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Epilepsy surgery is the therapy of choice for many patients with drug-resistant focal epilepsy. Recognizing and describing ictal and interictal patterns with intracranial electroencephalography (EEG) recordings is important in order to most efficiently leverage advantages of this technique to accurately delineate the seizure-onset zone before undergoing surgery. In this seminar in epileptology, we address learning objective "1.4.11 Recognize and describe ictal and interictal patterns with intracranial recordings" of the International League against Epilepsy curriculum for epileptologists. We will review principal considerations of the implantation planning, summarize the literature for the most relevant ictal and interictal EEG patterns within and beyond the Berger frequency spectrum, review invasive stimulation for seizure and functional mapping, discuss caveats in the interpretation of intracranial EEG findings, provide an overview on special considerations in children and in subdural grids/strips, and review available quantitative/signal analysis approaches. To be as practically oriented as possible, we will provide a mini atlas of the most frequent EEG patterns, highlight pearls for its not infrequently challenging interpretation, and conclude with two illustrative case examples. This article shall serve as a useful learning resource for trainees in clinical neurophysiology/epileptology by providing a basic understanding on the concepts of invasive intracranial EEG.

BACKGROUND: A third of people with juvenile myoclonic epilepsy (JME) are drug-resistant. Three-quarters have a seizure relapse when attempting to withdraw anti-seizure medication (ASM) after achieving seizure-freedom. It is currently impossible to predict who is likely to become drug-resistant and safely withdraw treatment. We aimed to identify predictors of drug resistance and seizure recurrence to allow for individualised prediction of treatment outcomes in people with JME. METHODS: We performed an individual participant data (IPD) meta-analysis based on a systematic search in EMBASE and PubMed - last updated on March 11, 2021 - including prospective and retrospective observational studies reporting on treatment outcomes of people diagnosed with JME and available seizure outcome data after a minimum one-year follow-up. We invited authors to share standardised IPD to identify predictors of drug resistance using multivariable logistic regression. We excluded pseudo-resistant individuals. A subset who attempted to withdraw ASM was included in a multivariable proportional hazards analysis on seizure recurrence after ASM withdrawal. The study was registered at the Open Science Framework (OSF; https://osf.io/b9zjc/). FINDINGS: Our search yielded 1641 articles; 53 were eligible, of which the authors of 24 studies agreed to collaborate by sharing IPD. Using data from 2518 people with JME, we found nine independent predictors of drug resistance: three seizure types, psychiatric comorbidities, catamenial epilepsy, epileptiform focality, ethnicity, history of CAE, family history of epilepsy, status epilepticus, and febrile seizures. Internal-external cross-validation of our multivariable model showed an area under the receiver operating characteristic curve of 0·70 (95%CI 0·68-0·72). Recurrence of seizures after ASM withdrawal (n = 368) was predicted by an earlier age at the start of withdrawal, shorter seizure-free interval and more currently used ASMs, resulting in an aver

Machine learning (ML) is increasingly recognized as a useful tool in healthcare applications, including epilepsy. One of the most important applications of ML in epilepsy is seizure detection and prediction, using wearable devices (WDs). However, not all currently available algorithms implemented in WDs are using ML. In this review, we summarize the state of the art of using WDs and ML in epilepsy, and we outline future development in these domains. There is published evidence for reliable detection of epileptic seizures using implanted electroencephalography (EEG) electrodes and wearable, non-EEG devices. Application of ML using the data recorded with WDs from a large number of patients could change radically the way we diagnose and manage patients with epilepsy.

Background and purpose: Some epilepsy syndromes (sleep-related epilepsies, SREs) have a strong link with sleep. Comorbid sleep disorders are common in patients with SRE and can exert a negative impact on seizure control and quality of life. Our purpose was to define the standard procedures for the diagnostic pathway of patients with possible SRE (scenario 1) and the general management of patients with SRE and comorbidity with sleep disorders (scenario 2). Methods: The project was conducted under the auspices of the European Academy of Neurology, the European Sleep Research Society and the International League Against Epilepsy Europe. The framework entailed the following phases: conception of the clinical scenarios; literature review; statements regarding the standard procedures. For the literature search a stepwise approach starting from systematic reviews to primary studies was applied. Published studies were identified from the National Library of Medicine’s MEDLINE database and Cochrane Library. Results: Scenario 1: Despite a low quality of evidence, recommendations on anamnestic evaluation and tools for capturing the event at home or in the laboratory are provided for specific SREs. Scenario 2: Early diagnosis and treatment of sleep disorders (especially respiratory disorders) in patients with SRE are likely to be beneficial for seizure control. Conclusions: Definitive procedures for evaluating patients with SRE are lacking. Advice is provided that could be of help for standardizing and improving the diagnostic approach of specific SREs. The importance of identifying and treating specific sleep disorders for the management and outcome of patients with SRE is underlined.

