Nocturnal visual hallucinations in patients with disorders of arousal: a novel behavioral and EEG pattern.

AIM: To investigate clinical and video-polysomnography (VPSG) findings of hallucinatory experiences in patients suffering from disorders of arousal (DOA) in the absence of other pathologies. METHODS: The authors retrospectively reviewed the records of 370 adults with DOA. Thirty (8.1%) patients concomitantly reported complex nocturnal visual hallucinations. VPSG recordings were scrutinized, and motor behavioral and electroencephalogram (EEG) patterns were classified according to previous descriptions of DOA. RESULTS: Thirty DOA patients reported seeing images of objects, people, and animals; either distorted, static, or mobile. The images disappeared with increased illumination in 80% of patients, and 23.3% reported preceding dream imagery. In addition to the classical DOA patterns on VPSG, a distinct pattern of behavioral and EEG manifestation associated with complex hallucinatory episodes was identified in 16 (53.3%) DOA patients. This consisted of low-voltage mixed-frequency EEG activity before eye opening that persisted while patients were observed staring or visually tracking before the onset of motor behavior. CONCLUSION: A novel, distinct behavioral and EEG pattern in patients with DOA and history of reported complex nocturnal visual hallucinations was identified. This may represent a unique phenotype of dissociation between sleep states that merits further investigation.

Neurocraft: software for microscale brain network dynamics.

The brain operates at millisecond timescales but despite of that, the study of its functional networks is approached with time invariant methods. Equally, for a variety of brain conditions treatment is delivered with fixed temporal protocols unable to monitor and follow the rapid progression and therefore the cycles of a disease. To facilitate the understanding of brain network dynamics we developed Neurocraft, a user friendly software suite. Neurocraft features a highly novel signal processing engine fit for tracking evolving network states with superior time and frequency resolution. A variety of analytics like dynamic connectivity maps, force-directed representations and propagation models, allow for the highly selective investigation of transient pathophysiological dynamics. In addition, machine-learning tools enable the unsupervised investigation and selection of key network features at individual and group-levels. For proof of concept, we compared six seizure-free and non seizure-free focal epilepsy patients after resective surgery using Neurocraft. The network features were calculated using 50 intracranial electrodes on average during at least 120 epileptiform discharges lasting less than one second, per patient. Powerful network differences were detected in the pre-operative data of the two patient groups (effect size = 1.27), suggesting the predictive value of dynamic network features. More than one million patients are treated with cardiac and neuro modulation devices that are unable to track the hourly or daily changes in a subject's disease. Decoding the dynamics of transition from normal to abnormal states may be crucial in the understanding, tracking and treatment of neurological conditions. Neurocraft provides a user-friendly platform for the research of microscale brain dynamics and a stepping stone for the personalised device-based adaptive neuromodulation in real-time.

Evaluation of absences and myoclonic seizures in adults with genetic (idiopathic) generalized epilepsy: a comparison between self-evaluation and objective evaluation based on home video-EEG telemetry.

People with focal epilepsies are known to under-document their seizures, but there is no data on self-documentation in adults with genetic (idiopathic) generalized epilepsy (GGE/IGE). We assessed the accuracy of self-evaluation of typical absences (TA) or myoclonic seizures (MS) in adults with IGE based on home video-EEG telemetry (HVET). Patients' own estimates were compared to the objective count of definite TA and MS, performed visually. We considered definite TA as generalized spike-wave discharges (GSWD) that met any of the following criteria: 1) coinciding with clear behavioural arrest on video, 2) followed after a few seconds by positive indication that an absence occurred, or 3) in the absence of video, consistently coinciding with clear motor arrest, as evidenced by interruption of continuous muscle activity. For each patient, we also classified probable TA as GSWDs that were longer than those corresponding to the shortest definite TA on HVET or based on the most recent sleep-deprived EEG (SDEEG). From the first 300 consecutive adults who had HVET, 24 had IGE with TA and / or MS; 23 were women. Only one patient had newly diagnosed IGE. Erroneous self-assessment of TA and MS was noted in 16/24 patients (66.7%). Seizures were overestimated in nine (37.5%) and underestimated in seven (29.2%). Only one patient (4.2%) documented all her TA and MS without false-positive estimates. Overestimation (but not underestimation) of TA on HVET could be predicted when patients reported daily or multiple weekly TA and a recent SDEEG was either normal or contained only subclinical GSWD (p=0.0095). Under- and over-self-documentation of TA and MS occurred in two thirds of adults with GGE/IGE, with substantial impact on their outpatient management and treatment. Diagnostic HVET is a useful tool for the detection of erroneous self-evaluation in these patients.

