EEG-to-EEG: Scalp-to-Intracranial EEG Translation Using a Combination of Variational Autoencoder and Generative Adversarial Networks.

A generative adversarial network (GAN) makes it possible to map a data sample from one domain to another one. It has extensively been employed in image-to-image and text-to image translation. We propose an EEG-to-EEG translation model to map the scalp-mounted EEG (scEEG) sensor signals to intracranial EEG (iEEG) sensor signals recorded by foramen ovale sensors inserted into the brain.

Lack of context modulation in human single neuron responses in the medial temporal lobe.

In subjects implanted with intracranial electrodes, we use two different stories involving the same person (or place) to evaluate whether and to what extent context modulates human single-neuron responses. Nearly all neurons (97% during encoding and 100% during recall) initially responding to a person/place do not modulate their response with context. Likewise, nearly none (<1%) of the initially non-responsive neurons show conjunctive coding, responding to particular persons/places in a particular context during the tasks.

Do Interictal Epileptiform Discharges and Brain Responses to Electrical Stimulation Come From the Same Location? An Advanced Source Localization Solution.

Identification of seizure sources in the brain is of paramount importance, particularly for drug-resistant epilepsy patients who may require surgical operation. Interictal epileptiform discharges (IEDs), which may or may not be frequent, are known to originate from seizure networks. Delayed responses (DRs) to brain electrical stimulation have been recently discovered.

A review of signal processing and machine learning techniques for interictal epileptiform discharge detection.

Brain interictal epileptiform discharges (IEDs), as one of the hallmarks of epileptic brain, are transient events captured by electroencephalogram (EEG). IEDs are generated by seizure networks, and they occur between seizures (interictal periods). The development of a robust method for IED detection could be highly informative for clinical treatment procedures and epileptic patient management.

Neuromodulation Techniques in Children with Super-Refractory Status Epilepticus.

Status epilepticus (SE) is a life-threatening condition and medical emergency which can have lifelong consequences, including neuronal death and alteration of neuronal networks, resulting in long-term neurologic and cognitive deficits in children. When standard pharmacological treatment for SE is not successful in controlling seizures, the condition evolves to refractory SE (rSE) and finally to super-refractory SE (srSE) if it exceeds 24 h despite using anaesthetics. In this systematic review, we present literature data on the potential uses of clinical neuromodulation techniques for the management of srSE in children, including electroconvulsive therapy, vagus nerve stimulation, and deep brain stimulation.

Localization of Epileptic Brain Responses to Single-Pulse Electrical Stimulation by Developing an Adaptive Iterative Linearly Constrained Minimum Variance Beamformer.

Delayed responses (DRs) to single pulse electrical stimulation (SPES) in patients with severe refractory epilepsy, from their intracranial recordings, can help to identify regions associated with epileptogenicity. Automatic DR localization is a large step in speeding up the identification of epileptogenic focus. Here, for the first time, an adaptive iterative linearly constrained minimum variance beamformer (AI-LCMV) is developed and employed to localize the DR sources from intracranial electroencephalogram (EEG) recorded using subdural electrodes.

Separating Inhibitory and Excitatory Responses of Epileptic Brain to Single-Pulse Electrical Stimulation.

To enable an accurate recognition of neuronal excitability in an epileptic brain for modeling or localization of epileptic zone, here the brain response to single-pulse electrical stimulation (SPES) has been decomposed into its constituent components using adaptive singular spectrum analysis (SSA). Given the response at neuronal level, these components are expected to be the inhibitory and excitatory components. The prime objective is to thoroughly investigate the nature of delayed responses (elicited between 100[Formula: see text]ms-1 s after SPES) for localization of the epileptic zone.

Higher-order tensor decomposition based scalp-to-intracranial EEG projection for detection of interictal epileptiform discharges.

Interictal epileptiform discharges (IEDs) occur between two seizures onsets. IEDs are mainly captured by intracranial recordings and are often invisible over the scalp. This study proposes a model based on tensor factorization to map the time-frequency (TF) features of scalp EEG (sEEG) to the TF features of intracranial EEG (iEEG) in order to detect IEDs from over the scalp with high sensitivity.

24-Hour video EEG in the evaluation of the first unprovoked seizure.

Objective: To assess the gain in detection of epileptiform abnormalities in 24-hour EEG recordings following the first seizure.

Methods: We identified patients who underwent 24-hour video EEG (VEEG) with "first seizure" as an indication. We noted the presence or absence of epileptiform discharges (EDs) in the VEEG study and the latency for the appearance of such discharges.

Incorporating Uncertainty in Data Labeling into Automatic Detection of Interictal Epileptiform Discharges from Concurrent Scalp-EEG via Multi-way Analysis.

Interictal epileptiform discharges (IEDs) are elicited from an epileptic brain, whereas they can also be due to other neurological abnormalities. The diversity in their morphologies, their strengths, and their sources within the brain cause a great deal of uncertainty in their labeling by clinicians. The aim of this study is therefore to exploit and incorporate this uncertainty (the probability of the waveform being an IED) in the IED detection system which combines spatial component analysis (SCA) with the IED probabilities referred to as SCA-IEDP-based method.

