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In this paper we look at non-pharmaceutical treatments for intractable epilepsy based on neurophysiological methods especially with EEG analysis. In summary, there are a number of limbic and thalamo-cortical related structures involved in the processing of musical emotion (exposure), including the amygdala (arousal, expression of mood, fear), hippocampus (memory, regulation of HPA axis, stress), parahippocampal gyrus (recognition, memory retrieval), insula (valence), temporal poles (connectivity), ventral striatum (expectation and experience of reward), orbitofrontal cortex (valence) and cingulate cortex (autonomic regulation). One method is to audify (a form of sonification) EEG activity to find music by feedback to entrain abnormal EEG activity. We discuss various methods and our use of X-System (https://www.x-system.co.uk/) which is a computational model of the musical brain capable of predicting the neurophysiological effects of music. It models structures and pathways related to responses to music, including the cochlea, brain stem, auditory and motor cortex, as well as basal ganglia, cerebellum and limbic structures. It can predict autonomic and endocrine activity as well as the substrates of electrical activity to select music which can regularise EEG abnormalities to decrease epileptic activity and seizures, especially in those unresponsive to antiepileptic medication or invasive treatments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: Interictal dysphoric disorder (IDD) has been regarded as an affective disorder occurring only in people with epilepsy (PWE). Data showing similar characteristics and similar prevalence of IDD in patients with migraine and with psychogenic nonepileptic seizures question the epilepsy-specific nature of IDD. The aim of the study was to investigate the nature of IDD in people with prevalent epilepsy with mood disorders and people with mood disorders who are free of neurological disease., Methods: This is a case-control study, with 142 patients with a confirmed diagnosis of epilepsy and major depressive disorder (MDD; cases) and 222 patients with MDD only (controls). MDD diagnosis was confirmed by a structured clinical interview for Diagnostic and Statistical Manual of Mental Disorders, 4th edition (SCID-I-RV). We used the Beck Depression Inventory and the Beck Anxiety Inventory to estimate anxiety and depression levels and the Interictal Dysphoric Disorder Inventory (IDDI) to confirm the presence of IDD. Mann-Whitney U test, Pearson chi-squared, Spearman correlation, and logistic regression were used., Results: No differences were found in the prevalence of IDD between PWE with MDD and people with MDD alone (88.73% vs. 85.13%, χ2 = .96, p = .32). There were no differences between the groups overall or for any IDDI subscales (all p > .05). In both groups, IDD symptoms were grouped with the same incidence and had the same duration and periodicity. IDD was not associated with epilepsy (odds ratio = .84, 95% confidence interval = .40-1.98, p = .72). No significant correlation was found between epilepsy, demographic characteristics, and all IDDI subscales (all p > .05). Notably, patients with IDD suffered from affective disorders longer (6.68 ± 6.82 years vs. 3.7 ± 3.97 years, p = .001) and also received higher scores on all psychometric scales (all p < .05)., Significance: This study does not confirm the specificity of IDD for epilepsy. The presence of IDD symptoms may be associated with a more severe course of MDD and significant anxiety distress., (© 2021 International League Against Epilepsy.)