BACKGROUND AND PURPOSE: Accurate localization of the epileptic focus is essential for surgical treatment of patients with drug-resistant epilepsy. Electric source imaging (ESI) is increasingly used in pre-surgical evaluation. However, most previous studies have analysed interictal (II) discharges. Prospective studies comparing the feasibility and accuracy of II and ictal (IC) ESI are lacking.METHODS: We prospectively analysed long-term video-electroencephalography recordings (LTM) of patients admitted for pre-surgical evaluation. We performed ESI of II and IC signals using two methods, i.e. equivalent current dipole (ECD) and a distributed source model (DSM). LTM recordings employed the standard 25-electrode array (including inferior temporal electrodes). An age-matched template head model was used for source analysis. Results were compared with intracranial recordings, conventional neuroimaging methods [magnetic resonance imaging (MRI), positron emission tomography (PET), single-photon emission computed tomography (SPECT)] and outcome at 1 year after surgery.RESULTS: A total of 87 consecutive patients were analysed. ECD gave a significantly higher proportion of patients with localized focal abnormalities (94%) compared with MRI (70%), PET (66%) and SPECT (64%). Agreement between the ESI methods and intracranial recording was moderate to substantial (k = 0.56-0.79). A total of 54 patients were operated (47 patients more than 1 year ago) and 62% of them became seizure-free. The localization accuracy of II-ESI was 51% for DSM and 57% for ECD, and that for IC-ESI was 51% for DSM and 62% for ECD. The differences between the ESI methods were not significant. Differences in localization accuracy between ESI and MRI (55%), PET (33%) and SPECT (40%) were not significant.CONCLUSIONS: The II-ESI and IC-ESI of LTM data have high feasibility and their localization accuracy is similar to that of conventional neuroimaging methods.

OBJECTIVE: Despite optimal medical treatment, approximately one-third of patients with epilepsy continue to have seizures. Epilepsy surgery is widely accepted as a therapeutic option in the selected subset of patients with drug-resistant focal epilepsy. Here, we report the results of the Danish epilepsy surgery programme from 2009 to 2014.MATERIAL AND METHODS: A total of 169 consecutive patients, operated at Rigshospitalet, were included. Information was gathered from digital patient records. Before 1-year follow-up, two patients were lost to follow-up and three were referred to new surgery.RESULTS: The median years of drug resistance before operation were 11 years. At 1-year follow-up (n = 164), seizure outcomes were as follows: 65% Engel I (free from disabling seizures), 51% Engel IA (completely seizure free) and 9% Engel IV (no worthwhile improvement), and for patients operated in the medial temporal lobe (n = 114): 70% Engel I, 56% Engel IA, 5% Engel IV. The outcomes of the 53 patients needing intracranial EEG recording (ICR) were not significantly different from the patients only evaluated with surface EEG. None of the eight MRI-negative patients operated outside the medial temporal lobe after ICR were free of disabling seizures. 12% of MTLE patients developed de novo depression after epilepsy surgery despite good surgical outcome. Three patients required rehabilitation due to post-operative hemiplegia.CONCLUSION: The outcomes of the Danish epilepsy surgery programme align with international results found in recent meta-analyses. Serious complications to epilepsy surgery are seldom. In accordance with international recommendations, Danish drug-resistant patients should be referred to epilepsy surgery evaluation at an earlier stage of the disease.

BACKGROUND AND PURPOSE: The aim of this study was to describe clinical and paraclinical characteristics of all Danish patients who tested positive for anti-voltage-gated potassium channels (VGKC)-complex, anti-leucine-rich glioma-inactivated 1 (LGI1) and anti-contactin-associated protein-2 antibodies in the serum/cerebrospinal fluid between 2009 and 2013 with follow-up interviews in 2015 and 2016.METHODS: We evaluated antibody status, symptoms leading to testing, course of disease, suspected diagnosis and time of admission as well as diagnosis and treatment. All magnetic resonance imaging, electroencephalography and 18 F-fluorodeoxyglucose positron emission tomography scans were re-evaluated by experts in the field.RESULTS: A total of 28/192 patients tested positive for VGKC-complex antibodies by radioimmunoassay and indirect immunofluorescence; 17 had antibodies to LGI1 and 6/7 of the available cerebrospinal fluids from these patients were seropositive. These 17 patients all had a clinical phenotype appropriate to LGI1 antibodies. The remaining 11 were LGI1 negative (n = 4) or not tested (n = 7). Of these, two had a phenotype consistent with limbic encephalitis. The remaining phenotypes were Guillain-Barré syndrome, Creutzfeldt-Jakob disease, neuromyotonia and anti-N-methyl-D-aspartate receptor encephalitis. Magnetic resonance imaging abnormalities were demonstrated in 69% of the LGI1-positive patients. Two patients with normal magnetic resonance imaging demonstrated temporal lobe hypermetabolism using 18 F-fluorodeoxyglucose positron emission tomography. Abnormal electroencephalography recordings were found in 86% of the patients. Upon follow-up (median 3.2 years), the median modified Rankin Scale score of anti-LGI1-positive patients was 2 and only two patients reported seizures in the past year.CONCLUSIONS: Patients diagnosed with anti-LGI1 autoimmune encephalitis increased significantly from 2009 to 2014, probably due to increased awarene