Epileptic Events Research Articles

Migraine and epilepsy frontiers, new challenges in its understanding: A case report

The relationship between migraine and epilepsy has been recognized since the 20th century. Currently, both pathologies share several characteristics, from molecular and electrophysiological mechanisms to their similarity in clinical symptoms and response to treatment. This is a case report of an 11-year-old male patient who presented with focal epilepsy at the age of 8 years. One year later, he developed episodes of migraine without aura followed by seizures with a frequency of 1–2 times per month, with headache duration ranging from 10 min to 6 h. At age 11, he also presented other episodes in which the headache occurred after the epileptic event and other episodes in which the headache was present both before and after the epileptic seizure. An interictal EEG study and an EEG study during a migraine attack showed the presence of high-voltage theta activity and bilateral temporo-parieto-occipital spikes with a greater expression in the right cerebral hemisphere. To our knowledge, this is the first report of an atypical presentation of migraine without aura and epileptic seizure. This case opens new challenges in the search for understanding between both pathologies.

Effect of Helicobacter pylori Eradication on Serum Level of Valproic Acid in Children with Idiopathic Generalized Epilepsy.

The purpose of this study was to determine the influence of H. pylori eradication on the serum level of the orally administered valproic acid (VPA) in children with idiopathic generalized epilepsy; Methods: This prospective cohort observational study included 100 children with idiopathic generalized epilepsy, recruited from a neurology clinic from May 2021 to December 2021. The patients were divided into two groups, each containing 50 children. The first group had a positive H. pylori stool antigen and H. pylori-related symptoms, while the second group had a negative antigen. H. pylori Eradication therapy was given to the positive H. pylori group. The serum level of VPA was obtained at baseline and 4 weeks after eradication therapy. Despite there being no significant difference between the H. pylori-positive and H. pylori-negative groups regarding the baseline VPA serum level (79.9 ± 13.9 and 77.9 ± 13.1 mcg/mL), respectively, the serum VPA level had significantly increased after H. pylori eradication therapy (99.4 ± 11 mcg/mL) (p value = 0.000), as opposed to the H. pylori-negative group (85.3 ± 10.9 mcg/mL) (p value = 0.142). Furthermore, there was a statistically significant association with a negative correlation between the VPA serum level after eradication and the number of epileptic attacks per month (p value = 0.033, R value = -0.301) and the dose of VPA (p value = 0.046, R value = -0.284). The eradication of H. pylori resulted in a highly significant improvement in the serum level of the orally given VPA in children with idiopathic generalized epilepsy, as well as an indirect decrease in the frequency of epileptic events per month, allowing for dose reduction. Eradication therapy may have anticonvulsant properties and might indirectly aid in the management of epileptic activity. H. pylori screening for children with idiopathic generalized epilepsy can optimize serum VPA levels, potentially leading to better seizure control. To our knowledge, this is the first study in the literature to describe the effect of H. pylori eradication on the serum level of the orally administered VPA in children with idiopathic generalized epilepsy.

A - 27 Case Study Approach to Initial Exploration of Adaptations of Cognitive Behavioral Therapy (CBT) for Non-Epileptic Seizures (NES) in the Context of Cognitive Impairment

Abstract Objective The following case study seeks to review implementation of CBT for NES, discuss psychotherapeutic adaptations and outcomes while balancing treatment fidelity, and offer preliminary recommendations for expansion of psychotherapeutic modalities for individuals with cognitive impairment. Methods 49-year-old Hispanic male with a history of mixed epileptic (non-lesional frontal lobe medically refractory) and non-epileptic events. Neurological workup included video EEG, which captured seven events without EEG correlate and an unremarkable brain MRI. Neuropsychological evaluation indicated mild cognitive impairment due to epilepsy with deficits in processing speed, executive functioning, and confrontation naming with borderline to low average core visual and verbal abilities. The patient participated in manualized CBT for PNES. Results Treatment adaptations included extending treatment sessions from 12–19 sessions and including the patient’s sister. They read the chapters together and practiced strategies outside of session. She participated in helping him notice patterns of manifestations of fear and anger and their influence on somatic symptoms. Omission of treatment elements with higher cognitive demand (i.e., thought chart). Outcomes included increased awareness of emotions, triggers, and warnings but not episode reduction in the context of increased epileptic seizures. Conclusions Feasibility of treatment may be limited for individuals with mixed epileptic and NES episodes, particularly if there is cognitive impairment and difficulty differentiating between the two. Psychotherapeutic techniques that are concrete and behaviorally based will = be beneficial for individuals with cognitive impairment. Episode reduction in isolation is likely reductionistic when considering treatment effectiveness. Ability to self-manage episodes, quality of life, functional status, and self-efficacy are valuable markers of improvement.

