Epileptiform Discharges In Epilepsy Research Articles

Circadian distribution of epileptiform discharges in epilepsy: Candidate mechanisms of variability.

Epilepsy is a serious neurological disorder characterised by a tendency to have recurrent, spontaneous, seizures. Classically, seizures are assumed to occur at random. However, recent research has uncovered underlying rhythms both in seizures and in key signatures of epilepsy-so-called interictal epileptiform activity-with timescales that vary from hours and days through to months. Understanding the physiological mechanisms that determine these rhythmic patterns of epileptiform discharges remains an open question. Many people with epilepsy identify precipitants of their seizures, the most common of which include stress, sleep deprivation and fatigue. To quantify the impact of these physiological factors, we analysed 24-hour EEG recordings from a cohort of 107 people with idiopathic generalized epilepsy. We found two subgroups with distinct distributions of epileptiform discharges: one with highest incidence during sleep and the other during day-time. We interrogated these data using a mathematical model that describes the transitions between background and epileptiform activity in large-scale brain networks. This model was extended to include a time-dependent forcing term, where the excitability of nodes within the network could be modulated by other factors. We calibrated this forcing term using independently-collected human cortisol (the primary stress-responsive hormone characterised by circadian and ultradian patterns of secretion) data and sleep-staged EEG from healthy human participants. We found that either the dynamics of cortisol or sleep stage transition, or a combination of both, could explain most of the observed distributions of epileptiform discharges. Our findings provide conceptual evidence for the existence of underlying physiological drivers of rhythms of epileptiform discharges. These findings should motivate future research to explore these mechanisms in carefully designed experiments using animal models or people with epilepsy.

Detection of mesial temporal lobe epileptiform discharges on intracranial electrodes using deep learning

ObjectiveDevelop a high-performing algorithm to detect mesial temporal lobe (mTL) epileptiform discharges on intracranial electrode recordings. MethodsAn epileptologist annotated 13,959 epileptiform discharges from a dataset of intracranial EEG recordings from 46 epilepsy patients. Using this dataset, we trained a convolutional neural network (CNN) to recognize mTL epileptiform discharges from a single intracranial bipolar channel. The CNN outputs from multiple bipolar channel inputs were averaged to generate the final detector output. Algorithm performance was estimated using a nested 5-fold cross-validation. ResultsOn the receiver-operating characteristic curve, our algorithm achieved an area under the curve (AUC) of 0.996 and a partial AUC (for specificity > 0.9) of 0.981. AUC on a precision-recall curve was 0.807. A sensitivity of 84% was attained at a false positive rate of 1 per minute. 35.9% of the false positive detections corresponded to epileptiform discharges that were missed during expert annotation. ConclusionsUsing deep learning, we developed a high-performing, patient non-specific algorithm for detection of mTL epileptiform discharges on intracranial electrodes. SignificanceOur algorithm has many potential applications for understanding the impact of mTL epileptiform discharges in epilepsy and on cognition, and for developing therapies to specifically reduce mTL epileptiform activity.

Mobile EEG in epilepsy

The sensitivity of routine EEG recordings for interictal epileptiform discharges in epilepsy is limited. In some patients, inpatient video-EEG may be performed to increase the likelihood of finding abnormalities. Although many agree that home EEG recordings may provide a cost-effective alternative to these recordings, their use is still not introduced everywhere. We surveyed Dutch neurologists and patients and evaluated a novel mobile EEG device (Mobita, TMSi). Key specifications were compared with three other current mobile EEG devices. We shortly discuss algorithms to assist in the review process. Thirty percent (33 out of 109) of Dutch neurologists reported that home EEG recordings are used in their hospital. The majority of neurologists think that mobile EEG can have additional value in investigation of unclear paroxysms, but not in the initial diagnosis after a first seizure. Poor electrode contacts and signal quality, limited recording time and absence of software for reliable and effective assistance in the interpretation of EEGs have been important constraints for usage, but in recent devices discussed here, many of these problems have been solved. The majority of our patients were satisfied with the home EEG procedure and did not think that our EEG device was uncomfortable to wear, but they did feel uneasy wearing it in public.

Negative BOLD responses to epileptic spikes

Simultaneous electroencephalogram/functional magnetic resonance imaging (EEG-fMRI) during interictal epileptiform discharges can result in positive (activation) and negative (deactivation) changes in the blood oxygenation level-dependent (BOLD) signal. Activation probably reflects increased neuronal activity and energy demand, but deactivation is more difficult to explain. Our objective was to evaluate the occurrence and significance of deactivations related to epileptiform discharges in epilepsy. We reviewed all EEG-fMRI studies from our database, identified those with robust responses (P = 0.01, with > or =5 contiguous voxels with a |t| > 3.1, including > or =1 voxel at |t| > 5.0), and divided them into three groups: activation (A = 8), deactivation (D = 9), and both responses (AD = 43). We correlated responses with discharge type and location and evaluated their spatial relationship with regions involved in the "default" brain state (Raichle et al. [2001]: Proc Natl Acad Sci 98:676-682]. Deactivations were seen in 52/60 studies (AD + D): 26 related to focal discharges, 12 bilateral, and 14 generalized. Deactivations were usually distant from anatomical areas related to the discharges and more frequently related to polyspike- and spike-and-slow waves than to spikes. The "default" pattern occurred in 10/43 AD studies, often associated with bursts of generalized discharges. In conclusion, deactivations are frequent, mostly with concomitant activation, for focal and generalized discharges. Discharges followed by a slow wave are more likely to result in deactivation, suggesting neuronal inhibition as the underlying phenomenon. Involvement of the "default" areas, related to bursts of generalized discharges, provides evidence of a subclinical effect of the discharges, temporarily suspending normal brain function in the resting state.

EEG/Functional MRI in Epilepsy: The Queen Square Experience

The recording of EEG during functional MRI scanning (EEG/fMRI) has opened up new dimensions in brain research. The simultaneous recording of EEG activity and its temparospatial haemodynamic correlates is a powerful tool in the non-invasive mapping of normal and pathological brain function. The technological constraints imposed by having a conductor (the EEG) within the magnetic environment of the MRI scanner have been sufficiently overcome for high quality EEG recording during MRI. The initial applications of EEG/fMRI were in the study of epileptiform discharges in epilepsy. This has been rapidly followed by studies of normal EEG rhythms and evoked response in healthy subjects. The ability to map brain areas involved in the generation of epileptiform discharges recorded on the surface EEG has been shown using EEG/fMRI in patients with epilepsy. This has potential clinical applications in providing additional localizing information in the pre-surgical workup of epilepsy patients and in gaining a greater understanding of the neurobiology of interictal epileptiform discharges and epileptic seizures. In this review we address the issues in recording EEG during fMRI and review the application of EEG/fMRI in the study of patients with epilepsy at our centre.