Standard procedures for the diagnostic pathway of sleep-related epilepsies and comorbid sleep disorders: A European Academy of Neurology, European Sleep Research Society and International League against Epilepsy-Europe consensus review.

BACKGROUND: Some epilepsy syndromes (sleep-related epilepsies [SRE]) 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. PURPOSES: 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 (EAN), the European Sleep Research Society (ESRS) and the International League against Epilepsy (ILAE) Europe. The framework of the document entailed the following phases: conception of the clinical scenarios; literature review; statements regarding the standard procedures. For literature search a step-wise 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, tools for capturing the event at home or in the laboratory are provided for specific SRE. Scenario 2: Early diagnosis and treatment of sleep disorders (especially respiratory disorders) in patients with SRE are likely to be beneficial for seizures control. CONCLUSIONS: Definitive procedures for evaluating patients with SRE are lacking. We provide advice that could be of help for standardising and improving the diagnostic approach of specific SRE. The importance of identifying and treating specific sleep disorders for the management and outcome of patients with SRE is underlined.

How to diagnose and classify idiopathic (genetic) generalized epilepsies.

Idiopathic or genetic generalized epilepsies (IGE) constitute an electroclinically well-defined group that accounts for almost one third of all people with epilepsy. They consist of four well-established syndromes and some other rarer phenotypes. The main four IGEs are juvenile myoclonic epilepsy, childhood absence epilepsy, juvenile absence epilepsy and IGE with generalized tonic-clonic seizures alone. There are three main seizure types in IGE, namely generalized tonic-clonic seizures, typical absences and myoclonic seizures, occurring either alone or in any combination. Diagnosing IGEs requires a multidimensional approach. The diagnostic process begins with a thorough medical history with a specific focus on seizure types, age at onset, timing and triggers. Comorbidities and family history should be questioned comprehensively. The EEG can provide valuable information for the diagnosis, including specific IGE syndromes, and therefore contribute to their optimal pharmacological treatment and management.

Heritability of alpha and sensorimotor network changes in temporal lobe epilepsy.

OBJECTIVE: Electroencephalography (EEG) features in the alpha band have been shown to differ between people with epilepsy and healthy controls. Here, in a group of patients with mesial temporal lobe epilepsy (mTLE), we seek to confirm these EEG features, and using simultaneous functional magnetic resonance imaging, we investigate whether brain networks related to the alpha rhythm differ between patients and healthy controls. Additionally, we investigate whether alpha abnormalities are found as an inherited endophenotype in asymptomatic relatives. METHODS: We acquired scalp EEG and simultaneous EEG and functional magnetic resonance imaging in 24 unrelated patients with unilateral mTLE, 23 asymptomatic first-degree relatives of patients with mTLE, and 32 healthy controls. We compared peak alpha power and frequency from electroencephalographic data in patients and relatives to healthy controls. We identified brain networks associated with alpha oscillations and compared these networks in patients and relatives to healthy controls. RESULTS: Patients had significantly reduced peak alpha frequency (PAF) across all parietal and occipital electrodes. Asymptomatic relatives also had significantly reduced PAF over 14 of 17 parietal and occipital electrodes. Both patients and asymptomatic relatives showed a combination of increased activation and a failure of deactivation in relation to alpha oscillations compared to healthy controls in the sensorimotor network. INTERPRETATION: Genetic factors may contribute to the shift in PAF and alterations in brain networks related to alpha oscillations. These may not entirely be a consequence of anti-epileptic drugs, seizures or hippocampal sclerosis and deserve further investigation as mechanistic contributors to mTLE.

Vagus nerve stimulation for drug-resistant epilepsy.