Association of dietary fiber intake with epileptic seizures in U.S. adults: A Population-base study of 13,277 participants

ObjectiveEpilepsy, a neurological disorder, is identified by the presence of recurrent seizures. We aimed to detect dietary fiber intake and its association with epilepsy prevalence in U.S. adults. MethodsThis cross-sectional study obtained data from the 2013–2018 National Health and Nutrition Examination Survey database. Univariate and multivariate logistic regression models were employed to estimate the association between dietary fiber intake and epilepsy prevalence. The restricted cubic spline (RCS) model was also applied to investigate the dose-response relationships between dietary fiber intake and epileptic seizure events(ESEs). ResultsOur final sample included 13,277 NHANES participants, with the average prevalence of ESEs being 1.09 % (145/13277). After adjusting for all confounding factors, the third quartile of dietary fiber intake levels remained significantly associated with a decreased risk of ESEs[odds ratios (OR) 0.54,95 % confidence interval (CI) 0.33–0.88, P = 0.014)] compared to the first quartile. Higher fiber intake indicated a stable negative association with ESEs in the multivariate logistic regression analysis, weighted generalized additive model. A nonlinear dose-response relationship was observed between dietary fiber intake levels and decreased ESEs risk (P for overall=0.017, P for nonlinear=0.155). Interaction tests showed no significant effect of demographic and disease status on the association between dietary fiber intake and ESEs. ConclusionIn this cross-sectional study, people with a high dietary fiber intake were at a reduced risk of ESEs. However, further prospective studies are needed to investigate the effect of dietary fiber intake in epilepsy events and to determine causality.

The spectrum of indications for ultralong-term EEG monitoring

PurposeWe assessed clinical cases to investigate the spectrum of indications for ultra-longterm EEG monitoring using a subcutaneous implantable device in adult patients with focal epilepsy. MethodsElectronic charts were reviewed from patients undergoing ultra-longterm recordings at the European Epilepsy centers Barcelona, Freiburg and Vienna. Specific patient settings approached in the three centers were analyzed, and the main clinical question was extracted. Results from recordings were analyzed based on the specific results and information obtained. Results24 patients in whom ultra-longterm recordings were available were analyzed. A total of 11 main indications for subcutaneous long-term EEG recordings were identified, including the identification of active epilepsy in patients with low seizure frequency, under- and overreporting of patients, differentiation of non-epileptic from epileptic events, assessment of seizure severity, circadian and multidian rhythms of seizure occurrence, validation of treatment efficacy, improvement of patient-based reporting and medicolegal evidence for seizure freedom. This is reported with patient-specific case vignettes. ConclusionUltra-longterm monitoring using subcutaneous implantable EEG devices can provide relevant diagnostic and treatment information in a large spectrum of clinical situations. This is discussed considering the intrinsic limitations of the method related to spatial coverage, sensitivity and validity as a biomarker of ongoing seizures.

Seizure detection in EEG signal using Gaussian-stockwell transform and Hermite polynomial features

Electroencephalography (EEG) is a non-intrusive and powerful tool for understanding the complex nature of the brain. Epileptic seizures, a neurological disorder, are characterized by excessively synchronized neuronal activity within the brain. This abnormal synchronization disrupts the normal functioning of neural networks, leading to seizures. This work proposes to use the Gaussian-based Stockwell Transform (GST) to segment EEG signals into various frequency bands such as delta, theta, alpha, beta, and gamma band for analysis. The feature extraction process on these sub-band signals generates a feature set, encompassing the fluctuation index, relative amplitude, holoentropy, logarithmic band power, and the newly introduced Hermite polynomial-based delta amplitude modulation spectrogram. To differentiate between epileptic and non-epileptic events in EEG signals, the previous features have been applied to the Random Forest Classifier (RFC) algorithm. The effectiveness of our proposed method is validated using a benchmark EEG dataset, with GST and RFC demonstrating accurate results in distinguishing seizure activity. Experimental results show an optimal classification accuracy of 96.4 %, a sensitivity of 97 %, and a specificity of 96.4 %.

