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. If DRs and IEDs come from the same location and the DRs can be accurately localized, there will be a significant step in identification of the seizure sources. The solution to this important question has been investigated in this paper. For this, we have exploited the morphology of these spike-type events, as well as the variability in their temporal locations, to develop new constraints for an adaptive Bayesian beamformer that outperforms the conventional and recently proposed beamformers even for identifying correlated sources. This beamformer is applied to an array (a.k.a mat) of cortical EEG electrodes. The developed approach has been tested on 300 data segments from five epileptic patients included in this study, which clinically represent a large population of candidates for surgical treatment. As the significant outcome of applying this beamformer, it is very likely (if not certain) that for an epileptic subject, the IEDs and DRs originate from the same location in the brain. This paves the way for a quick identification of the source(s) of seizure in the brain.

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. Since 1972, different machine learning techniques, from template matching to deep learning, have been developed to automatically detect IEDs from scalp EEG (scEEG) and intracranial EEG (iEEG). While the scEEG signals suffer from low information details and high attenuation of IEDs due to the high skull electrical impedance, the iEEG signals recorded using implanted electrodes enjoy higher details and are more suitable for identifying the IEDs. In this review paper, we group IED detection techniques into six categories: (1) template matching, (2) feature representation (mimetic, time-frequency, and nonlinear features), (3) matrix decomposition, (4) tensor factorization, (5) neural networks, and (6) estimation of the iEEG from the concurrent scEEG followed by detection and classification. The methods are compared quantitatively (e.g., in terms of accuracy, sensitivity, and specificity), and their general advantages and limitations are described. Finally, current limitations and possible future research paths related to this field are mentioned.

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. The evaluation of these techniques is limited by the small number of published paediatric cases (n = 25, one with two techniques) in peer-reviewed articles (n = 18). Although neuromodulation strategies have not been tested through randomised, prospective controlled clinical trials, this review presents the existing data and the potential benefits of neuromodulation therapy, suggesting that these techniques, when available, could be considered at earlier stages within the course of srSE intending to prevent long-term neurologic complications. Clinical trials aiming to establish whether early intervention can prevent long-term sequelae are necessary in order to establish the potential clinical value of neuromodulation techniques for the treatment of srSE in children.

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. The prime objective here is to accurately localize the regions for the corresponding DRs using an adaptive localization method that exploits the morphology of DRs as the desired sources. The traditional closed-form linearly constrained minimum variance (CF-LCMV) solution is meant for tracking the sources with dominating power. Here, by incorporating the morphology of DRs, as a constraint, to an iterative linearly constrained minimum variance (LCMV) solution, the array of subdural electrodes is used to localize the low-power DRs, some not even visible in any of the electrode signals. The results from the cases included in this study also indicate more distinctive locations compared to those achievable by conventional beamformers. Most importantly, the proposed AI-LCMV is able to localize the DRs invisible over other 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. SSA is a powerful subspace signal analysis method for separation of single channel signals into their constituent uncorrelated components. The consistency in the results for both early and delayed brain responses verifies the usability of the approach.

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

Objective.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.Approach.Continuous wavelet transform is employed to extract the TF features. Time, frequency, and channel modes of IED segments from iEEG recordings are concatenated into a four-way tensor. Tucker and CANDECOMP/PARAFAC decomposition techniques are employed to decompose the tensor into temporal, spectral, spatial, and segmental factors. Finally, TF features of both IED and non-IED segments from scalp recordings are projected onto the temporal components for classification.Main results.The model performance is obtained in two different approaches: within- and between-subject classification approaches. Our proposed method is compared with four other methods, namely a tensor-based spatial component analysis method, TF-based method, linear regression mapping model, and asymmetric-symmetric autoencoder mapping model followed by convolutional neural networks. Our proposed method outperforms all these methods in both within- and between-subject classification approaches by respectively achieving 84.2% and 72.6% accuracy values.Significance.The findings show that mapping sEEG to iEEG improves the performance of the scalp-based IED detection model. Furthermore, the tensor-based mapping model outperforms the autoencoder- and regression-based mapping models.

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. We compared the rate of EDs during the initial 60 min with those occurring only later during the recording. RESULTS: Data from 25 patients, aged 15 to 59, were included. Of the 11 patients with EDs, eight (73%) appeared only after 60 min of recording. This equates to a 32% absolute increase in the detection of EDs across all patients. The latency to first EDs varied from one to 1080 min with a median of 170 min. In four cases, actual subtle seizures were recorded. CONCLUSION: This study suggests an increase in the detection of EDs with the 24-hour studies compared to the traditional shorter recordings, in the context of a first seizure. SIGNIFICANCE: A standard EEG can be performed close to the seizure, followed by a longer up to 24-hour recording if the initial shorter study is unrevealing.

