Epilepsia partialis continua: A review.

Epilepsia partialis continua (EPC) is a rare type of focal motor seizure characterized by continuous, involuntary muscle contractions in a specific part of the body. These contractions usually involve rhythmic, twitching movements and can last for several hours to days. The seizures are usually limited to one part of the body and can be clonic or dystonic. EPC can affect people of all ages but is more common in children and adolescents. The pathophysiology of EPC is complex and depends on the cause. There are several possible causes of EPC including structural brain abnormalities, infections, metabolic and genetic disorders, inflammatory conditions, traumatic brain injury, and vascular causes. The work-up of EPC includes electroencephalography (EEG), magnetic resonance imaging (MRI) of the brain, position emission tomography (PET) scan of the brain, autoimmune antibodies, infection work-up, and metabolic and genetic work-up. The management of EPC can be challenging. Antiseizure medications (ASDs) including benzodiazepines are an integral part of the management of EPC. Immunotherapy trials are recommended in resistant cases. Epilepsy surgery is one of the effective modalities in some surgically amenable cases. This article reviews the topic of EPC and summarizes diagnostic and .treatment recommendations.

Unrecognized Focal Nonmotor Seizures in Adolescents Presenting to Emergency Departments.

BACKGROUND AND OBJECTIVES: Many adolescents with undiagnosed focal epilepsy seek evaluation in emergency departments (EDs). Accurate history-taking is essential to prompt diagnosis and treatment. In this study, we investigated ED recognition of motor vs nonmotor seizures and its effect on management and treatment of focal epilepsy in adolescents. METHODS: This was a retrospective analysis of enrollment data from the Human Epilepsy Project (HEP), an international multi-institutional study that collected data from 34 sites between 2012 and 2017. Participants were 12 years or older, neurotypical, and within 4 months of treatment initiation for focal epilepsy. We used HEP enrollment medical records to review participants' initial diagnosis and management. RESULTS: A total of 83 adolescents were enrolled between 12 and 18 years. Fifty-eight (70%) presented to an ED before diagnosis of epilepsy. Although most ED presentations were for motor seizures (n = 52; 90%), many patients had a history of nonmotor seizures (20/52 or 38%). Adolescents with initial nonmotor seizures were less likely to present to EDs (26/44 or 59% vs 32/39 or 82%, p = 0.02), and nonmotor seizures were less likely to be correctly identified (2/6 or 33% vs 42/52 or 81%, p = 0.008). A history of initial nonmotor seizures was not recognized in any adolescent who presented for a first-lifetime motor seizure. As a result, initiation of treatment and admission from the ED was not more likely for these adolescents who met the definition of epilepsy compared with those with no seizure history. This lack of nonmotor seizure history recognition in the ED was greater than that observed in the adult group (0% vs 23%, p = 0.03) and occurred in both pediatric and nonpediatric ED settings. DISCUSSION: Our study supports growing evidence that nonmotor seizures are often undiagnosed, with many individuals coming to attention only after conversion to motor seizures. We found this treatment gap is exacerbated in the adolescent population. Our study highlights a critical need for physicians to inquire about the symptoms of nonmotor seizures, even when the presenting seizure is motor. Future interventions should focus on improving nonmotor seizure recognition for this population in EDs.

Stereoelectroencephalography-guided radiofrequency thermocoagulation of the epileptogenic zone: a potential treatment and prognostic indicator for subsequent excision surgery.

PURPOSE: To evaluate the safety and efficacy of stereoelectroencephalography (SEEG)-guided radiofrequency thermocoagulation (RFTC) for drug-resistant focal epilepsy and investigate the relationship between post-RFTC remission duration and delayed excision surgery effectiveness. METHODS: We conducted a retrospective analysis of 43 patients with drug-resistant focal epilepsy who underwent RFTC via SEEG electrodes. After excluding three, the remaining 40 were classified into subgroups based on procedures and outcomes. Twenty-four patients (60%) underwent a secondary excision surgery. We determined the predictive value of RFTC outcome upon subsequent surgical outcome by categorizing the delayed secondary surgery outcome as success (Engel I/II) versus failure (Engel III/IV). Demographic information, epilepsy characteristics, and the duration of seizure freedom after RFTC were assessed. RESULTS: Among 40 patients, 20% achieved Engel class I with RFTC alone, while 24 underwent delayed secondary excision surgery. Overall, 41.7% attained Engel class I, with a 66.7% success rate combining RFTC with delayed surgery. Seizure freedom duration was significantly longer in the success group (mean 4.9 months, SD = 2.7) versus the failure group (mean 1.9 months, SD = 1.1; P = 0.007). A higher proportion of RFTC-only and delayed surgical success group patients had preoperative lesional findings (p = 0.01), correlating with a longer time to seizure recurrence (p < 0.05). Transient postoperative complications occurred in 10%, resolving within a year. CONCLUSION: This study demonstrates that SEEG-guided RFTC is a safe and potential treatment option for patients with drug-resistant focal epilepsy. A prolonged duration of seizure freedom following RFTC may serve as a predictive marker for the success of subsequent excision surgery.