Subacute neocortical stimulation (SNCS) and its effects on epileptic activity in adults and children diagnosed with focal cortical dysplasia (FCD).

Background: Chronic intracranial electrical stimulation is now widely used as treatment for drug resistant epilepsy. Subacute neocortical stimulation (SNCS) can also be performed during EEG recordings with intracranial electrodes (iEEG), but its diagnostic value remains largely unknown.

Methods: We assessed the effects of SNCS on the frequency of seizures and epileptiform discharges (EDs) during 290 h of iEEG- from 12 patients (6 adults, 6 children) with epilepsy secondary to focal cortical dysplasia (FCD).

Electrical Cortical Stimulation: Mapping for Function and Seizures.

Surgical procedures for the treatment of epilepsy and brain tumors can involve resection of regions closed or merged to functionally eloquent cortical areas. Removal of language, primary motor, or sensory areas can be associated with transient or permanent functional deficits, which should be avoided if possible. Functional electrical cortical stimulation is a reliable technique to prevent or minimize motor, sensory and language deficits and has been used in humans since the 1950s to identify functional cortex, and it can also localize epileptogenic regions.

The Single Word Auditory Comprehension (SWAC) test: A simple method to identify receptive language areas with electrical stimulation.

Objectives: Resective surgery for medically refractory epilepsy in proximity to speech receptive areas requires balancing adequate resection of the epileptogenic zone for optimal seizure control with preservation of function. We develop a simple test (Single Word Auditory Comprehension or SWAC) to localize speech receptive areas by evaluating patients' ability to comprehend a single word.

Methods: Patients were studied during presurgical or intraoperative assessment for epilepsy with intracranial electrodes.

Encoding of long-term associations through neural unitization in the human medial temporal lobe.

Besides decades of research showing the role of the medial temporal lobe (MTL) in memory and the encoding of associations, the neural substrates underlying these functions remain unknown. We identified single neurons in the human MTL that responded to multiple and, in most cases, associated stimuli. We observed that most of these neurons exhibit no differences in their spike and local field potential (LFP) activity associated with the individual response-eliciting stimuli.

Deep Neural Architectures for Mapping Scalp to Intracranial EEG.

Data is often plagued by noise which encumbers machine learning of clinically useful biomarkers and electroencephalogram (EEG) data is no exemption. Intracranial EEG (iEEG) data enhances the training of deep learning models of the human brain, yet is often prohibitive due to the invasive recording process. A more convenient alternative is to record brain activity using scalp electrodes.

Characterizing EEG Cortical Dynamics and Connectivity with Responses to Single Pulse Electrical Stimulation (SPES).

Objectives: To model cortical connections in order to characterize their oscillatory behavior and role in the generation of spontaneous electroencephalogram (EEG).

Methods: We studied averaged responses to single pulse electrical stimulation (SPES) from the non-epileptogenic hemisphere of five patients assessed with intracranial EEG who became seizure free after contralateral temporal lobectomy. Second-order control system equations were modified to characterize the systems generating a given response.

Detection of Interictal Discharges With Convolutional Neural Networks Using Discrete Ordered Multichannel Intracranial EEG.

Detection algorithms for electroencephalography (EEG) data, especially in the field of interictal epileptiform discharge (IED) detection, have traditionally employed handcrafted features, which utilized specific characteristics of neural responses. Although these algorithms achieve high accuracy, mere detection of an IED holds little clinical significance. In this paper, we consider deep learning for epileptic subjects to accommodate automatic feature generation from intracranial EEG data, while also providing clinical insight.

Mechanisms underlying different onset patterns of focal seizures.

Focal seizures are episodes of pathological brain activity that appear to arise from a localised area of the brain. The onset patterns of focal seizure activity have been studied intensively, and they have largely been distinguished into two types-low amplitude fast oscillations (LAF), or high amplitude spikes (HAS). Here we explore whether these two patterns arise from fundamentally different mechanisms.

The Role of Thalamus Versus Cortex in Epilepsy: Evidence from Human Ictal Centromedian Recordings in Patients Assessed for Deep Brain Stimulation.

Background: The onset of generalized seizures is a long debated subject in epilepsy. The relative roles of cortex and thalamus in initiating and maintaining the different seizure types are unclear.

Objective: The purpose of the study is to estimate whether the cortex or the centromedian thalamic nucleus is leading in initiating and maintaining seizures in humans.

Intracranial stimulation for children with epilepsy.

Objectives: To evaluate the efficacy of intracranial stimulation to treat refractory epilepsy in children.

Methods: This is a retrospective analysis of a pilot study on all 8 children who had intracranial electrical stimulation for the investigation and treatment of refractory epilepsy at King's College Hospital between 2014 and 2015. Five children (one with temporal lobe epilepsy and four with frontal lobe epilepsy) had subacute cortical stimulation (SCS) for a period of 20-161 h during intracranial video-telemetry.