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. For comparison, we also propose and study SCA-based method in which probability of the waveform being an IED is ignored. The proposed models are employed to detect IEDs in two different classification approaches: (1) subject-dependent and (2) subject-independent classification approaches. The proposed methods are compared with two other state-of-the-art methods namely, time-frequency features and tensor factorization methods. The proposed SCA-IEDP model has achieved superior performance in comparison with the traditional SCA and other competing methods. It achieved 79.9% and 63.4% accuracy values in subject-dependent and subject-independent classification approaches, respectively. This shows that considering the IED probabilities in designing an IED detection system can boost its performance.

Beta-2 agonists for the treatment of bronchiolitis. / Beta-2 agonistas para el tratamiento de bronquiolitis.

INTRODUCCIÓN: La bronquiolitis es la inflamación aguda de las vías aéreas de pequeño calibre, teniendo como causa principal las infecciones virales. Es altamente frecuente en menores de dos años, sobretodo en menores de 12 meses. Existe gran controversia sobre el manejo de esta patología, siendo especialmente cuestionable el uso de beta-2 agonistas de corta acción tanto en el ámbito ambulatorio como hospitalario. MÉTODOS: Para responder esta pregunta utilizamos Epistemonikos, la mayor base de datos de revisiones sistemáticas en salud a nivel mundial, la cual es mantenida mediante búsquedas en múltiples fuentes de información, incluyendo MEDLINE, EMBASE, Cochrane, entre otras. Extrajimos los datos desde las revisiones identificadas, reanalizamos los datos de los estudios primarios, realizamos un metanálisis, y preparamos una tabla de resumen de los resultados utilizando el método GRADE. RESULTADOS Y CONCLUSIONES: Identificamos siete revisiones sistemáticas que en conjunto incluyen 47 estudios primarios, de los cuales 44 corresponden a ensayos aleatorizados. Concluimos que el uso de beta-2 agonistas podría no tener ningún beneficio en el manejo de la bronquiolitis, en términos de necesidad de hospitalización y/o duración de la misma. Por otra parte, podría aumentar efectos adversos como arritmias, sin embargo, la certeza de esta evidencia es baja.

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). RESULTS: In 9/12 patients, SNCS periods showed decreased seizure-frequency (Median -73 %, p = 0.0093). At baseline, incidence of EDs were correlated with seizure-frequency (Spearman r = 0.59). However, this correlation disappeared during SNCS and a significant change in the incidence of EDs was observed. In addition, there was a trend towards greater reduction in seizure-frequency during SNCS in patients who underwent surgery. CONCLUSION: In summary, SNCS can reduce seizure-frequency and changes ED-frequency. The variability in ED changes may be explained by different effects of SNCS depending on electrode location. The magnitude of seizure reduction during SNCS suggests that this technique could contribute to preoperative assessment in epilepsy surgery.

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. This article discusses functional electrical stimulation in adults and children for different functional modalities.

Beta-2 agonistas para el tratamiento de bronquiolitis / Beta-2 agonists for the treatment of bronchiolitis

INTRODUCCIÓN La bronquiolitis es la inflamación aguda de las vías aéreas de pequeño calibre, teniendo como causa principal las infecciones virales. Es altamente frecuente en menores de dos años, sobretodo en menores de 12 meses. Existe gran controversia sobre el manejo de esta patología, siendo especialmente cuestionable el uso de beta-2 agonistas de corta acción tanto en el ámbito ambulatorio como hospitalario. MÉTODOS Para responder esta pregunta utilizamos Epistemonikos, la mayor base de datos de revisiones sistemáticas en salud a nivel mundial, la cual es mantenida mediante búsquedas en múltiples fuentes de información, incluyendo MEDLINE, EMBASE, Cochrane, entre otras. Extrajimos los datos desde las revisiones identificadas, reanalizamos los datos de los estudios primarios, realizamos un metanálisis, y preparamos una tabla de resumen de los resultados utilizando el método GRADE. RESULTADOS Y CONCLUSIONES Identificamos siete revisiones sistemáticas que en conjunto incluyen 47 estudios primarios, de los cuales 44 corresponden a ensayos aleatorizados. Concluimos que el uso de beta-2 agonistas podría no tener ningún beneficio en el manejo de la bronquiolitis, en términos de necesidad de hospitalización y/o duración de la misma. Por otra parte, podría aumentar efectos adversos como arritmias, sin embargo, la certeza de esta evidencia es baja