Vagus nerve stimulation (VNS) is a neuromodulatory therapeutic option for drug-resistant epilepsy. In randomised controlled trials, VNS implantation has resulted in over 50% reduction in seizure frequency in 26%-40% of patients within 1 year. Long-term uncontrolled studies suggest better responses to VNS over time; however, the assessment of other potential predictive factors has led to contradictory results. Although initially designed for managing focal seizures, its use has been extended to other forms of drug-resistant epilepsy. In this review, we discuss the evidence supporting the use of VNS, its impact on seizure frequency and quality of life, and common adverse effects of this therapy. We also include practical guidance for the approach to and the management of patients with VNS in situ.

Cross-subject network investigation of the EEG microstructure: A sleep spindles study.

BACKGROUND: The microstructural EEG elements and their functional networks relate to many neurophysiological functions of the brain and can reveal abnormalities. Despite the blooming variety of methods for estimating connectivity in the EEG of a single subject, a common pitfall is seen in relevant studies; grand averaging is used for estimating the characteristic connectivity patterns of a group of subjects. This averaging may distort results and fail to account for the internal variability of connectivity results across the subjects of a group. NEW METHOD: In this study, we propose a novel methodology for the cross-subject network investigation of EEG graphoelements. We used dimensionality reduction techniques in order to reveal internal connectivity properties and to examine how consistent these are across a number of subjects. In addition, graph theoretical measures were utilized to prioritize regions according to their network attributes. RESULTS: As proof of concept, we applied this method on fast sleep spindles across 10 healthy subjects. Neurophysiological findings revealed subnetworks of the spindle events across subjects, highlighting a predominance for occipito-parietal areas and their connectivity with frontal regions. COMPARISON WITH EXISTING METHODS: This is a new approach for the examination of within-group connectivities in EEG research. The results accounted for more than 85% of the overall data variance and the detected subnetworks were found to be meaningful down-projections of the grand average of the group, suggesting sufficient performance for the proposed methodology. CONCLUSION: We conclude that the proposed methodology can serve as an observatory tool for the EEG connectivity patterns across subjects, providing a supplementary analysis of the existing topography techniques.

Abnormal temporal lobe morphology in asymptomatic relatives of patients with hippocampal sclerosis: A replication study.

We investigated gray and white matter morphology in patients with mesial temporal lobe epilepsy with hippocampal sclerosis (mTLE+HS) and first-degree asymptomatic relatives of patients with mTLE+HS. Using T1-weighted magnetic resonance imaging (MRI), we sought to replicate previously reported findings of structural surface abnormalities of the anterior temporal lobe in asymptomatic relatives of patients with mTLE+HS in an independent cohort. We performed whole-brain MRI in 19 patients with mTLE+HS, 14 first-degree asymptomatic relatives of mTLE+HS patients, and 32 healthy control participants. Structural alterations in patients and relatives compared to controls were assessed using automated hippocampal volumetry and cortical surface-based morphometry. We replicated previously reported cortical surface area contractions in the ipsilateral anterior temporal lobe in both patients and relatives compared to healthy controls, with asymptomatic relatives showing similar but less extensive changes than patients. These findings suggest morphologic abnormality in asymptomatic relatives of mTLE+HS patients, suggesting an inherited brain structure endophenotype.

A hemodynamic network involving the insula, the cingulate, and the basal forebrain correlates with EEG synchronization phases of sleep instability.

The cyclic alternating pattern (CAP) encompasses the pseudoperiodic appearance of synchronized brain waves and rhythms and is considered a regulator of the nonrapid eye movement (NREM) sleep vigilance level, reflecting sleep instability. To determine the brain regions responsible for this phenomenon, we scored and analyzed sleep functional magnetic resonance imaging data acquired with simultaneous electroencephalography (EEG-fMRI). Group analysis revealed a set of brain areas showing statistically significant blood oxygen-level dependent signal correlated positively with the synchronization phase of the CAP, most prominent being the insula, the middle cingulate gyrus, and the basal forebrain. These areas may form a network acting as a synchronization pacemaker, controlling the level of NREM sleep vigilance and the sleeper's arousability.

Epileptology of the first tonic-clonic seizure in adults and prediction of seizure recurrence.