Intraoperative changes in large-scale thalamic circuitry following laser ablation of hypothalamic hamartomas.

BACKGROUND AND OBJECTIVES: Gelastic seizures due to hypothalamic hamartomas (HH) are challenging to treat, in part due to an incomplete understanding of seizure propagation pathways. Although magnetic resonance imaging-guided laser interstitial thermal therapy (MRgLITT) is a promising intervention to disconnect HH from ictal propagation networks, the optimal site of ablation to achieve seizure freedom is not known. In this study, we investigated intraoperative post-ablation changes in resting-state functional connectivity to identify large-scale networks associated with successful disconnection of HH. METHODS: Children who underwent MRgLITT for HH at two institutions were consecutively recruited and followed for a minimum of one year. Seizure freedom was defined as Engel score of 1A at the last available follow-up. Immediate pre- and post- ablation resting-state functional MRI scans were acquired while maintaining a constant depth of general anesthetic. Multivariable generalized linear models were used to identify intraoperative changes in large-scale connectivity associated with seizure outcomes. RESULTS: Twelve patients underwent MRgLITT for HH, five of whom were seizure-free at their last follow-up. Intraprocedural changes in thalamocortical circuitry involving the anterior cingulate cortex were associated with seizure-freedom. Children who were seizure-free demonstrated an increase and decrease in connectivity to the pregenual and dorsal anterior cingulate cortices, respectively. In addition, children who became seizure-free demonstrated increased thalamic connectivity to the periaqueductal gray immediately following MRgLITT. DISCUSSION: Successful disconnection of HH is associated with intraoperative, large-scale changes in thalamocortical connectivity. These changes provide novel insights into the large-scale basis of gelastic seizures and may represent intraoperative biomarkers of treatment success.

Attention-based deep convolutional neural network for classification of generalized and focal epileptic seizures.

Epilepsy affects over 50 million people globally. Electroencephalography is critical for epilepsy diagnosis, but manual seizure classification is time-consuming and requires extensive expertise. This paper presents an automated multi-class seizure classification model using EEG signals from the Temple University Hospital Seizure Corpus ver. 1.5.2. 11 features including time-based correlation, time-based eigenvalues, power spectral density, frequency-based correlation, frequency-based eigenvalues, sample entropy, spectral entropy, logarithmic sum, standard deviation, absolute mean, and ratio of Daubechies D4 wavelet transformed coefficients were extracted from 10-second sliding windows across channels. The model combines multi-head self-attention mechanism with a deep convolutional neural network (CNN) to classify seven subtypes of generalized and focal epileptic seizures. The model achieved 0.921 weighted accuracy and 0.902 weighted F1 score in classifying focal onset non-motor, generalized onset non-motor, simple partial, complex partial, absence, tonic, and tonic-clonic seizures. In comparison, a CNN model without multi-head attention achieved 0.767 weighted accuracy. Ablation studies were conducted to validate the importance of transformer encoders and attention. The promising classification results demonstrate the potential of deep learning for handling EEG complexity and improving epilepsy diagnosis. This seizure classification model could enable timely interventions when translated into clinical practice.

Construction and validation of an algorithm to separate focal and generalised epilepsy using clinical variables: A comparison of machine learning approaches.