OTHR-14. AN ADOLESCENT WITH A RARE SCHWANNOMA LOCALIZATION AND THE IMPORTANCE OF METHYLATION STUDIES

Abstract BACKGROUND Schwannomas are benign nerve sheath tumours, accounting for about 8% of intracranial tumours, with different histologic patterns described. Olfactory nerves are not expected to have Schwann cells, several theories exist about the origin of these tumours. METHODS/RESULTS A 16-year-old boy was admitted to the emergency department due to a first, self-limited, isolated epileptic event. He scored 15 in the GCS and no focal neurological deficits were observed. At that time, he complained about headaches, lasting for 3 months. Brain CT showed a frontobasal heterogeneous mass. MR characterized it as a 43X34X38 mm well-circumscribed mass, with solid and cystic areas, having an intimate relationship with lamina cribosa, with extensive vasogenic oedema surrounding it, causing deviation of adjacent structures. At that time, he was COVID-19 positive. He was submitted to a craniotomy with a transcortical approach, with an apparent total resection. Retrospectively, he became aware of an improved sense of smell after intervention. The histopathological study revealed a tumour composed of sheets and lobules of large, round cells showing immunopositivity for SOX-10 and S100 and with a Ki-67 index of 5-6%. We proceed to a molecular diagnosis, as the morphology was elusive, finding a methylation pattern highly close to those of schwannomas. With this presumptive diagnosis, clinical and radiological follow-up has been done. After two years, he is doing well, without signs of recurrence. CONCLUSIONS Although rare, an olfactory nerve schwannoma should be considered when there is a frontobasal tumour and impaired sense of smell, although in this case, the COVID-19 infection could be responsible for hyposmia. The clinical picture, imaging and histopathology description were not enough to make the diagnosis and, therefore, to plan the post-surgical approach. We emphasize the importance of a comprehensive molecular study, with a methylation classifier, as this tumour exhibits a typical DNA methylation pattern.

Calibrating Deep Learning Classifiers for Patient-Independent Electroencephalogram Seizure Forecasting.

The recent scientific literature abounds in proposals of seizure forecasting methods that exploit machine learning to automatically analyze electroencephalogram (EEG) signals. Deep learning algorithms seem to achieve a particularly remarkable performance, suggesting that the implementation of clinical devices for seizure prediction might be within reach. However, most of the research evaluated the robustness of automatic forecasting methods through randomized cross-validation techniques, while clinical applications require much more stringent validation based on patient-independent testing. In this study, we show that automatic seizure forecasting can be performed, to some extent, even on independent patients who have never been seen during the training phase, thanks to the implementation of a simple calibration pipeline that can fine-tune deep learning models, even on a single epileptic event recorded from a new patient. We evaluate our calibration procedure using two datasets containing EEG signals recorded from a large cohort of epileptic subjects, demonstrating that the forecast accuracy of deep learning methods can increase on average by more than 20%, and that performance improves systematically in all independent patients. We further show that our calibration procedure works best for deep learning models, but can also be successfully applied to machine learning algorithms based on engineered signal features. Although our method still requires at least one epileptic event per patient to calibrate the forecasting model, we conclude that focusing on realistic validation methods allows to more reliably compare different machine learning approaches for seizure prediction, enabling the implementation of robust and effective forecasting systems that can be used in daily healthcare practice.