The risk of seizure recurrence after a first unprovoked seizure is influenced by certain risk factors. To understand their effect in people with early diagnosed new epilepsy, we assessed the risk of recurrence of focal to bilateral tonic-clonic or generalized tonic-clonic seizures and the associated factors in a clinically well-characterized cohort of adults with a first unprovoked tonic-clonic seizure. We prospectively studied 150 consecutive adults with a first unprovoked tonic-clonic seizure and full clinical, EEG, and brain imaging assessment within the first four weeks. New epilepsy was diagnosed and classified according to the International League Against Epilepsy criteria. Time to second focal to bilateral tonic-clonic or generalized tonic-clonic seizure was analysed using the Kaplan-Meier method. Early diagnosis of new epilepsy, including type or syndrome and aetiology, was possible in 109 patients (72.7%). The diagnostic yield of sleep-deprived EEG was high in both genetic and non-genetic localized focal epilepsies. A second focal to bilateral tonic-clonic or generalized tonic-clonic seizure occurred in 100 patients (66.7%) during a three-year mean observation period. The risk was higher in non-genetic focal epilepsies and lower in genetic epilepsies. Concurrent absences or myoclonic seizures and a first occurrence after awakening were predictors of a second generalized tonic-clonic seizure in patients with genetic generalized epilepsy, while diagnosis of temporal or frontal lobe epilepsy, focal EEG discharges, and focal changes on brain imaging were related to an increased risk of focal to bilateral tonic-clonic seizure recurrence, showing additive effects. Identifiable modulators or triggers for the first tonic-clonic seizure, early treatment, and older age showed inverse association. The risk of a second generalized or focal to bilateral tonic-clonic seizure and the factors involved vary across epilepsy aetiologies and syndromes. Early diagnosis and classification of new epilepsy is possible in most patients and may enable important adjustments to their management and treatment.

The role of EEG in the diagnosis and classification of the epilepsy syndromes: a tool for clinical practice by the ILAE Neurophysiology Task Force (Part 1).

The concept of epilepsy syndromes, introduced in 1989, was defined as "clusters of signs and symptoms customarily occurring together". Definition of epilepsy syndromes based on electro-clinical features facilitated clinical practice and, whenever possible, clinical research in homogeneous groups of patients with epilepsies. Progress in the fields of neuroimaging and genetics made it rapidly clear that, although crucial, the electro-clinical description of epilepsy syndromes was not sufficient to allow much needed development of targeted therapies and a better understanding of the underlying pathophysiological mechanisms of seizures. The 2017 ILAE position paper on Classification of the Epilepsies recognized that "as a critical tool for the practicing clinician, epilepsy classification must be relevant and dynamic to changes in thinking". The concept of "epilepsy syndromes" evolved, incorporating issues related to aetiologies and comorbidities. A comprehensive update (and revision where necessary) of the EEG diagnostic criteria in the light of the 2017 revised terminology and concepts was deemed necessary. The work was commissioned by the Neurophysiology Task Force of the ILAE Committee on the Diagnostic Methods. Diagnostic criteria and recording procedures were developed by group consensus, reached through an "informal", internal decision-making process. Each working group member was allocated a number of syndromes, and a standard structured template was used. International literature was extensively reviewed. We developed a simple diagnostic system that is applicable to all epilepsy syndromes which allows the physician (i) to rate the strength of EEG diagnosis (degree of diagnostic certainty) by weighting EEG findings in relation to the available clinical information or the specific clinical question, and ii) to suggest further EEG diagnostics where conclusive diagnostic evidence is lacking. We also propose a system of syndrome-specific recording protocols that, used with the relevant clinical presentation or specific clinical question, may maximize activation of epileptic discharges and ultimately help with standardization of EEG recording across departments, worldwide. Because recording methodology also depends on available resources, a two-tier system was developed to embrace clinical EEG services in resource-limited and industrialized countries. A clinical practice statement for each of the epilepsy syndromes discussed underscores the crucial role of the clinical information with regards to both the optimization of the EEG recording and mainly its meaningful interpretation. Part I covers Genetic (Idiopathic) generalized epilepsies and syndromes, Reflex epilepsies, structural and genetic focal (lobar) syndromes and Progressive Myoclonus Epilepsies [Published with educational EEG plates on www.epilepticdisorders.com].

Spatiotemporal propagation patterns of generalized ictal spikes in childhood absence epilepsy.