Objective: To develop and validate a tool for individualized prediction of sudden unexpected death in epilepsy (SUDEP) risk, we reanalyzed data from 1 cohort and 3 case-control studies undertaken from 1980 through 2005., Methods: We entered 1,273 epilepsy cases (287 SUDEP, 986 controls) and 22 clinical predictor variables into a Bayesian logistic regression model., Results: Cross-validated individualized model predictions were superior to baseline models developed from only average population risk or from generalized tonic-clonic seizure frequency (pairwise difference in leave-one-subject-out expected log posterior density = 35.9, SEM ± 12.5, and 22.9, SEM ± 11.0, respectively). The mean cross-validated (95% bootstrap confidence interval) area under the receiver operating curve was 0.71 (0.68-0.74) for our model vs 0.38 (0.33-0.42) and 0.63 (0.59-0.67) for the baseline average and generalized tonic-clonic seizure frequency models, respectively. Model performance was weaker when applied to nonrepresented populations. Prognostic factors included generalized tonic-clonic and focal-onset seizure frequency, alcohol excess, younger age at epilepsy onset, and family history of epilepsy. Antiseizure medication adherence was associated with lower risk., Conclusions: Even when generalized to unseen data, model predictions are more accurate than population-based estimates of SUDEP. Our tool can enable risk-based stratification for biomarker discovery and interventional trials. With further validation in unrepresented populations, it may be suitable for routine individualized clinical decision-making. Clinicians should consider assessment of multiple risk factors, and not focus only on the frequency of convulsions., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Based on a multicenter cohort of people with anti-NMDA receptor encephalitis (anti-NMDARE), we describe seizure phenotypes, electroencephalographic (EEG) findings, and anti-seizure treatment strategies. We also investigated whether specific electrographic features are associated with persistent seizures or status epilepticus after acute presentation. In this retrospective cohort study, we reviewed records of children and adults with anti-NMDARE between 2010 and 2014 who were included in the Rare Epilepsy of New York City database, which included the text of physician notes from five academic medical centers. Clinical history (e.g., seizure semiology) and EEG features (e.g., background organization, slowing, epileptiform activity, seizures, sleep architecture, extreme delta brush) were abstracted. We compared clinical features associated with persistent seizures (ongoing seizures after one month from presentation) and status epilepticus, using bivariate and multivariable analyses. Among the 38 individuals with definite anti-NMDARE, 32 (84%) had seizures and 29 (76%) had seizures captured on EEG. Electrographic-only seizures were identified in five (13%) individuals. Seizures started at a median of four days after initial symptoms (IQR: 3-6 days). Frontal lobe-onset focal seizures were most common (n=12; 32%). Most individuals (31/38; 82%) were refractory to anti-seizure medications. Status epilepticus was associated with younger age (15 years [9-20] vs. 23 years [18-27]; p=0.04) and Hispanic ethnicity (30 [80%] vs. 8 [36%]; p=0.04). Persistent seizures (ongoing seizures after one month from presentation) were associated with younger age (nine years [3-14] vs. 22 years [15-28]; p<0.01). Measured electrographic features were not associated with persistent seizures. Seizures associated with anti-NMDARE are primarily focal seizures originating in the frontal lobes. Younger patients may be at increased risk of epileptogenesis and status epilepticus. Continuous EEG monitoring helps identify subclinical seizures, but specific EEG findings may not predict the severity or persistence of seizures during hospitalization.

Objective: To obtain medical records, family interviews, and death-related reports of sudden unexpected death in epilepsy (SUDEP) cases to better understand SUDEP., Methods: All cases referred to the North American SUDEP Registry (NASR) between October 2011 and June 2018 were reviewed; cause of death was determined by consensus review. Available medical records, death scene investigation reports, autopsy reports, and next-of-kin interviews were reviewed for all cases of SUDEP. Seizure type, EEG, MRI, and SUDEP classification were adjudicated by 2 epileptologists., Results: There were 237 definite and probable cases of SUDEP among 530 NASR participants. SUDEP decedents had a median age of 26 (range 1-70) years at death, and 38% were female. In 143 with sufficient information, 40% had generalized and 60% had focal epilepsy. SUDEP affected the full spectrum of epilepsies, from benign epilepsy with centrotemporal spikes (n = 3, 1%) to intractable epileptic encephalopathies (n = 27, 11%). Most (93%) SUDEPs were unwitnessed; 70% occurred during apparent sleep; and 69% of patients were prone. Only 37% of cases of SUDEP took their last dose of antiseizure medications (ASMs). Reported lifetime generalized tonic-clonic seizures (GTCS) were <10 in 33% and 0 in 4%., Conclusions: NASR participants commonly have clinical features that have been previously been associated with SUDEP risk such as young adult age, ASM nonadherence, and frequent GTCS. However, a sizeable minority of SUDEP occurred in patients thought to be treatment responsive or to have benign epilepsies. These results emphasize the importance of SUDEP education across the spectrum of epilepsy severities. We aim to make NASR data and biospecimens available for researchers to advance SUDEP understanding and prevention., (Copyright © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Objective: This retrospective study explores to what extent additional information from event witnesses provided using the novel 31-item Paroxysmal Event Observer (PEO) Questionnaire improves the differentiation among epilepsy, syncope, and psychogenic nonepileptic seizures (PNES) achievable with information provided by patients alone., Methods: Patients with transient loss of consciousness caused by proven epilepsy (n = 86), syncope (n = 79), or PNES (n = 84) attending specialist neurology/syncope services in the United Kingdom and event observers provided Paroxysmal Event Profile (PEP), PEO, and personal information (PI) (e.g., sex, age, medical history) data. PEO data were subjected to exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA). PEO, PEP, and PI data were used separately and in combination to differentiate diagnoses by pairwise and multinomial logistic regressions. Predicted diagnoses were compared with gold standard medical diagnoses., Results: EFA/CFA identified a 4-factor structure of the PEO based on 26/31 questionnaire items with loadings ≥0.4. Observer-reported factors alone differentiated better between syncope and epilepsy than patient-reported factors (accuracy: 96% vs 85%, p = 0.0004). Observer-reported data improved accuracy over differentiation based on patient-reported data alone from 90% to 100% between syncope and epilepsy ( p = 0.005), 76% to 83% between epilepsy and PNES ( p = 0.006), and 93% to 95% between syncope and PNES ( p = 0.098)., Conclusions: Information from observers can make an important contribution to the differentiation of epilepsy from syncope or PNES but adds less to that of syncope from PNES., (© 2019 American Academy of Neurology.)