PURPOSE: Epilepsy type, whether focal or generalised, is important in deciding anti-seizure medication (ASM). In resource-limited settings, investigations are usually not available, so a clinical separation is required. We used a naïve Bayes approach to devise an algorithm to do this, and compared its accuracy with algorithms devised by five other machine learning methods. METHODS: We used data on 28 clinical variables from 503 patients attending an epilepsy clinic in India with defined epilepsy type, as determined by an epileptologist with access to clinical, imaging, and EEG data. We adopted a machine learning approach to select the most relevant variables based on mutual information, to train the model on part of the data, and then to evaluate it on the remaining data (testing set). We used a naïve Bayes approach and compared the results in the testing set with those obtained by several other machine learning algorithms by measuring sensitivity, specificity, accuracy, area under the curve, and Cohen's kappa. RESULTS: The six machine learning methods produced broadly similar results. The best naïve Bayes algorithm contained eleven variables, and its accuracy was 92.2% in determining epilepsy type (sensitivity 92.0%, specificity 92.7%). An algorithm incorporating the best eight of these variables was only slightly less accurate - 91.0% (sensitivity 89.6%, and specificity 95.1%) - and easier for clinicians to use. CONCLUSION: A clinical algorithm with eight variables is effective and accurate at separating focal from generalised epilepsy. It should be useful in resource-limited settings, by epilepsy-inexperienced doctors, to help determine epilepsy type and therefore optimal ASMs for individual patients, without the need for EEG or neuroimaging.

Using scalp EEG to predict seizure recurrence and electrical status epilepticus in children with idiopathic focal epilepsy.

PURPOSE: Some individuals with idiopathic focal epilepsy (IFE) experience recurring seizures accompanied by the evolution of electrical status epilepticus during sleep (ESES). Here, we aimed to develop a predictor for the early detection of seizure recurrence with ESES in children with IFE using resting state electroencephalogram (EEG) data. METHODS: The study group included 15 IFE patients who developed seizure recurrence with ESES. There were 17 children in the control group who did not experience seizure recurrence with ESES during at least 2-year follow-up. We used the degree value of the partial directed coherence (PDC) from the EEG data to predict seizure recurrence with ESES via 6 machine learning (ML) algorithms. RESULTS: Among the models, the Xgboost Classifier (XGBC) model achieved the highest specificity of 0.90, and a remarkable sensitivity and accuracy of 0.80 and 0.85, respectively. The CATC showed balanced performance with a specificity of 0.85, sensitivity of 0.73, and an accuracy of 0.80, with an AUC equal to 0.78. For both of these models, F4, Fz and T4 were the overlaps of the top 4 features. CONCLUSIONS: Considering its high classification accuracy, the XGBC model is an effective and quantitative tool for predicting seizure recurrence with ESES evolution in IFE patients. We developed an ML-based tool for predicting the development of IFE using resting state EEG data. This could facilitate the diagnosis and treatment of patients with IFE.

Feasibility study of microburst VNS therapy in drug-resistant focal and generalized epilepsy.

BACKGROUND: Vagus nerve stimulation (VNS) at low frequencies (≤30 Hz) has been an established treatment for drug-resistant epilepsy (DRE) for over 25 years. OBJECTIVE: To examine the initial safety and efficacy performance of an investigational, high-frequency (≥250 Hz) VNS paradigm herein called "Microburst VNS" (µVNS). µVNS consists of short, high-frequency bursts of electrical pulses believed to preferentially modulate certain brain regions. METHODS: Thirty-three (33) participants were enrolled into an exploratory feasibility study, 21 with focal-onset seizures and 12 with generalized-onset seizures. Participants were titrated to a personalized target dose of µVNS using an investigational fMRI protocol. Participants were then followed for up to 12 months, with visits every 3 months, and monitored for side-effects at all time points. This study was registered as NCT03446664 on February 27th, 2018. RESULTS: The device was well-tolerated. Reported adverse events were consistent with typical low frequency VNS outcomes and tended to diminish in severity over time, including dysphonia, cough, dyspnea, and implant site pain. After 12 months of µVNS, the mean seizure frequency reduction for all seizures was 61.3% (median reduction: 70.4%; 90% CI of median: 48.9%-83.3%). The 12-month responder rate (≥50% reduction) was 63.3% (90% CI: 46.7%-77.9%) and the super-responder rate (≥80% reduction) was 40% (90% CI: 25.0%-56.6%). Participants with focal-onset seizures appeared to benefit similarly to participants with generalized-onset seizures (mean reduction in seizures at 12 months: 62.6% focal [n = 19], versus 59.0% generalized [n = 11]). CONCLUSION: Overall, µVNS appears to be safe and potentially a promising therapeutic alternative to traditional VNS. It merits further investigation in randomized controlled trials which will help determine the impact of investigational variables and which patients are most suitable for this novel therapy.