Primary vs. pre-emptive anti-seizure medication prophylaxis in anti-CD19 CAR T-cell therapy

IntroductionSeizures may occur in up to 30% of non-Hodgkin lymphoma patients who received anti-CD19 CAR T-cell therapy, yet the optimal anti-seizure medication (ASM) prevention strategy has not been thoroughly investigated.MethodsConsecutive patients affected by refractory non-Hodgkin lymphoma who received anti-CD19 CAR T-cells were included. Patients were selected and assessed using similar internal protocols. ASM was started either as a primary prophylaxis (PP-group) before CAR T-cells infusion or as a pre-emptive therapy (PET-group) only upon the onset of neurotoxicity development.ResultsOne hundred fifty-six patients were included (PP-group = 88, PET-group = 66). Overall, neurotoxicity and severe neurotoxicity occurred in 45 (29%) and 20 (13%) patients, respectively, equally distributed between the two groups. Five patients experienced epileptic events (PET-group = 3 [4%]; PP-group = 2 [2%]). For all the PET-group patients, seizure/status epilepticus occurred in the absence of overt CAR-T-related neurotoxicity, whereas patients in the PP-group experienced brief seizures only in the context of critical neurotoxicity with progressive severe encephalopathy. ASMs were well-tolerated by all patients, even without titration. No patients developed epilepsy or required long-term ASMs.ConclusionOur data suggest that both primary and pre-emptive anti-seizure prophylaxis are safe and effective in anti-CD19 CAR T-cell recipients. Clinical rationale suggests a possible more favourable profile of primary prophylaxis, yet no definitive conclusion of superiority between the two ASM strategies can be drawn from our study.

Multiscale neuro-inspired models for interpretation of EEG signals in patients with epilepsy

ObjectiveThe aim is to gain insight into the pathophysiological mechanisms underlying interictal epileptiform discharges observed in electroencephalographic (EEG) and stereo-EEG (SEEG, depth electrodes) recordings performed during pre-surgical evaluation of patients with drug-resistant epilepsy. MethodsWe developed novel neuro-inspired computational models of the human cerebral cortex at three different levels of description: i) microscale (detailed neuron models), ii) mesoscale (neuronal mass models) and iii) macroscale (whole brain models). Although conceptually different, micro- and mesoscale models share some similar features, such as the typology of neurons (pyramidal cells and three types of interneurons), their spatial arrangement in cortical layers, and their synaptic connectivity (excitatory and inhibitory). The whole brain model consists of a large-scale network of interconnected neuronal masses, with connectivity based on the human connectome. ResultsFor these three levels of description, the fine-tuning of free parameters and the quantitative comparison with real data allowed us to reproduce interictal epileptiform discharges with a high degree of fidelity and to formulate hypotheses about the cell- and network-related mechanisms underlying the generation of fast ripples and SEEG-recorded epileptic spikes and spike-waves. ConclusionsThe proposed models provide valuable insights into the pathophysiological mechanisms underlying the generation of epileptic events. The knowledge gained from these models effectively complements the clinical analysis of SEEG data collected during the evaluation of patients with epilepsy. SignificanceThese models are likely to play a key role in the mechanistic interpretation of epileptiform activity.

Ultra-Long-Term-EEG Monitoring (ULTEEM) Systems: Towards User-Friendly Out-of-Hospital Recordings of Electrical Brain Signals in Epilepsy.

Epilepsy is characterized by the occurrence of epileptic events, ranging from brief bursts of interictal epileptiform brain activity to their most dramatic manifestation as clinically overt bilateral tonic-clonic seizures. Epileptic events are often modulated in a patient-specific way, for example by sleep. But they also reveal temporal patterns not only on ultra- and circadian, but also on multidien scales. Thus, to accurately track the dynamics of epilepsy and to thereby enable and improve personalized diagnostics and therapies, user-friendly systems for long-term out-of-hospital recordings of electrical brain signals are needed. Here, we present two wearable devices, namely ULTEEM and ULTEEMNite, to address this unmet need. We demonstrate how the usability concerns of the patients and the signal quality requirements of the clinicians have been incorporated in the design. Upon testbench verification of the devices, ULTEEM was successfully benchmarked against a reference EEG device in a pilot clinical study. ULTEEMNite was shown to record typical macro- and micro-sleep EEG characteristics in a proof-of-concept study. We conclude by discussing how these devices can be further improved and become particularly useful for a better understanding of the relationships between sleep, epilepsy, and neurodegeneration.

Effect of GABAa-receptors on neuronal discharge and ion activity in focal seizures.

