937139

Video-EEG telemetry is often used to support the diagnosis of non-epileptic seizures (NES). Although rare, some patients may have both epileptic seizures (ES) and NES. It is crucially important to identify such patients to avoid the hazards of inappropriate anticonvulsant withdrawal. To delineate the electroclinical characteristics and diagnostic problems in this group of patients, we studied the clinical, EEG and MRI features of 14 consecutive patients in whom separate attacks, considered to be both NES and ES were recorded using video-EEG telemetry. Only two patients were drug-reduced during the telemetry. Most patients had their first seizure (ES or NES) in childhood (median age 7 years; range: 6 months-24 years); 8/14 patients were female. Brain MRI was abnormal in 10/14 patients. Interictal EEG abnormalities were present in all patients; 13/14 had epileptiform and 1/14 only background abnormalities. Over 70 seizures were recorded in these 14 patients: in 12/14 patients, the first recorded seizure was a NES (p < 0.001), and 7 of these patients had at least one more NES before an ES was recorded. Only 3/14 patients had more than 5 NES before an ES was recorded. Recording a small number of apparently NES in an individual by no means precludes the possibility of additional epilepsy. Particular care should be taken, and multiple (> 5) seizure recording may be advisable, in patients with a young age of seizure onset, interictal EEG abnormalities, or a clear, potential aetiology for epilepsy.

Matched MeSH terms: Epilepsy/diagnosis*
Detection of copy number variations in epilepsy using exome data

Tsuchida N, Nakashima M, Kato M, Heyman E, Inui T, Haginoya K, et al.

Clin Genet, 2018 03;93(3):577-587.
PMID: 28940419 DOI: 10.1111/cge.13144

Epilepsies are common neurological disorders and genetic factors contribute to their pathogenesis. Copy number variations (CNVs) are increasingly recognized as an important etiology of many human diseases including epilepsy. Whole-exome sequencing (WES) is becoming a standard tool for detecting pathogenic mutations and has recently been applied to detecting CNVs. Here, we analyzed 294 families with epilepsy using WES, and focused on 168 families with no causative single nucleotide variants in known epilepsy-associated genes to further validate CNVs using 2 different CNV detection tools using WES data. We confirmed 18 pathogenic CNVs, and 2 deletions and 2 duplications at chr15q11.2 of clinically unknown significance. Of note, we were able to identify small CNVs less than 10 kb in size, which might be difficult to detect by conventional microarray. We revealed 2 cases with pathogenic CNVs that one of the 2 CNV detection tools failed to find, suggesting that using different CNV tools is recommended to increase diagnostic yield. Considering a relatively high discovery rate of CNVs (18 out of 168 families, 10.7%) and successful detection of CNV with <10 kb in size, CNV detection by WES may be able to surrogate, or at least complement, conventional microarray analysis.

Matched MeSH terms: Epilepsy/diagnosis
Potential anti-epileptic phytoconstituents: An updated review

Kaur J, Famta P, Famta M, Mehta M, Satija S, Sharma N, et al.

J Ethnopharmacol, 2021 Mar 25;268:113565.
PMID: 33166627 DOI: 10.1016/j.jep.2020.113565

ETHNOPHARMACOLOGICAL RELEVANCE: Epilepsy is one of the most commonly occurring non-communicable neurological disorder that affects people of all age groups. Around 50 million people globally are epileptic, with 80% cases in developing countries due to lack of access to treatments determined by high cost and poor availability or it can be defined by the fraction of active epileptic patients who are not appropriately being treated. The availability of antiepileptic drugs and their adjuvant therapy in such countries is less than 50% and these are highly susceptible to drug interactions and severe adverse effects. As a result, the use of herbal medicine is increasingly becoming popular.
AIM OF THE STUDY: To provide pharmacological information on the active constituents evaluated in the preclinical study to treat epilepsy with potential to be used as an alternative therapeutic option in future. It also provides affirmation for the development of novel antiepileptic drugs derived from medicinal plants.
MATERIALS AND METHODS: Relevant information on the antiepileptic potential of phytoconstituents in the preclinical study (in-vitro, in-vivo) is provided based on their effect on screening parameters. Besides, relevant information on pharmacology of phytoconstituents, the traditional use of their medicinal plants related to epilepsy and status of phytoconstituents in the clinical study were derived from online databases, including PubMed, Clinicaltrial. gov, The Plant List (TPL, www.theplantlist.org), Science Direct. Articles identified using preset searching syntax and inclusion criteria are presented.
RESULTS: More than 70% of the phytoconstituents reviewed in this paper justified the traditional use of their medicinal plant related to epilepsy by primarily acting on the GABAergic system. Amongst the phytoconstituents, only cannabidiol and tetrahydrocannabinol have been explored for clinical application in epilepsy.
CONCLUSION: The preclinical and clinical data of the phytoconstituents to treat epilepsy and its associated comorbidities provides evidence for the discovery and development of novel antiepileptic drugs from medicinal plants. In terms of efficacy and safety, further randomized and controlled clinical studies are required to understand the complete pharmacodynamic and pharmacokinetic picture of phytoconstituents. Also, specific botanical source evaluation is needed.

Matched MeSH terms: Epilepsy/diagnosis
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/diagnosis*
GRIN2D variants in three cases of developmental and epileptic encephalopathy

Tsuchida N, Hamada K, Shiina M, Kato M, Kobayashi Y, Tohyama J, et al.

Clin Genet, 2018 12;94(6):538-547.
PMID: 30280376 DOI: 10.1111/cge.13454

N-methyl-d-aspartate (NMDA) receptors are glutamate-activated ion channels that are widely distributed in the central nervous system and essential for brain development and function. Dysfunction of NMDA receptors has been associated with various neurodevelopmental disorders. Recently, a de novo recurrent GRIN2D missense variant was found in two unrelated patients with developmental and epileptic encephalopathy. In this study, we identified by whole exome sequencing novel heterozygous GRIN2D missense variants in three unrelated patients with severe developmental delay and intractable epilepsy. All altered residues were highly conserved across vertebrates and among the four GluN2 subunits. Structural consideration indicated that all three variants are probably to impair GluN2D function, either by affecting intersubunit interaction or altering channel gating activity. We assessed the clinical features of our three cases and compared them to those of the two previously reported GRIN2D variant cases, and found that they all show similar clinical features. This study provides further evidence of GRIN2D variants being causal for epilepsy. Genetic diagnosis for GluN2-related disorders may be clinically useful when considering drug therapy targeting NMDA receptors.

Matched MeSH terms: Epilepsy/diagnosis*

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