Specific consistency score for rational selection of epilepsy resection surgery candidates.

OBJECTIVE: Degree of indication for epilepsy surgery is determined by taking multiple factors into account. This study aimed to investigate the usefulness of the Specific Consistency Score (SCS), a proposed score for focal epilepsy to rate the indication for epilepsy focal resection. METHODS: This retrospective cohort study included patients considered for resective epilepsy surgery in Kyoto University Hospital from 2011 to 2022. Plausible epileptic focus was tentatively defined. Cardinal findings were scored based on specificity and consistency with the estimated laterality and lobe. The total points represented SCS. The association between SCS and the following clinical parameters was assessed by univariate and multivariate analysis: (1) probability of undergoing resective epilepsy surgery, (2) good postoperative seizure outcome (Engel I and II or Engel I only), and (3) lobar concordance between the noninvasively estimated focus and intracranial electroencephalographic (EEG) recordings. RESULTS: A total of 131 patients were evaluated. Univariate analysis revealed higher SCS in the (1) epilepsy surgery group (8.4 [95% confidence interval (CI) = 7.8-8.9] vs. 4.9 [95% CI = 4.3-5.5] points; p < .001), (2) good postoperative seizure outcome group (Engel I and II; 8.7 [95% CI = 8.2-9.3] vs. 6.4 [95% CI = 4.5-8.3] points; p = .008), and (3) patients whose focus defined by intracranial EEG matched the noninvasively estimated focus (8.3 [95% CI = 7.3-9.2] vs. 5.4 [95% CI = 3.5-7.3] points; p = .004). Multivariate analysis revealed areas under the curve of .843, .825, and .881 for Parameters 1, 2, and 3, respectively. SIGNIFICANCE: SCS provides a reliable index of good indication for resective epilepsy surgery and can be easily available in many institutions not necessarily specializing in epilepsy.

Functional brain connectivity in children with focal epilepsy: A systematic review of functional MRI studies.

Epilepsy is increasingly recognised as a brain network disorder and many studies have investigated functional connectivity (FC) in children with epilepsy using functional MRI (fMRI). This systematic review of fMRI studies, published up to November 2023, investigated profiles of FC changes and their clinical relevance in children with focal epilepsy compared to healthy controls. A literature search in PubMed and Web of Science yielded 62 articles. We categorised the results into three groups: 1) differences in correlation-based FC between patients and controls; 2) differences in other FC measures between patients and controls; and 3) associations between FC and disease variables (for example, age of onset), cognitive and seizure outcomes. Studies revealed either increased or decreased FC across multiple brain regions in children with focal epilepsy. However, findings lacked consistency: conflicting FC alterations (decreased and increased FC) co-existed within or between brain regions across all focal epilepsy groups. The studies demonstrated overall that 1) interhemispheric connections often displayed abnormal connectivity and 2) connectivity within and between canonical functional networks was decreased, particularly for the default mode network. Focal epilepsy disrupted FC in children both locally (e.g., seizure-onset zones, or within-brain subnetworks) and globally (e.g., whole-brain network architecture). The wide variety of FC study methodologies limits clinical application of the results. Future research should employ longitudinal designs to understand the evolution of brain networks during the disease course and explore the potential of FC biomarkers for predicting cognitive and postsurgical seizure outcomes.

Ictal Central Apnea Is Predictive of Mesial Temporal Seizure Onset: An Intracranial Investigation.