Focal seizures are a type of epileptic event that has plagued the medical community for a long time, and the existing drug treatment is mainly based on the modulation of ${GABA}_a$-receptors to affect GABAergic signaling to achieve the therapeutic purpose. The majority of research currently focuses on the impact of ${GABA}_a$-receptors on neuronal firing, failing to analyze the molecular and ionic mechanisms involved. Specifically, the research on deeper-level mechanisms on how ${GABA}_a$-receptors affect neuronal firing by altering ion activity has not been addressed. This research aimed to study the effects of different ${GABA}_a$-receptor structures on ion activity in focal seizures model by adjusting parameters of the ${GABA}_a$-receptors: the rise time constant (${tau}_1$) and decay time constant (${tau}_2$). The research indicates that as the values of ${tau}_1$ and ${tau}_2$ of the ${GABA}_a$-receptor change, the ion concentration will vary based on the change of the ${GABA}_a$-receptor potential. To a certain extent, the duration of epileptic activity will also be affected to a certain extent. In conclusion, the alteration of ${GABA}_a$-receptor structure will affect the inhibitory effect of interneurons on pyramidal neurons, and different parameters of the ${GABA}_a$-receptor will directly impact the therapeutic effect.

Decrease in phase slip rates and phase cone structures during seizure evolution and epileptogenic activities derived from microgrid ECoG data

Sudden phase changes are related to cortical phase transitions, which likely change in frequency and spatial distribution as epileptogenic activity evolves. A 100 s long section of micro-ECoG data obtained before and during a seizure was selected and analyzed. In addition, nine other short-duration epileptic events were also examined. The data was collected at 420 Hz, imported into MATLAB, downsampled to 200 Hz, and filtered in the 1–50 Hz band. The Hilbert transform was applied to compute the analytic phase, which was then unwrapped, and detrended to look for sudden phase changes. The phase slip rate (counts/s) and its acceleration (counts/s2) were computed with a stepping window of 1-s duration and with a step size of 5 ms. The analysis was performed for theta (3–7 Hz), alpha (7–12 Hz), and beta (12–30 Hz) bands. The phase slip rate on all electrodes in the theta band decreased while it increased for the alpha and beta bands during the seizure period. Similar patterns were observed for isolated epileptogenic events. Spatiotemporal contour plots of the phase slip rates were also constructed using a montage layout of 8 × 8 electrode positions. These plots exhibited dynamic and oscillatory formation of phase cone-like structures which were higher in the theta band and lower in the alpha and beta bands during the seizure period and epileptogenic events. These results indicate that the formation of phase cones might be an excellent biomarker to study the evolution of a seizure and also the cortical dynamics of isolated epileptogenic events.

Predictive capability of Cys112Arg single nucleotide polymorphisms of the apolipoprotein E gene in assessing the risk of immediate and early post-traumatic seizures

This study is aimed at investigating epileptic seizures, one of the consequences of traumatic brain injury (TBI). Immediate and early post-traumatic seizures, as well as late post-traumatic epileptic seizures or post-traumatic epilepsy, can have different pathogenetic bases. The following key risk factors associated with post-traumatic epilepsy are known: duration of unconsciousness, gunshot wounds, intracranial hemorrhage, diffuse axonal injury, prolonged (more than 3 days) post-traumatic amnesia, acute subdural hematoma with surgical evacuation, immediate and early post-traumatic epileptic seizures, fracture of the skull bones. The role of genetic factors in post-traumatic seizures is poorly understood due to the complexity and multiple causal mechanisms. This paper addresses the role of genetic factors in the occurrence and severity of epileptic events in patients with TBI. In particular, we investigated the role of the Cys112Arg single nucleotide polymorphism of the apolipoprotein E gene. Apolipoprotein E is known for its role in the transport and metabolism of lipids and, therefore, the development of cardiovascular diseases; it is also associated with Alzheimer's disease and has recently been studied in the context of association with epilepsy. The study shows an association between this polymorphism and the risk of immediate and early epileptic seizures in patients with severe TBI.