Objective: To examine the consistency of applying the Nashef et al (2012) criteria to classify sudden unexpected death in epilepsy (SUDEP)., Methods: We reviewed cases from the North American SUDEP Registry (n = 250) and Medical Examiner Offices (n = 1301: 698 Maryland, 457 New York City, 146 San Diego). Two epileptologists with expertise in SUDEP and epilepsy-related mortality independently reviewed medical records, scene investigation, autopsy, and toxicology and assigned a SUDEP class., Results: Major areas of disagreement arose between adjudicators concerned differentiating (1) Definite SUDEP Plus Comorbidity from Possible SUDEP and (2) Resuscitated (Near) SUDEP from SUDEP. In many cases, distinguishing between contributing and competing causes of death when trying to classify Definite SUDEP Plus Comorbidity versus Possible SUDEP is ambiguous and relies on judgement. Similarly, determining if an intervention was lifesaving or not (Resuscitated SUDEP or Not SUDEP), or if resuscitation merely delayed SUDEP (Resuscitated SUDEP or SUDEP) is often a judgement call and can differ between experienced adjudicators. Given these persisting ambiguities, we propose more explicit criteria for distinguishing these categories., Significance: Accurate and consistent classification of cause of death among individuals with epilepsy remains a dire public health concern. SUDEP is likely underestimated in national health statistics. Greater standardization of criteria among epilepsy researchers, medical examiners, and epidemiologists to determine cause and classify death will lead to more accurate tracking of SUDEP and other epilepsy-related mortalities., (Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.)

Sudden unexpected death of an individual with epilepsy can pose a challenge to death investigators, as most deaths are unwitnessed, and the individual is commonly found dead in bed. Anatomic findings (eg, tongue/lip bite) are commonly absent and of varying specificity, thereby limiting the evidence to implicate epilepsy as a cause of or contributor to death. Thus it is likely that death certificates significantly underrepresent the true number of deaths in which epilepsy was a factor. To address this, members of the National Association of Medical Examiners, North American SUDEP Registry, Epilepsy Foundation SUDEP Institute, American Epilepsy Society, and the Centers for Disease Control and Prevention constituted an expert panel to generate evidence-based recommendations for the practice of death investigation and autopsy, toxicological analysis, interpretation of autopsy and toxicology findings, and death certification to improve the precision of death certificate data available for public health surveillance of epilepsy-related deaths. The recommendations provided in this paper are intended to assist medical examiners, coroners, and death investigators when a sudden unexpected death in a person with epilepsy is encountered., (© 2018 National Association of Medical Examiners. This paper has been simultaneously published in Epilepsia. Volume 59, #3 and Academic Forensic Pathology: The Official Publication of the National Association of Medical Examiners, Volume 8, #1.)

Central nervous system infections (CNSI) are a leading cause of death and long-term disability in children. Using ICD-10 data from 2005 to 2015 from three central hospitals in Ho Chi Minh City (HCMC), Vietnam, we exploited generalized additive mixed models (GAMM) to examine the spatial-temporal distribution and spatial and climatic risk factors of paediatric CNSI, excluding tuberculous meningitis, in this setting. From 2005 to 2015, there were 9469 cases of paediatric CNSI; 33% were ⩽1 year old at admission and were mainly diagnosed with presumed bacterial CNSI (BI) (79%), the remainder were >1 year old and mainly diagnosed with presumed non-bacterial CNSI (non-BI) (59%). The urban districts of HCMC in proximity to the hospitals as well as some outer districts had the highest incidences of BI and non-BI; BI incidence was higher in the dry season. Monthly BI incidence exhibited a significant decreasing trend over the study. Both BI and non-BI were significantly associated with lags in monthly average temperature, rainfall, and river water level. Our findings add new insights into this important group of infections in Vietnam, and highlight where resources for the prevention and control of paediatric CNSI should be allocated.