OBJECTIVE: Ictal central apnea (ICA) is a semiological sign of focal epilepsy, associated with temporal and frontal lobe seizures. In this study, using qualitative and quantitative approaches, we aimed to assess the localizational value of ICA. We also aimed to compare ICA clinical utility in relation to other seizure semiological features of focal epilepsy. METHODS: We analyzed seizures in patients with medically refractory focal epilepsy undergoing intracranial stereotactic electroencephalographic (SEEG) evaluations with simultaneous multimodal cardiorespiratory monitoring. A total of 179 seizures in 72 patients with reliable artifact-free respiratory signal were analyzed. RESULTS: ICA was seen in 55 of 179 (30.7%) seizures. Presence of ICA predicted a mesial temporal seizure onset compared to those without ICA (odds ratio = 3.8, 95% confidence interval = 1.3-11.6, p = 0.01). ICA specificity was 0.82. ICA onset was correlated with increased high-frequency broadband gamma (60-150Hz) activity in specific mesial or basal temporal regions, including amygdala, hippocampus, and fusiform and lingual gyri. Based on our results, ICA has an almost 4-fold greater association with mesial temporal seizure onset zones compared to those without ICA and is highly specific for mesial temporal seizure onset zones. As evidence of symptomatogenic areas, onset-synchronous increase in high gamma activity in mesial or basal temporal structures was seen in early onset ICA, likely representing anatomical substrates for ICA generation. INTERPRETATION: ICA recognition may help anatomoelectroclinical localization of clinical seizure onset to specific mesial and basal temporal brain regions, and the inclusion of these regions in SEEG evaluations may help accurately pinpoint seizure onset zones for resection. ANN NEUROL 2024;95:998-1008.

Clinical characteristics, seizure control, and delivery outcomes in pregnant women with focal and generalized epilepsies.

OBJECTIVE: To prospectively investigate the course of epilepsy and assess seizure control during pregnancy in women with focal epilepsy (FE) compared with generalized epilepsy (GE), to ascertain the effects of epilepsy and its types on delivery and neonatal outcomes, and to compare adverse outcomes between pregnancies complicated by epilepsy and normal pregnancies. METHODS: 124 pregnant women with epilepsy (WWE) were enrolled in a prospective study. Obstetric and neonatal outcomes were compared with those of 277 healthy women in the control group. RESULTS: Occurrence of seizures during pregnancy was more often in FE (77.1 %) compared with GE (50.0 %) (Odds ratio [OR] 2.08; 95 % confidence interval [CI] 0.97-4.46, p = 0.06); the overall seizure freedom was significantly higher in women with GE compared with women with FE (p = 0.0038). Poor seizure control one year prior to the pregnancy and nonadherence to treatment were significantly associated with presence of seizures during pregnancy (p < 0.0001). Compared with pregnancies of women without epilepsy, WWE were at increased risk of cesarean section (CS) (p < 0.0001) and preterm birth (p = 0.03). Offspring of mothers with epilepsy were at higher risks of Apgar scores at 5 min ≤7 (p < 0.0001) and perinatal hypoxia (p = 0.03) compared with infants of unaffected women. Seizures during pregnancy were significantly correlated with the higher rate of CS, Apgar scores at 5 min ≤7, and perinatal hypoxia (p = 0.0069; p = 0.0098; and p = 0.0045, respectively). The risks of adverse outcomes were not significantly increased in women with FE compared to women with GE. CONCLUSION: Epileptic seizures in pregnancy are associated with increased risks of adverse delivery and neonatal outcomes. Hence, early assessment of seizure disorder, adequate seizure control prior to and during pregnancy, and effective treatment are required to prevent potential seizure-related complications and improve maternal and fetal outcomes.

Epilepsy with eyelid myoclonia (Jeavons syndrome): Generalized, focal, or combined generalized and focal epilepsy syndrome?

Epilepsy with eyelid myoclonia (EM) or Jeavons syndrome (JS) is an epileptic syndrome related to the spectrum of genetic generalized epilepsies (GGE). We report two untreated children on which EEGs were performed several hours after a generalized tonic-clonic seizure (GTCS). These showed a unilateral, nearly continuous posterior slowing. This slow-wave activity was associated with contralateral epileptiform activity in one case, while in the second case, it was associated with an ipsilateral activity. However, in the latter child, a few months later an independent focus on the contralateral side was observed. A diagnosis of focal occipital lobe epilepsy was proposed in both cases, and one child underwent a left occipital lobectomy at 3.5 years of age. Despite surgery, absences with EM persisted in this child, and a marked photosensitivity to photic stimulation was observed two years later. The focal slow wave activity of one occipital lobe several hours after a GTCS in these two subjects was in favor of a focal onset preceding the generalization. The EEG evidence for independent left and right posterior focus in these two cases, the persistence of EM, and the development of a marked photosensitivity to photic stimulation in the child who underwent an occipital lobectomy, allow us to suggest that JS is associated with a network of bi-occipital hyperexcitability that rapidly engages bilaterally to produce generalized seizures.

