Adaptive Remote Sensing Paradigm for Real-Time Alerting of Convulsive Epileptic Seizures.

Epilepsy is a debilitating neurological condition characterized by intermittent paroxysmal states called fits or seizures. Especially, the major motor seizures of a convulsive nature, such as tonic-clonic seizures, can cause aggravating consequences. Timely alerting for these convulsive epileptic states can therefore prevent numerous complications, during, or following the fit.

Validation of virtual resection on intraoperative interictal data acquired during epilepsy surgery.

. A 'Virtual resection' consists of computationally simulating the effect of an actual resection on the brain. We validated two functional connectivity based virtual resection methods with the actual connectivity measured using post-resection intraoperative recordings.

The value of intra-operative electrographic biomarkers for tailoring during epilepsy surgery: from group-level to patient-level analysis.

Signal analysis biomarkers, in an intra-operative setting, may be complementary tools to guide and tailor the resection in drug-resistant focal epilepsy patients. Effective assessment of biomarker performances are needed to evaluate their clinical usefulness and translation. We defined a realistic ground-truth scenario and compared the effectiveness of different biomarkers alone and combined to localize epileptogenic tissue during surgery.

Automated video-based detection of nocturnal motor seizures in children.

Seizure detection devices can improve epilepsy care, but wearables are not always tolerated. We previously demonstrated good performance of a real-time video-based algorithm for detection of nocturnal convulsive seizures in adults with learning disabilities. The algorithm calculates the relative frequency content based on the group velocity reconstruction from video-sequence optical flow.

Epilepsy as a manifestation of a multistate network of oscillatory systems.

The human brain, largely accepted as the most complex biological system known, is still far from being understood in its parts or as a whole. More specifically, biological mechanisms of epileptic states and state transitions are not well understood. Here, we explore the concept of the epilepsy as a manifestation of a multistate network composed of coupled oscillatory units.

Automated remote fall detection using impact features from video and audio.

Elderly people and people with epilepsy may need assistance after falling, but may be unable to summon help due to injuries or impairment of consciousness. Several wearable fall detection devices have been developed, but these are not used by all people at risk. We present an automated analysis algorithm for remote detection of high impact falls, based on a physical model of a fall, aiming at universality and robustness.

Phase clustering in transcranial magnetic stimulation-evoked EEG responses in genetic generalized epilepsy and migraine.

Background: Epilepsy and migraine are paroxysmal neurological conditions associated with disturbances of cortical excitability. No useful biomarkers to monitor disease activity in these conditions are available. Phase clustering was previously described in electroencephalographic (EEG) responses to photic stimulation and may be a potential epilepsy biomarker.

Automated video-based detection of nocturnal convulsive seizures in a residential care setting.

People with epilepsy need assistance and are at risk of sudden death when having convulsive seizures (CS). Automated real-time seizure detection systems can help alert caregivers, but wearable sensors are not always tolerated. We determined algorithm settings and investigated detection performance of a video algorithm to detect CS in a residential care setting.

Multimodal, automated detection of nocturnal motor seizures at home: Is a reliable seizure detector feasible?

Objective: Automated seizure detection and alarming could improve quality of life and potentially prevent sudden, unexpected death in patients with severe epilepsy. As currently available systems focus on tonic-clonic seizures, we want to detect a broader range of seizure types, including tonic, hypermotor, and clusters of seizures.

Methods: In this multicenter, prospective cohort study, the nonelectroencephalographic (non-EEG) signals heart rate and accelerometry were measured during the night in patients undergoing a diagnostic video-EEG examination.

Long-interval intracortical inhibition as biomarker for epilepsy: a transcranial magnetic stimulation study.

Cortical excitability, as measured by transcranial magnetic stimulation combined with electromyography, is a potential biomarker for the diagnosis and follow-up of epilepsy. We report on long-interval intracortical inhibition data measured in four different centres in healthy controls (n = 95), subjects with refractory genetic generalized epilepsy (n = 40) and with refractory focal epilepsy (n = 69). Long-interval intracortical inhibition was measured by applying two supra-threshold stimuli with an interstimulus interval of 50, 100, 150, 200 and 250 ms and calculating the ratio between the response to the second (test stimulus) and to the first (conditioning stimulus).

Dynamics of convulsive seizure termination and postictal generalized EEG suppression.

It is not fully understood how seizures terminate and why some seizures are followed by a period of complete brain activity suppression, postictal generalized EEG suppression. This is clinically relevant as there is a potential association between postictal generalized EEG suppression, cardiorespiratory arrest and sudden death following a seizure. We combined human encephalographic seizure data with data of a computational model of seizures to elucidate the neuronal network dynamics underlying seizure termination and the postictal generalized EEG suppression state.

Non-harmonicity in high-frequency components of the intra-operative corticogram to delineate epileptogenic tissue during surgery.

Objective: We aimed to test the potential of auto-regressive model residual modulation (ARRm), an artefact-insensitive method based on non-harmonicity of the high-frequency signal, to identify epileptogenic tissue during surgery.