Persistent Homology-Based Classification of Chaotic Multi-variate Time Series: Application to Electroencephalograms

In this work, we present a combination of dimension reduction techniques and persistent homology for detection of epileptic events in electroencephalograms for a special kind of epilepsy called petit-mal epilepsy. Persistent homology, one of the main methods in topological data analysis, extracts information about the structures appearing in a given data set. Since during an epileptic seizure of the above type the electrical brain activity is more synchronized, we take the resulting structure in the EEG signal as classification feature that is analyzed topologically by means of persistent homology. As preprocessing step, the dimension of the data is reduced by two alternative techniques, principal component analysis and dynamical component analysis, and their performance is compared. Our results show that in comparison to principal component analysis, dynamical component analysis captures the dynamics of the system when projected onto a low-dimensional subspace. Furthermore, the results prove that persistent homology is well-suited for the detection of petit-mal epileptic seizures by means of their inherent structure.

A randomised controlled trial on the effect of viewing the event on psychological outcome in patients with psychogenic non epileptic events (EVEPOP Trial)

A randomised controlled trial on the effect of viewing the event on psychological outcome in patients with psychogenic non epileptic events (EVEPOP Trial)

A new epileptic seizure prediction model based on maximal overlap discrete wavelet packet transform, homogeneity index, and machine learning using ECG signals

Epilepsy, a complex pathology with various etiological origins, is characterized by producing hyperexcitability in the brain, which can have multiple disruptive symptoms. It impacts about 40 million people worldwide, of which 20 to 30% have chronic and intractable seizures. Each seizure can create hazardous situations for patients resulting from fractures, burns, submersion accidents, and soft-tissue injuries. Therefore, a method capable of predicting a seizure with sufficient window time before its onset is highly desirable because it will allow the patient to locate a safe place or take appropriate precautionary actions. In this article, a novel method is presented through adroit integration of maximal overlap wavelet packet transform, homogeneity index, and a K-Nearest Neighbors classifier to predict an epileptic event twenty minutes before its onset using electrocardiogram (ECG) signals. The method's effectiveness for predicting an epileptic seizure is verified by employing a database provided by the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH), which includes seven patients with ten epileptic seizures. The results show that the proposed method effectively predicts an epileptic seizure 20 min prior to its onset with an accuracy of 93.25%.

Menthol Dissolved in Dimethyl Sulfoxide Protects Against Epileptiform Activity Induced by Pentylenetetrazol in Male Rats.

This research aims to investigate the protective action of menthol dissolved in dimethyl sulfoxide (DMSO) on experimental epileptiform activity induced by the intraperitoneal (IP) injection of pentylenetetrazol (PTZ) in male rats. Thirty adult male Wistar rats weighing 200-250 g were randomly assigned to five equal groups. The control animals received normal saline (200 μL) and the rest four cohorts were considered as treatment. Menthol was dissolved in DMSO and intraperitoneally injected at the doses of 100, 200, and 400 mg/kg into the first, second, and third groups (M100, M200, and M400 V=200 μL), respectively. The fourth treatment was injected with the solvent (200 μL). The animals were anesthetized, then underwent cranial surgery and a recording electrode was implanted in the stratum radiatum of the hippocampal carbonic anhydrase 1 (CA1) region (AP=-2.76 mm, ML=-1.4 mm and DV=3 mm). The seizure activity was induced by PTZ (IP) and assessed by counting and measuring amplitudes of the spikes for 10 minutes using the eTrace program. Menthol was observed to significantly reduce the activity level of PTZ-induced epileptiform activity, as well as exert a protective and inhibitory action on proconvulsant effect of DMSO in a dose-dependent manner. Menthol can potentially be used as an adjuvant to prevent seizure activity. Dimethyl sulfoxide (DMSO) induces proconvulsant effects, significantly increasing spike counts.Menthol 100 mg/kg also stimulates seizure activity, leading to a substantial spike count increase.Menthol 200 and 400 mg/kg exhibit inhibitory effects, decreasing seizure activity and spike counts. In this study, we explored the potential protective effects of menthol, dissolved in dimethyl sulfoxide (DMSO), on experimentally induced epileptiform activity in male rats. Our research involved thirty adult male Wistar rats, divided into five groups. While the control group received normal saline, the remaining four groups were treated with different doses of menthol in DMSO. The rats underwent surgery, and electrodes were implanted in the hippocampal region for recording. Using pentylenetetrazol (PTZ) to induce seizure activity, we observed that menthol, administered at varying doses, significantly reduced the level of epileptiform activity triggered by PTZ. Notably, menthol also demonstrated a protective and inhibitory effect on the proconvulsant action of DMSO, and this effect was dose-dependent. In simpler terms, our findings suggest that menthol has the potential to be used as an additional treatment to prevent seizure activity. This means that incorporating menthol, especially at specific doses, may offer a protective influence against epileptic events. This research sheds light on a promising avenue for potential therapeutic interventions, emphasizing the importance of further exploration of menthol's role in epilepsy prevention. Ultimately, our study opens the door to considering menthol as a valuable component in the development of strategies to mitigate the impact of seizures.

