Evaluation of connectivity measures to identify Seizure Onset and Propagation Zones in Refractory Epilepsy: A Case study with two different Post- Surgical Outcomes.

High Frequency Oscillations (HFO) have been found very useful in refractory epilepsy. They have been used to identify the epileptogenic zone and as a promising clinical biomarker for presurgical evaluation in childhood epilepsy. There is controversy about whether there is a spread of HFOs and their propagation.

A Tailored and Engaging mHealth Gamified Framework for Nutritional Behaviour Change.

Mobile health applications (apps) have been shown to be effective for improving eating habits. However, most of the existing apps rely on calorie and nutrient counting which have several limitations including the difficulty in sustaining long-term use, inaccuracy, and the risk of developing eating disorders. We designed and developed a mHealth framework for nutritional behaviour change, integrated into the CarpeDiem app, that focuses on the intake of key food groups which are known to have a higher impact on health indicators instead of the intake of nutrients.

Multidimensional Biomechanics-Based Score to Assess Disease Progression in Duchenne Muscular Dystrophy.

(1) Background: Duchenne (DMD) is a rare neuromuscular disease that progressively weakens muscles, which severely impairs gait capacity. The Six Minute-Walk Test (6MWT), which is commonly used to evaluate and monitor the disease's evolution, presents significant variability due to extrinsic factors such as patient motivation, fatigue, and learning effects. Therefore, there is a clear need for the establishment of precise clinical endpoints to measure patient mobility.

Influence of the number of trials on evoked motor cortical activity in EEG recordings.

. Improvements in electroencephalography enable the study of the localization of active brain regions during motor tasks. Movement-related cortical potentials (MRCPs), and event-related desynchronization (ERD) and synchronization are the main motor-related cortical phenomena/neural correlates observed when a movement is elicited.

Cognitive stimulation has potential for brain activation in individuals with Rett syndrome.

Background: Knowledge regarding neuropsychological training in Rett syndrome (RS) is scarce. The aim of this study was to assess the outcome and the duration of the effect of cognitive stimulation on topographic electroencephalography (EEG) data in RS.

Methods: Twenty female children diagnosed with RS were included in the analysis.

The Kappa Opioid Receptor and the Sleep of Reason: Cortico-Subcortical Imbalance Following Salvinorin-A.

Background: The mechanisms through which kappa opioid receptor (KOR) agonists induce psychotomimetic effects are largely unknown, although the modulation of this receptor has attracted attention for its clinical use. In this work, we characterize the neuropharmacological effects of salvinorin-A, a highly selective KOR agonist.

Methods: Changes in multimodal electroencephalography, single-photon emission computed tomography, and subjective effects following the acute administration of salvinorin-A are reported.

Choosing Strategies to Deal with Artifactual EEG Data in Children with Cognitive Impairment.

Rett syndrome is a disease that involves acute cognitive impairment and, consequently, a complex and varied symptomatology. This study evaluates the EEG signals of twenty-nine patients and classify them according to the level of movement artifact. The main goal is to achieve an artifact rejection strategy that performs well in all signals, regardless of the artifact level.

Improving the ripple classification in focal pediatric epilepsy: identifying pathological high-frequency oscillations by Gaussian mixture model clustering.

. High-frequency oscillations (HFOs) have emerged as a promising clinical biomarker for presurgical evaluation in childhood epilepsy. HFOs are commonly classified in stereo-encephalography as ripples (80-200 Hz) and fast ripples (200-500 Hz).

Alterations in EEG connectivity in healthy young adults provide an indicator of sleep depth.

Current sleep analyses have used electroencephalography (EEG) to establish sleep intensity through linear and nonlinear measures. Slow wave activity (SWA) and entropy are the most commonly used markers of sleep depth. The purpose of this study is to evaluate changes in brain EEG connectivity during sleep in healthy subjects and compare them with SWA and entropy.

Automated detection of epileptic ripples in MEG using beamformer-based virtual sensors.

Objective: In epilepsy, high-frequency oscillations (HFOs) are expressively linked to the seizure onset zone (SOZ). The detection of HFOs in the noninvasive signals from scalp electroencephalography (EEG) and magnetoencephalography (MEG) is still a challenging task. The aim of this study was to automate the detection of ripples in MEG signals by reducing the high-frequency noise using beamformer-based virtual sensors (VSs) and applying an automatic procedure for exploring the time-frequency content of the detected events.

Influence of metallic artifact filtering on MEG signals for source localization during interictal epileptiform activity.

Objective: Medical intractable epilepsy is a common condition that affects 40% of epileptic patients that generally have to undergo resective surgery. Magnetoencephalography (MEG) has been increasingly used to identify the epileptogenic foci through equivalent current dipole (ECD) modeling, one of the most accepted methods to obtain an accurate localization of interictal epileptiform discharges (IEDs). Modeling requires that MEG signals are adequately preprocessed to reduce interferences, a task that has been greatly improved by the use of blind source separation (BSS) methods.

Automatic BSS-based filtering of metallic interference in MEG recordings: definition and validation using simulated signals.

Objective: One of the principal drawbacks of magnetoencephalography (MEG) is its high sensitivity to metallic artifacts, which come from implanted intracranial electrodes and dental ferromagnetic prosthesis and produce a high distortion that masks cerebral activity. The aim of this study was to develop an automatic algorithm based on blind source separation (BSS) techniques to remove metallic artifacts from MEG signals.

Approach: Three methods were evaluated: AMUSE, a second-order technique; and INFOMAX and FastICA, both based on high-order statistics.

Reduction of metallic interference in MEG signals using AMUSE.

Magnetoencephalography is a technique that can noninvasively measure the brain signal. There are many advantages of using this technique rather than similar procedures such as the EEG for the evaluation of medical diseases. However, one of its main problems is its high sensitivity to sources causing metallic distortion of the signal, and the removal of this type of artifacts remains unsolved.