OBJECTIVE: This work investigates the spatial distribution in time of generalized ictal spikes in the typical absences of childhood absence epilepsy (CAE). METHODS: We studied twelve children with CAE, who had more than two typical absences during their routine video-EEG. Seizures were identified, and ictal spikes were marked over the maximum electronegative peak, clustered, waveform-averaged and spatiotemporaly analyzed in 2D electrode space. RESULTS: Consistency of spatiotemporal patterns of ictal spikes was high between the absences of the same child, but low between children. Three main discharge patterns were identified: of anterio-posterior propagation, of posterio-anterior propagation and confined to the frontal/prefrontal regions. In 4 patients, the propagation patterns transformed during the seizure into either a lateralized diminished or a non-lateralized reverse direction form. Most spikes originated fronto-temporaly, all maximized over the frontal/prefrontal electrodes and mostly decayed prefrontaly. In 4 patients, lateralized propagation patterns were identified. CONCLUSIONS: Ictal spike propagation patterns suggest that epileptogenic CAE networks are personalized, interconnect distal areas in the brain - not the entire cortex - with a tendency to generate bilateral symmetrical discharges, sometimes unsuccessfully. The transformation of propagation patterns during the seizure indicates the existence of dynamic interplay within epileptogenic networks. SIGNIFICANCE: Our results support the revised concept of ictogenesis of ILAE definition in genetic (also known as idiopathic) generalized epilepsies. Understanding the focal features in CAE avoids misdiagnosis as focal epilepsy and inappropriate treatment.

Topography of generalized periodic epileptiform discharges in postanoxic nonconvulsive status epilepticus.

We studied slow (≤2.5 Hz) nonevolving generalized periodic epileptiform discharges (GPEDs) in the electroencephalogram (EEG) of comatose patients after cardiac arrest (CA) in search of evidence that could assist early diagnosis of possible hypoxic nonconvulsive status epilepticus (NCSE) and its differentiation from terminal brain anoxia (BA), which can present with a similar EEG pattern. We investigated the topography of the GPEDs in the first post-CA EEGs of 13 patients, using voltage-mapping, and compared findings between two patients with NCSE and GPEDs > 2.5 Hz (group 1), and 11 with GPEDs ≤ 2 Hz, of whom six had possible NCSE (group 2) and five had terminal BA (group 3). Voltage mapping showed frontal maximum for the negative phase of the GPEDs in all patients of groups 1 and 2, but not in any of the patients of group 3, who invariably showed maximization of the negative phase posteriorly. Morphology, amplitude, and duration of the GPEDs varied across the groups, without distinctive features for possible NCSE. These findings provide evidence that, in hypoxic coma after CA with slow GPEDs, anterior topography of the maximum GPED negativity on voltage mapping may be a distinctive biomarker for possible NCSE contributing to the coma.

The role of EEG in the diagnosis and classification of the epilepsy syndromes: a tool for clinical practice by the ILAE Neurophysiology Task Force (Part 2).

The concept of epilepsy syndromes, introduced in 1989, was defined as "clusters of signs and symptoms customarily occurring together". Definition of epilepsy syndromes based on electro-clinical features facilitated clinical practice and, whenever possible, clinical research in homogeneous groups of patients with epilepsies. Progress in the fields of neuroimaging and genetics made it rapidly clear that, although crucial, the electro-clinical description of epilepsy syndromes was not sufficient to allow much needed development of targeted therapies and a better understanding of the underlying pathophysiological mechanisms of seizures. The 2017 ILAE position paper on Classification of the Epilepsies recognized that "as a critical tool for the practicing clinician, epilepsy classification must be relevant and dynamic to changes in thinking". The concept of "epilepsy syndromes" evolved, incorporating issues related to aetiologies and comorbidities. A comprehensive update (and revision where necessary) of the EEG diagnostic criteria in the light of the 2017 revised terminology and concepts was deemed necessary. Part 2 covers the neonatal and paediatric syndromes in accordance with the age of onset. [Published with educational EEG plates at www.epilepticdisorders.com].

TMS combined with EEG in genetic generalized epilepsy: A phase II diagnostic accuracy study.

