Detection of epileptic activity in presumably normal EEG.

Monitoring epileptic activity in the absence of interictal discharges is a major need given the well-established lack of reliability of patients' reports of their seizures. Up to now, there are no other tools than reviewing the seizure diary; however, seizures may not be remembered or dismissed voluntarily. In the present study, we set out to determine if EEG voltage maps of epileptogenic activity in individual patients can help to identify disease activity, even if their scalp EEG appears normal.

Capturing the spatiotemporal dynamics of self-generated, task-initiated thoughts with EEG and fMRI.

The temporal structure of self-generated cognition is a key attribute to the formation of a meaningful stream of consciousness. When at rest, our mind wanders from thought to thought in distinct mental states. Despite the marked importance of ongoing mental processes, it is challenging to capture and relate these states to specific cognitive contents.

Large-Scale 3-5 Hz Oscillation Constrains the Expression of Neocortical Fast Ripples in a Mouse Model of Mesial Temporal Lobe Epilepsy.

Large-scale slow oscillations allow the integration of neuronal activity across brain regions during sensory or cognitive processing. However, evidence that this form of coding also holds for pathological networks, such as for distributed networks in epileptic disorders, does not yet exist. Here, we show in a mouse model of unilateral hippocampal epilepsy that epileptic fast ripples generated in the neocortex distant from the primary focus occur during transient trains of interictal epileptic discharges.

Automated long-term EEG analysis to localize the epileptogenic zone.

Objective: We investigated the performance of automatic spike detection and subsequent electroencephalogram (EEG) source imaging to localize the epileptogenic zone (EZ) from long-term EEG recorded during video-EEG monitoring.

Methods: In 32 patients, spikes were automatically detected in the EEG and clustered according to their morphology. The two spike clusters with most single events in each patient were averaged and localized in the brain at the half-rising time and peak of the spike using EEG source imaging.

Electrophysiological Evidence for the Development of a Self-Sustained Large-Scale Epileptic Network in the Kainate Mouse Model of Temporal Lobe Epilepsy.

Most research on focal epilepsy focuses on mechanisms of seizure generation in the primary epileptic focus (EF). However, neurological deficits that are not directly linked to seizure activity and that may persist after focus removal are frequent. The recruitment of remote brain regions of an epileptic network (EN) is recognized as a possible cause, but a profound lack of experimental evidence exists concerning their recruitment and the type of pathological activities they exhibit.

Source localization of ictal epileptic activity based on high-density scalp EEG data.

Objective: Electrical source imaging (ESI) is a well-established approach to localizing the epileptic focus in drug-resistant focal epilepsy. So far, ESI has been used primarily on interictal events. Emerging evidence suggests that ictal ESI is also feasible and potentially useful.

Seizure Onset Zone Localization from Ictal High-Density EEG in Refractory Focal Epilepsy.

Epilepsy surgery is the most efficient treatment option for patients with refractory epilepsy. Before surgery, it is of utmost importance to accurately delineate the seizure onset zone (SOZ). Non-invasive EEG is the most used neuroimaging technique to diagnose epilepsy, but it is hard to localize the SOZ from EEG due to its low spatial resolution and because epilepsy is a network disease, with several brain regions becoming active during a seizure.

Complex patterns of spatially extended generators of epileptic activity: Comparison of source localization methods cMEM and 4-ExSo-MUSIC on high resolution EEG and MEG data.

Electric Source Imaging (ESI) and Magnetic Source Imaging (MSI) of EEG and MEG signals are widely used to determine the origin of interictal epileptic discharges during the pre-surgical evaluation of patients with epilepsy. Epileptic discharges are detectable on EEG/MEG scalp recordings only when associated with a spatially extended cortical generator of several square centimeters, therefore it is essential to assess the ability of source localization methods to recover such spatial extent. In this study we evaluated two source localization methods that have been developed for localizing spatially extended sources using EEG/MEG data: coherent Maximum Entropy on the Mean (cMEM) and 4th order Extended Source Multiple Signal Classification (4-ExSo-MUSIC).

Head model and electrical source imaging: a study of 38 epileptic patients.

Electrical source imaging (ESI) aims at reconstructing the electrical brain activity from scalp EEG. When applied to interictal epileptiform discharges (IEDs), this technique is of great use for identifying the irritative zone in focal epilepsies. Inaccuracies in the modeling of electro-magnetic field propagation in the head (forward model) may strongly influence ESI and lead to mislocalization of IED generators.

EEG extended source localization: tensor-based vs. conventional methods.

The localization of brain sources based on EEG measurements is a topic that has attracted a lot of attention in the last decades and many different source localization algorithms have been proposed. However, their performance is limited in the case of several simultaneously active brain regions and low signal-to-noise ratios. To overcome these problems, tensor-based preprocessing can be applied, which consists in constructing a space-time-frequency (STF) or space-time-wave-vector (STWV) tensor and decomposing it using the Canonical Polyadic (CP) decomposition.

From oscillatory transcranial current stimulation to scalp EEG changes: a biophysical and physiological modeling study.

Both biophysical and neurophysiological aspects need to be considered to assess the impact of electric fields induced by transcranial current stimulation (tCS) on the cerebral cortex and the subsequent effects occurring on scalp EEG. The objective of this work was to elaborate a global model allowing for the simulation of scalp EEG signals under tCS. In our integrated modeling approach, realistic meshes of the head tissues and of the stimulation electrodes were first built to map the generated electric field distribution on the cortical surface.

Automatic detection of fast ripples.

Objective: We propose a new method for automatic detection of fast ripples (FRs) which have been identified as a potential biomarker of epileptogenic processes.

Methods: This method is based on a two-stage procedure: (i) global detection of events of interest (EOIs, defined as transient signals accompanied with an energy increase in the frequency band of interest 250-600Hz) and (ii) local energy vs. frequency analysis of detected EOIs for classification as FRs, interictal epileptic spikes or artifacts.

Effects of transcranial Direct Current Stimulation (tDCS) on cortical activity: a computational modeling study.

Although it is well-admitted that transcranial Direct Current Stimulation (tDCS) allows for interacting with brain endogenous rhythms, the exact mechanisms by which externally-applied fields modulate the activity of neurons remain elusive. In this study a novel computational model (a neural mass model including subpopulations of pyramidal cells and inhibitory interneurons mediating synaptic currents with either slow or fast kinetics) of the cerebral cortex was elaborated to investigate the local effects of tDCS on neuronal populations based on an in-vivo experimental study. Model parameters were adjusted to reproduce evoked potentials (EPs) recorded from the somatosensory cortex of the rabbit in response to air-puffs applied on the whiskers.

Localization of extended brain sources from EEG/MEG: the ExSo-MUSIC approach.

We propose a new MUSIC-like method, called 2q-ExSo-MUSIC (q ≥ 1). This method is an extension of the 2q-MUSIC (q ≥ 1) approach for solving the EEG/MEG inverse problem, when spatially-extended neocortical sources ("ExSo") are considered. It introduces a novel ExSo-MUSIC principle.