45 Can Surgical Ablation Modify a Developmental Visuospatial Impairment in Periventricular Nodular Heterotopia? A Case Study

Objective:Periventricular nodular heterotopia (PVNH) is a malformation of cortical development (MCD) characterized by aggregates of gray matter adjacent to the lateral ventricular walls. Clinical presentation is heterogeneous with higher rates of seizures and reading impairments typically in the setting of average IQ (Felker et al. 2011). The majority of neuropsychological inquiry has focused on reading fluency, though a single case study showed a neurocognitive profile consistent with nonverbal learning deficits in a 7-year old boy with suspected autosomal dominant bilateral heterotopia (McCann et al., 2008). Given the periventricular focus and potential for unilateral presentations, non-linguistic neurocognitive sequelae may be expected in cases affecting the non-dominant hemisphere, yet this remains largely unexplored. Surgical ablation by laser interstitial thermal therapy (LITT) is increasingly used for epilepsy management in PVNH (Thompson et al., 2016, Whiting et al. 2020). However, there are no reported studies exploring cognitive outcomes following LITT of focal PVNH.Participants and Methods:A 46-year-old, right handed, Black female with 16 years of education presented for management of medically refractory epilepsy. Epilepsy monitoring captured intermittent slow waves in the right temporal lobe, interictal polyspikes in the right temporal lobe, and three epileptic events all emanating from the right temporal lobe. MRI showed extensive migrational anomalies involving the right hemisphere posteriorly consistent with PVNH with no associated mesial temporal sclerosis. Pre-surgical neuropsychological evaluation showed a significant split in IQ, with verbal IQ = 99 and performance IQ = 76. Testing indicated circumscribed deficits in visuoperceptual judgement, visuoconstruction, visuospatial reasoning, non-verbal recall, and several executive weaknesses in the context of otherwise average neurocognitive functioning. Fine motor speed was impaired bilaterally. Her profile was suggestive of non-dominant fronto-parieto-temporal dysfunction, concordant with the remainder of her work-up. By history she reported longstanding academic weaknesses in math and organization with strong verbal and reading abilities.Results:The patient underwent partial LITT of right PVNH sparing areas involved in visual function. At 6-month follow-up she was seizure free (Engel outcome 1A). Post-surgical neuropsychological evaluation showed reliable improvements in perceptual reasoning, aspects of learning/memory, and verbal naming. Visuoconstruction remained impaired but qualitatively improved. She also reported subjective experience of improved mental clarity and was applying for jobs after regaining driving privileges.Conclusions:This case demonstrates symptoms and history concerning for a nonverbal learning disorder in an adult woman with epilepsy secondary to right hemisphere PVNH and underscores the importance of exploring the range of neurocognitive profiles in MCD. Her notable neurocognitive and functional improvements following surgical ablation and seizure freedom suggest a possible release of function in the absence of inhibitory neurophysiological influences. This raises interesting questions about the endurance of her developmental profile. This case report contributes to our understanding of neuroanatomical correlates of neurocognitive and neurodevelopmental presentations. Future investigations should explore neuropsychological changes following LITT for PVNH.

Recurrent transient amnesia: a case of transient epileptic amnesia misdiagnosed as transient global amnesia

Transient epileptic amnesia and transient global amnesia both exhibit temporary memory loss. The lack of clues of epileptic events and the absence of epileptiform abnormalities in electroencephalography, a clear brain lesion, and interictal cognitive decline can make diagnoses challenging. Here we present a middle-aged female who experienced long-term recurrent transient epileptic amnesia with subtle epileptic features over a period of 3 years.