OBJECTIVES: (A) To develop a TMS-EEG stimulation and data analysis protocol in genetic generalized epilepsy (GGE). (B) To investigate the diagnostic accuracy of TMS-EEG in GGE. METHODS: Pilot experiments resulted in the development and optimization of a paired-pulse TMS-EEG protocol at rest, during hyperventilation (HV), and post-HV combined with multi-level data analysis. This protocol was applied in 11 controls (C) and 25 GGE patients (P), further dichotomized into responders to antiepileptic drugs (R, n=13) and non-responders (n-R, n=12).Features (n=57) extracted from TMS-EEG responses after multi-level analysis were given to a feature selection scheme and a Bayesian classifier, and the accuracy of assigning participants into the classes P-C and R-nR was computed. RESULTS: On the basis of the optimal feature subset, the cross-validated accuracy of TMS-EEG for the classification P-C was 0.86 at rest, 0.81 during HV and 0.92 at post-HV, whereas for R-nR the corresponding figures are 0.80, 0.78 and 0.65, respectively. Applying a fusion approach on all conditions resulted in an accuracy of 0.84 for the classification P-C and 0.76 for the classification R-nR. CONCLUSION: TMS-EEG can be used for diagnostic purposes and for assessing the response to antiepileptic drugs. SIGNIFICANCE: TMS-EEG holds significant diagnostic potential in GGE.

A computational biomarker of idiopathic generalized epilepsy from resting state EEG.

Epilepsy is one of the most common serious neurologic conditions. It is characterized by the tendency to have recurrent seizures, which arise against a backdrop of apparently normal brain activity. At present, clinical diagnosis relies on the following: (1) case history, which can be unreliable; (2) observation of transient abnormal activity during electroencephalography (EEG), which may not be present during clinical evaluation; and (3) if diagnostic uncertainty occurs, undertaking prolonged monitoring in an attempt to observe EEG abnormalities, which is costly. Herein, we describe the discovery and validation of an epilepsy biomarker based on computational analysis of a short segment of resting-state (interictal) EEG. Our method utilizes a computer model of dynamic networks, where the network is inferred from the extent of synchrony between EEG channels (functional networks) and the normalized power spectrum of the clinical data. We optimize model parameters using a leave-one-out classification on a dataset comprising 30 people with idiopathic generalized epilepsy (IGE) and 38 normal controls. Applying this scheme to all 68 subjects we find 100% specificity at 56.7% sensitivity, and 100% sensitivity at 65.8% specificity. We believe this biomarker could readily provide additional support to the diagnostic process.

Idiopathic focal epilepsies: the "lost tribe".