Objective: Lack of standardized terminology on death certificates (DCs) of SUDEP type cases may obscure the presence of epilepsy in these deaths. Most DCs for individuals dying unexpectedly with epilepsy are certified by medical examiners (MEs). The purpose of this study was to gauge death certification practices of MEs when interpreting SUDEP cases and assess implications for valid surveillance of SUDEP., Materials and Methods: A survey consisting of clinical vignettes describing deaths in individuals with epilepsy was sent to medical examiners. Respondents were asked to indicate how they would certify death on a DC. Similar text responses were aggregated and coded according to the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) coding system., Results: A total of 847 responses on 11 cases were received. Depending upon the vignette, the proportion of responses within each case that did not have an ICD-10 seizure code ranged from 3% to 62%. G40.9 (Epilepsy, unspecified) resulted from 43% of responses, and R56.8 (Other and unspecified convulsion) resulted from 38% of responses., Conclusion: The survey indicates that a high proportion of DCs do not have a seizure code and would not be identified utilizing these ICD-10 codes. The complicated nature of deaths in SUDEP, unclear circumstances surrounding a given death, and the lack of familiarity with SUDEP by surviving relatives may all contribute to variable terminology used to certify SUDEP deaths. Our results emphasize the need for collaboration between neurologists and forensic pathologists to develop a more uniform approach to death certification in SUDEP that will facilitate SUDEP research and inform relatives of individuals who die of SUDEP., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Through music we can learn much about our human origins and the human brain. Music is a potential method of therapy and a means of accessing and stimulating specific cerebral circuits. There is also an association between musical creativity and psychopathology. This paper provides a brief review.

The North American SUDEP Registry (NASR) is a repository of clinical data and biospecimens in cases of sudden unexpected death in epilepsy (SUDEP), a leading cause of epilepsy-related deaths. We assessed whether bereaved families were aware of SUDEP before their family member's death and their preferences for SUDEP disclosure. At enrollment, next-of-kin of SUDEP cases completed an intake interview, including questions assessing premorbid SUDEP discussions. Only 18.1% of the 138 next-of-kin recalled a previous discussion of SUDEP with a healthcare provider or support resource. Of the 112 who did not recall such a discussion, 72.3% wished it was discussed, 10.7% were satisfied it was not discussed, and 17% were unsure. A history of status epilepticus predicted SUDEP discussion. Rates of SUDEP discussion were not significantly higher among SUDEPs after 2013 (the approximate study midpoint) compared with those before then. Our study suggests that SUDEP remains infrequently discussed with family members of persons with epilepsy. Nearly three-quarters of family members wished they had known of SUDEP before the death. However, some were indifferent or were satisfied that this discussion had not occurred. We must balance more systematic education of patients and families about SUDEP while respecting individual preferences about having this discussion., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: Epileptic seizures, syncope, and psychogenic nonepileptic seizures (PNES) account for over 90% of presentations with transient loss of consciousness (TLOC). The patient's history is crucial for the diagnosis, but the diagnostic value of individual semiologic features is limited. This study explores the diagnostic potential of a comprehensive questionnaire focusing on TLOC-associated symptoms., Methods: A total of 386 patients with proven epilepsy, 308 patients with proven PNES, and 371 patients with proven syncope were approached by post to recruit 100 patients in each diagnostic group. Symptoms were self-reported on an 86-item questionnaire (the Paroxysmal Event Profile [PEP]) using a 5-point Likert scale (always to never). Data were subjected to exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA). Factors were used to differentiate between diagnoses by pairwise and multinomial regression., Results: Patients with PNES reported more and more frequent TLOC-associated symptoms than those with epilepsy or syncope (p < 0.001). EFA/CFA identified a 5-factor structure based on 74/86 questionnaire items with loadings ≥0.4. Pairwise logistic regression analysis correctly classified 91% of patients with epilepsy vs those with syncope, 94% of those with PNES vs those with syncope, and 77% of those with epilepsy vs those with PNES. Multinomial logistic regression analysis yielded a similar pattern., Conclusions: Clusters of self-reported TLOC symptoms can be used to direct patients to appropriate investigation and treatment pathways for syncope on the one hand and seizures on the other, although additional information is required for a reliable distinction, especially between epilepsy and PNES., (© 2016 American Academy of Neurology.)