Methods: Intra-operative electrocorticography (ECoG) of 54 patients with refractory focal epilepsy were recorded pre- and post-resection at 2048Hz. The ARRm was calculated in one-minute epochs in which high-frequency oscillations (HFOs; fast ripples, 250-500Hz; ripples, 80-250Hz) and spikes were marked.

Brain (Hyper)Excitability Revealed by Optimal Electrical Stimulation of GABAergic Interneurons.

Background: Neurological disorders are often characterized by an excessive and prolonged imbalance between neural excitatory and inhibitory processes. An ubiquitous finding among these disorders is the disrupted function of inhibitory GABAergic interneurons.

Objective: The objective is to propose a novel stimulation procedure able to evaluate the efficacy of inhibition imposed by GABAergic interneurons onto pyramidal cells from evoked responses observed in local field potentials (LFPs).

Preventive and Abortive Strategies for Stimulation Based Control of Epilepsy: A Computational Model Study.

Epilepsy is a condition in which periods of ongoing normal EEG activity alternate with periods of oscillatory behavior characteristic of epileptic seizures. The dynamics of the transitions between the two states are still unclear. Computational models provide a powerful tool to explore the underlying mechanisms of such transitions, with the purpose of eventually finding therapeutic interventions for this debilitating condition.

Automated Video Detection of Epileptic Convulsion Slowing as a Precursor for Post-Seizure Neuronal Collapse.

Automated monitoring and alerting for adverse events in people with epilepsy can provide higher security and quality of life for those who suffer from this debilitating condition. Recently, we found a relation between clonic slowing at the end of a convulsive seizure (CS) and the occurrence and duration of a subsequent period of postictal generalized EEG suppression (PGES). Prolonged periods of PGES can be predicted by the amount of progressive increase of interclonic intervals (ICIs) during the seizure.

Gap Junctions as Common Cause of High-Frequency Oscillations and Epileptic Seizures in a Computational Cascade of Neuronal Mass and Compartmental Modeling.

High frequency oscillations (HFO) appear to be a promising marker for delineating the seizure onset zone (SOZ) in patients with localization related epilepsy. It remains, however, a purely observational phenomenon and no common mechanism has been proposed to relate HFOs and seizure generation. In this work we show that a cascade of two computational models, one on detailed compartmental scale and a second one on neural mass scale can explain both the autonomous generation of HFOs and the presence of epileptic seizures as emergent properties.

Automated Seizure Onset Zone Approximation Based on Nonharmonic High-Frequency Oscillations in Human Interictal Intracranial EEGs.

A novel automated algorithm is proposed to approximate the seizure onset zone (SOZ), while providing reproducible output. The SOZ, a surrogate marker for the epileptogenic zone (EZ), was approximated from intracranial electroencephalograms (iEEG) of nine people with temporal lobe epilepsy (TLE), using three methods: (1) Total ripple length (TRL): Manually segmented high-frequency oscillations, (2) Rippleness (R): Area under the curve (AUC) of the autocorrelation functions envelope, and (3) Autoregressive model residual variation (ARR, novel algorithm): Time-variation of residuals from autoregressive models of iEEG windows. TRL, R, and ARR results were compared in terms of separability, using Kolmogorov-Smirnov tests, and performance, using receiver operating characteristic (ROC) curves, to the gold standard for SOZ delineation: visual observation of ictal video-iEEGs.

Multiple oscillatory states in models of collective neuronal dynamics.

In our previous studies, we showed that the both realistic and analytical computational models of neural dynamics can display multiple sustained states (attractors) for the same values of model parameters. Some of these states can represent normal activity while other, of oscillatory nature, may represent epileptic types of activity. We also showed that a simplified, analytical model can mimic this type of behavior and can be used instead of the realistic model for large scale simulations.

Dynamics of collective multi-stability in models of multi-unit neuronal systems.

In this study, we investigate the correspondence between dynamic patterns of behavior in two types of computational models of neuronal activity. The first model type is the realistic neuronal model; the second model type is the phenomenological or analytical model. In the simplest model set-up of two interconnected units, we define a parameter space for both types of systems where their behavior is similar.

Cortical excitability as a potential clinical marker of epilepsy: a review of the clinical application of transcranial magnetic stimulation.

Transcranial magnetic stimulation (TMS) can be used for safe, noninvasive probing of cortical excitability (CE). We review 50 studies that measured CE in people with epilepsy. Most showed cortical hyperexcitability, which can be corrected with anti-epileptic drug treatment.

Connectivity and phase coherence in neural network models of interconnected Z(4)-bi-stable units.

A phenomenological neural network model with bi-stable oscillatory units is used to model up- and down-states. These states have been observed in vivo in biological neuronal systems and feature oscillatory, limit cycle type of behavior in the up-states. A network is formed by a set of interconnected units.

Electroencephalographic events prior to epileptic major motor seizures.

Rationale: The goal of this study is to evaluate the electroencephalographic (EEG) events, prior to clonic phases of epileptic motor seizures. Analyzing video sequences we were able to detect these special phases of motor seizures, by image features. This can be used for an early detection and alerting for these events.