Ejercicio: una herramienta clave en la prevención cardiovascular: Consenso de la Sociedad Chilena de Cardiología y Cirugía Cardiovascular y de la Sociedad Chilena de Kinesiología en Cardiología y Cirugía Cardiovascular / Excercise, a key intervention in Cardiovascular Prevention: Consensus of the Chilean Society of Cardiology and Cardiovascular Surgery and the Chilean Society of Kinesiology in Cardiology and Cardiovascular Surgery

This is a Document from de Chilean Society of Cardiology and Cardiovascular Surgery, along with the Chilean Society of Physical Therapy of Cardiology and Cardiovascular Surgery.

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. They were asked to listen to a common word (target word) and to describe what it meant without saying the target word. Electrical stimulation (trains of biphasic 2-ms pulses, 50 Hz for 3 s) was delivered while the patient listened to the target word, not while the patient explained the meaning of the word. In six patients, SWAC test was carried out during extraoperative chronic recordings, and in one patient in the operating theater under local anesthesia. RESULTS: Among the 7 patients where the test identified deficits, 6 underwent resection (4 temporal, 1 supramarginal, and 1 occipital). Two patients showed temporary minor speech deficits after resection. No patient showed permanent speech deficits after resection. CONCLUSION/SIGNIFICANCE: The SWAC test is reliable, simple and fast to implement, and suitable for intraoperating mapping. It could be used as a simple initial test to identify receptive language areas where more complex additional tests can be performed.

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. In addition, LFP responses in the theta band preceded single neuron responses by ~70 ms, with the single trial phase providing fine tuning of the spike response onset. We postulate that the finding of similar neuronal responses to associated items provides a simple and flexible way of encoding memories in the human MTL, increasing the effective capacity for memory storage and successful retrieval.

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. However, the inherent noise associated with scalp EEG data often impedes the learning process of neural models, achieving substandard performance. Here, an ensemble deep learning architecture for nonlinearly mapping scalp to iEEG data is proposed. The proposed architecture exploits the information from a limited number of joint scalp-intracranial recording to establish a novel methodology for detecting the epileptic discharges from the sEEG of a general population of subjects. Statistical tests and qualitative analysis have revealed that the generated pseudo-intracranial data are highly correlated with the true intracranial data. This facilitated the detection of IEDs from the scalp recordings where such waveforms are not often visible. As a real-world clinical application, these pseudo-iEEGs are then used by a convolutional neural network for the automated classification of intracranial epileptic discharges (IEDs) and non-IED of trials in the context of epilepsy analysis. Although the aim of this work was to circumvent the unavailability of iEEG and the limitations of sEEG, we have achieved a classification accuracy of 68% an increase of 6% over the previously proposed linear regression mapping.

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. SPES responses were modeled as responses to a unit step input. EEG power spectrum was calculated on the 20[Formula: see text]s preceding SPES. RESULTS: 121 channels showed responses to 32 stimulation sites. A single system could model the response in 41.3% and two systems were required in 58.7%. Peaks in the frequency response of the models tended to occur within the frequency range of most activity on the spontaneous EEG. Discrepancies were noted between activity predicted by models and activity recorded in the spontaneous EEG. These discrepancies could be explained by the existence of alpha rhythm or interictal epileptiform discharges. CONCLUSIONS: Cortical interactions shown by SPES can be described as control systems which can predict cortical oscillatory behavior. The method is unique as it describes connectivity as well as dynamic interactions.

Guías para la monitorización ambulatoria de presión arterial de 24 horas: documento de la Sociedad Chilena de Cardiología y Cirugía Cardiovascular / 24 hour blood pressure monitoring: recommendations from the Chilean Society of Cardiology and Cardiovascular Surgery

Abstracts: 24 hour blood pressure monitoring. Recommendations from the Chilean Society of Cardiology and Cardiovascular Surgery. The recommendations for blood pressure monitoring from the Chilean Society of Cardiology and Cardiovascular Surgery are analyzed. Emphasis is placed on indications for the procedure, according to different classes and causes of hypertension. Implications of different types of hypertension for prognosis and indications for adequate therapy are discussed.