The term idiopathic focal epilepsies of childhood (IFE) is not formally recognised by the ILAE in its 2010 revision (Berg et al., 2010), nor are its members and boundaries precisely delineated. The IFEs are amongst the most commonly encountered epilepsy syndromes affecting children. They are fascinating disorders that hold many "treats" for both clinicians and researchers. For example, the IFEs pose many of the most interesting questions central to epileptology: how are functional brain networks involved in the manifestation of epilepsy? What are the shared mechanisms of comorbidity between epilepsy and neurodevelopmental disorders? How do focal EEG discharges impact cognitive functioning? What explains the age-related expression of these syndromes? Why are EEG discharges and seizures so tightly locked to slow-wave sleep? In the last few decades, the clinical symptomatology and the respective courses of many IFEs have been described, although they are still not widely appreciated beyond the specialist community. Most neurologists would recognise the core syndromes of IFE to comprise: benign epilepsy of childhood with centro-temporal spikes or Rolandic epilepsy (BECTS/RE); Panayiotopoulos syndrome; and the idiopathic occipital epilepsies (Gastaut and photosensitive types). The Landau-Kleffner syndrome and the related (idiopathic) epilepsy with continuous spikes and waves in sleep (CSWS or ESES) are also often included, both as a consequence of the shared morphology of the interictal discharges and their potential evolution from core syndromes, for example, CSWS from BECTS. Atypical benign focal epilepsy of childhood also has shared electro-clinical features warranting inclusion. In addition, a number of less well-defined syndromes of IFE have been proposed, including benign childhood seizures with affective symptoms, benign childhood epilepsy with parietal spikes, benign childhood seizures with frontal or midline spikes, and benign focal seizures of adolescence. The term "benign" is often used in connection with the IFEs and is increasingly being challenged. Certainly most of these disorders are not associated with the devastating cognitive and behavioural problems seen with early childhood epileptic encephalopathies, such as West or Dravet syndromes. However, it is clear that specific, and sometimes persistent, neuropsychological deficits in attention, language and literacy accompany many of the IFEs that, when multiplied by the large numbers affected, make up a significant public health problem. Understanding the nature, distribution, evolution, risk and management of these is an important area of current research. A corollary to such questions regarding comorbidities is the role of focal interictal spikes and their enduring impact on cognitive functioning. What explains the paradox that epilepsies characterised by abundant interictal epileptiform abnormalities are often associated with very few clinical seizures? This is an exciting area in both clinical and experimental arenas and will eventually have important implications for clinical management of the whole child, taking into account not just seizures, but also adaptive functioning and quality of life. For several decades, we have accepted an evidence-free approach to using or not using antiepileptic drugs in IFEs. There is huge international variation and only a handful of studies examining neurocognitive outcomes. Clearly, this is a situation ready for an overhaul in practice. Fundamental to understanding treatment is knowledge of aetiology. In recent years, there have been several significant discoveries in IFEs from studies of copy number variation, exome sequencing, and linkage that prompt reconsideration of the "unknown cause" classification and strongly suggest a genetic aetiology. The IFE are strongly age-related, both with regards to age of seizure onset and remission. Does this time window solely relate to a similar age-related gene expression, or are there epigenetic factors involved that might also explain low observed twin concordance? The genetic (and epigenetic) models for different IFEs, their comorbidities, and their similarities to other neurodevelopmental disorders deserve investigation in the coming years. In so doing, we will probably learn much about normal brain functioning. This is because these disorders, perhaps more than any other human brain disease, are disorders of functional brain systems (even though these functional networks may not yet be fully defined). In June 2012, an international group of clinical and basic science researchers met in London under the auspices of the Waterloo Foundation to discuss and debate these issues in relation to IFEs. This Waterloo Foundation Symposium on the Idiopathic Focal Epilepsies: Phenotype to Genotype witnessed presentations that explored the clinical phenomenology, phenotypes and endophenotypes, and genetic approaches to investigation of these disorders. In parallel, the impact of these epilepsies on children and their families was reviewed. The papers in this supplement are based upon these presentations. They represent an updated state-of-the-art thinking on the topics explored. The symposium led to the formation of international working groups under the umbrella of "Luke's Idiopathic Focal Epilepsy Project" to investigate various aspects of the idiopathic focal epilepsies including: semiology and classification, genetics, cognition, sleep, high-frequency oscillations, and parental resources (see www.childhood-epilepsy.org). The next sponsored international workshop, in June 2014, was on randomised controlled trials in IFEs and overnight learning outcome measures.

Connectivity Measures in EEG Microstructural Sleep Elements.

During Non-Rapid Eye Movement sleep (NREM) the brain is relatively disconnected from the environment, while connectedness between brain areas is also decreased. Evidence indicates, that these dynamic connectivity changes are delivered by microstructural elements of sleep: short periods of environmental stimuli evaluation followed by sleep promoting procedures. The connectivity patterns of the latter, among other aspects of sleep microstructure, are still to be fully elucidated. We suggest here a methodology for the assessment and investigation of the connectivity patterns of EEG microstructural elements, such as sleep spindles. The methodology combines techniques in the preprocessing, estimation, error assessing and visualization of results levels in order to allow the detailed examination of the connectivity aspects (levels and directionality of information flow) over frequency and time with notable resolution, while dealing with the volume conduction and EEG reference assessment. The high temporal and frequency resolution of the methodology will allow the association between the microelements and the dynamically forming networks that characterize them, and consequently possibly reveal aspects of the EEG microstructure. The proposed methodology is initially tested on artificially generated signals for proof of concept and subsequently applied to real EEG recordings via a custom built MATLAB-based tool developed for such studies. Preliminary results from 843 fast sleep spindles recorded in whole night sleep of 5 healthy volunteers indicate a prevailing pattern of interactions between centroparietal and frontal regions. We demonstrate hereby, an opening to our knowledge attempt to estimate the scalp EEG connectivity that characterizes fast sleep spindles via an "EEG-element connectivity" methodology we propose. The application of the latter, via a computational tool we developed suggests it is able to investigate the connectivity patterns related to the occurrence of EEG microstructural elements. Network characterization of specified physiological or pathological EEG microstructural elements can potentially be of great importance in the understanding, identification, and prediction of health and disease.