Longitudinal evolution of electroencephalogram (EEG): Findings over five years of follow-up in children with Zika-related microcephaly from the Microcephaly Epidemic Research Group Pediatric Cohort (2015-2020).

OBJECTIVE: To assess the longitudinal evolution of EEG findings in children with Zika related-microcephaly (ZRM) and to evaluate the associations of these patterns with the children's clinical and neuroimaging characteristics. METHODS: As part of the follow-up of the Microcephaly Epidemic Research Group Pediatric Cohort (MERG-PC) in Recife, Brazil, we performed serial EEG recordings in a subgroup of children with ZRM to evaluate changes in background rhythms and epileptiform activity (EA). Latent class analysis was used to identify patterns in the evolution of EA over time; clinical and neuroimaging findings were compared across the identified groups. RESULTS: Out of the 72 children with ZRM who were evaluated during 190 EEGs/videoEEGs, all participants presented with abnormal background activity, 37.5% presented with an alpha-theta rhythmic activity, and 25% presented with sleep spindles, which were less commonly observed in children with epilepsy. EA changed over time in 79.2% of children, and three distinct trajectories were identified: (i) multifocal EA over time, (ii) no discharges/focal EA evolving to focal/multifocal EA, and (iii) focal/multifocal EA evolving to epileptic encephalopathy patterns (e.g., hypsarrhythmia or continuous EA in sleep). The multifocal EA over time trajectory was associated with periventricular and thalamus/basal ganglia calcifications, brainstem and corpus callosum atrophy and had less focal epilepsy, whereas the children in the trajectory which evolved to epileptic encephalopathy patterns had more frequently focal epilepsy. SIGNIFICANCE: These findings suggest that, in most children with ZRM, trajectories of changes in EA can be identified and associated with neuroimaging and clinical features.

A neuromorphic spiking neural network detects epileptic high frequency oscillations in the scalp EEG.

Interictal High Frequency Oscillations (HFO) are measurable in scalp EEG. This development has aroused interest in investigating their potential as biomarkers of epileptogenesis, seizure propensity, disease severity, and treatment response. The demand for therapy monitoring in epilepsy has kindled interest in compact wearable electronic devices for long-term EEG recording. Spiking neural networks (SNN) have emerged as optimal architectures for embedding in compact low-power signal processing hardware. We analyzed 20 scalp EEG recordings from 11 pediatric focal lesional epilepsy patients. We designed a custom SNN to detect events of interest (EoI) in the 80-250 Hz ripple band and reject artifacts in the 500-900 Hz band. We identified the optimal SNN parameters to detect EoI and reject artifacts automatically. The occurrence of HFO thus detected was associated with active epilepsy with 80% accuracy. The HFO rate mirrored the decrease in seizure frequency in 8 patients (p = 0.0047). Overall, the HFO rate correlated with seizure frequency (rho = 0.90 CI [0.75 0.96], p < 0.0001, Spearman's correlation). The fully automated SNN detected clinically relevant HFO in the scalp EEG. This study is a further step towards non-invasive epilepsy monitoring with a low-power wearable device.

Intracerebral electrical stimulation of the right anterior fusiform gyrus impairs human face identity recognition.

Brain regions located between the right fusiform face area (FFA) in the middle fusiform gyrus and the temporal pole may play a critical role in human face identity recognition but their investigation is limited by a large signal drop-out in functional magnetic resonance imaging (fMRI). Here we report an original case who is suddenly unable to recognize the identity of faces when electrically stimulated on a focal location inside this intermediate region of the right anterior fusiform gyrus. The reliable transient identity recognition deficit occurs without any change of percept, even during nonverbal face tasks (i.e., pointing out the famous face picture among three options; matching pictures of unfamiliar or familiar faces for their identities), and without difficulty at recognizing visual objects or famous written names. The effective contact is associated with the largest frequency-tagged electrophysiological signals of face-selectivity and of familiar and unfamiliar face identity recognition. This extensive multimodal investigation points to the right anterior fusiform gyrus as a critical hub of the human cortical face network, between posterior ventral occipito-temporal face-selective regions directly connected to low-level visual cortex, the medial temporal lobe involved in generic memory encoding, and ventral anterior temporal lobe regions holding semantic associations to people's identity.

Spatio-temporal spike dynamics predict surgical outcome in adult focal epilepsy.