The syndrome known as nocturnal frontal lobe epilepsy is recognized worldwide and has been studied in a wide range of clinical and scientific settings (epilepsy, sleep medicine, neurosurgery, pediatric neurology, epidemiology, genetics). Though uncommon, it is of considerable interest to practicing neurologists because of complexity in differential diagnosis from more common, benign sleep disorders such as parasomnias, or other disorders like psychogenic nonepileptic seizures. Moreover, misdiagnosis can have substantial adverse consequences on patients' lives. At present, there is no consensus definition of this disorder and disagreement persists about its core electroclinical features and the spectrum of etiologies involved. To improve the definition of the disorder and establish diagnostic criteria with levels of certainty, a consensus conference using formal recommended methodology was held in Bologna in September 2014. It was recommended that the name be changed to sleep-related hypermotor epilepsy (SHE), reflecting evidence that the attacks are associated with sleep rather than time of day, the seizures may arise from extrafrontal sites, and the motor aspects of the seizures are characteristic. The etiology may be genetic or due to structural pathology, but in most cases remains unknown. Diagnostic criteria were developed with 3 levels of certainty: witnessed (possible) SHE, video-documented (clinical) SHE, and video-EEG-documented (confirmed) SHE. The main research gaps involve epidemiology, pathophysiology, treatment, and prognosis., (© 2016 American Academy of Neurology.)

Epilepsy is one of the most common disabling neurological disorders, but significant gaps exist in our knowledge about childhood epilepsy in rural populations. The present study assessed the prevalence of pediatric epilepsy in nine low-income rural counties in the Midwestern United States overall and by gender, age, etiology, seizure type, and syndrome. Multiple sources of case identification were used, including medical records, schools, community agencies, and family interviews. The prevalence of active epilepsy was 5.0/1000. Prevalence was 5.1/1000 in males and 5.0/1000 in females. Differences by age group and gender were not statistically significant. Future research should focus on methods of increasing study participation in rural communities, particularly those in which research studies are rare., (Copyright © 2015 Elsevier Inc. All rights reserved.)

The Commission on Classification and Terminology and the Commission on Epidemiology of the International League Against Epilepsy (ILAE) have charged a Task Force to revise concepts, definition, and classification of status epilepticus (SE). The proposed new definition of SE is as follows: Status epilepticus is a condition resulting either from the failure of the mechanisms responsible for seizure termination or from the initiation of mechanisms, which lead to abnormally, prolonged seizures (after time point t1 ). It is a condition, which can have long-term consequences (after time point t2 ), including neuronal death, neuronal injury, and alteration of neuronal networks, depending on the type and duration of seizures. This definition is conceptual, with two operational dimensions: the first is the length of the seizure and the time point (t1 ) beyond which the seizure should be regarded as "continuous seizure activity." The second time point (t2 ) is the time of ongoing seizure activity after which there is a risk of long-term consequences. In the case of convulsive (tonic-clonic) SE, both time points (t1 at 5 min and t2 at 30 min) are based on animal experiments and clinical research. This evidence is incomplete, and there is furthermore considerable variation, so these time points should be considered as the best estimates currently available. Data are not yet available for other forms of SE, but as knowledge and understanding increase, time points can be defined for specific forms of SE based on scientific evidence and incorporated into the definition, without changing the underlying concepts. A new diagnostic classification system of SE is proposed, which will provide a framework for clinical diagnosis, investigation, and therapeutic approaches for each patient. There are four axes: (1) semiology; (2) etiology; (3) electroencephalography (EEG) correlates; and (4) age. Axis 1 (semiology) lists different forms of SE divided into those with prominent motor systems, those without prominent motor systems, and currently indeterminate conditions (such as acute confusional states with epileptiform EEG patterns). Axis 2 (etiology) is divided into subcategories of known and unknown causes. Axis 3 (EEG correlates) adopts the latest recommendations by consensus panels to use the following descriptors for the EEG: name of pattern, morphology, location, time-related features, modulation, and effect of intervention. Finally, axis 4 divides age groups into neonatal, infancy, childhood, adolescent and adulthood, and elderly., (Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.)

The World Health Organization (WHO) International Classification of Diseases (ICD) has been used to classify causes of morbidity and mortality such as epilepsy for more than 50 years. The aims of this critical commentary are to do the following: (1) Introduce the ICD classification, summarize the ICD-9 and ICD-10 codes for epilepsy and seizures, and discuss the challenges of mapping epilepsy codes between these two versions; (2) discuss how the ICD-9 and ICD-10 relate to the revised International League Against Epilepsy (ILAE) terminology and concepts for classification of seizures and epilepsies; (3) discuss how ICD-coded data have been used for epilepsy care and research and briefly examine the potential impact of the international ICD-10 clinical modifications on research; (4) discuss the upcoming ICD-11 codes and the role of the epilepsy community in their development; and (5) discuss how the ICD-11 will conform more closely to the current ILAE terminology and classification of the epilepsies and seizures and its potential impact on clinical care, surveillance, and public health and research., (Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.)