OBJECTIVE: We hypothesized that spatio-temporal dynamics of interictal spikes reflect the extent and stability of epileptic sources and determine surgical outcome. METHODS: We studied 30 consecutive patients (14 good outcome). Spikes were detected in prolonged stereo-electroencephalography recordings. We quantified the spatio-temporal dynamics of spikes using the variance of the spike rate, line length and skewness of the spike distribution, and related these features to outcome. We built a logistic regression model, and compared its performance to traditional markers. RESULTS: Good outcome patients had more dominant and stable sources than poor outcome patients as expressed by a higher variance of spike rates, a lower variance of line length, and a lower variance of positive skewness (ps < 0.05). The outcome was correctly predicted in 80% of patients. This was better or non-inferior to predictions based on a focal lesion (p = 0.016), focal seizure-onset zone, or complete resection (ps > 0.05). In the five patients where traditional markers failed, spike distribution predicted the outcome correctly. The best results were achieved by 18-h periods or longer. CONCLUSIONS: Analysis of spike dynamics shows that surgery outcome depends on strong, single and stable sources. SIGNIFICANCE: Our quantitative method has the potential to be a reliable predictor of surgical outcome.

A splicing variation in NPRL2 causing familial focal epilepsy with variable foci: additional cases and literature review.

NPRL2 (nitrogen permease regulator like 2) is a component of the GATOR1(GAP activity towards rags complex 1) proteins, which is an inhibitor of the amino acid-sensing branch of the mTORC1 pathway. GATOR1 complex variations were reported to correlate with familial focal epilepsy with variable foci (FFEVF). However, FFEVF caused by NPRL2 variants has not been widely explored. Here, we describe a variant, 339+2T>C, in NPRL2 identified by trio whole-exome sequencing (WES) in a family. This splicing variant that occurred at the 5' end of exon 3 was confirmed by minigene assays, which affected alternative splicing and led to exon 3 skipping in NPRL2. Our cases presented multiple seizure types (febrile seizures, infantile spasms, focal seizures, or focal to generalized tonic-clonic seizures). Electroencephalogram (EEG) showed frequent discharges in the left frontal and central regions. A favorable prognosis was achieved in response to vitamin B6 and topiramate when the patient was seven months old. Our study expands the phenotype and genotype spectrum of FFEVF and provides solid diagnostic evidence for FFEVF.

Determinants of postictal agitation and recovery after tonic-clonic seizures in generalized and focal epilepsy.

OBJECTIVE: The postictal state after bilateral tonic-clonic seizures is often prolonged and can have significant impact on a patient's quality of life. Considerable variability exists in the magnitude of postictal agitation and in the speed of recovery, the determinants of which are not well understood. We studied postictal behavior after tonic-clonic seizures in various epilepsy localizations, focusing on postictal agitation and time to responsiveness. METHODS: We retrospectively identified 15 adult patients each with idiopathic generalized, left temporal lobe, right temporal lobe and frontal lobe epilepsy. Localization in focal epilepsy was validated by good outcome after resective surgery at one-year of follow-up. The first tonic-clonic seizure with reliable video and EEG for each patient was analyzed by two reviewers, one of whom was blinded to clinical data. Clinical, ictal and postictal variables were collected for each patient and analyzed. Postictal agitation was classified as mild and marked. RESULTS: We reviewed 60 tonic-clonic seizures, 15 in each of four patient groups. Postictal agitation was observed in 14 patients (23.3%; marked in one and mild in 13). Postictal agitation was most common in patients with left temporal (seven patients) and least common in idiopathic generalized epilepsy (one patient) groups (p=0.035). Based on subgroup analysis (n=28), time to responsiveness was 6.6 minutes for frontal, 7.2 minutes for generalized, 10 minutes for right temporal and 15.7 minutes for the left temporal groups (p<0.05 for frontal vs. left temporal, generalized vs. left temporal). Time to responsiveness was longer in patients with agitation than without (13.9 minutes vs. 7.7 minutes; p=0.048). Patient ictal and postictal characteristics demonstrated no relationship to agitation or latency to postictal recovery. SIGNIFICANCE: To mitigate harm, patients must be monitored carefully after tonic-clonic seizures, especially patients with left temporal lobe epilepsy. Studies evaluating medical and behavioral interventions to promote postictal recovery are needed.