Seizures

Automated analysis of brain activity for seizure detection in zebrafish models of epilepsy.

BACKGROUND: Epilepsy is a chronic neurological condition, with over 30% of cases unresponsive to treatment. Zebrafish larvae show great potential to serve as an animal model of epilepsy in drug discovery. Thanks to their high fecundity and relatively low cost, they are amenable to high-throughput screening. However, the assessment of seizure occurrences in zebrafish larvae remains a bottleneck, as...

Noninvasive Electroencephalogram Based Control of a Robotic Arm for Writing Task Using Hybrid BCI System.

A novel hybrid brain-computer interface (BCI) based on the electroencephalogram (EEG) signal which consists of a motor imagery- (MI-) based online interactive brain-controlled switch, "teeth clenching" state detector, and a steady-state visual evoked potential- (SSVEP-) based BCI was proposed to provide multidimensional BCI control. MI-based BCI was used as single-pole double throw brain switch (S...

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion.

Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an importan...

A new near-lossless EEG compression method using ANN-based reconstruction technique.

Compression algorithm is an essential part of Telemedicine systems, to store and transmit large amount of medical signals. Most of existing compressio...

Auditory prediction errors as individual biomarkers of schizophrenia.

Schizophrenia is a complex psychiatric disorder, typically diagnosed through symptomatic evidence collected through patient interview. We aim to devel...

Towards Improved Design and Evaluation of Epileptic Seizure Predictors.

OBJECTIVE: Key issues in the epilepsy seizure prediction research are (1) the reproducibility of results (2) the inability to compare multiple approac...

Anticonvulsant effect of ethanolic extract of L. leaves on pentylenetetrazol induced seizure in mice.

(CA) rhizomes have demonstrated different properties on nervous system. However, the leaves still have not studied to treat epilepsy. The aim of this...

EEG-Based Computer Aided Diagnosis of Autism Spectrum Disorder Using Wavelet, Entropy, and ANN.

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with core impairments in the social relationships, communication, imagination,...

Progress in EEG-Based Brain Robot Interaction Systems.

The most popular noninvasive Brain Robot Interaction (BRI) technology uses the electroencephalogram- (EEG-) based Brain Computer Interface (BCI), to s...

(matico) prevents collagen-induced platelet activation by decreasing phospholipase C-gamma 2 and protein kinase C phosphorylation signaling.

Platelets play a key role in thrombosis and cardiovascular diseases. Medicinal plants could be one of the most important factors that influence risks ...

Recurring Functional Interactions Predict Network Architecture of Interictal and Ictal States in Neocortical Epilepsy.

Human epilepsy patients suffer from spontaneous seizures, which originate in brain regions that also subserve normal function. Prior studies demonstra...

Evolving Network Model That Almost Regenerates Epileptic Data.

In many realistic networks, the edges representing the interactions between nodes are time varying. Evidence is growing that the complex network that ...

AN ANALYSIS OF TWO COMMON REFERENCE POINTS FOR EEGS.

Clinical electroencephalographic (EEG) data varies significantly depending on a number of operational conditions (e.g., the type and placement of elec...

SEMI-AUTOMATED ANNOTATION OF SIGNAL EVENTS IN CLINICAL EEG DATA.

To be effective, state of the art machine learning technology needs large amounts of annotated data. There are numerous compelling applications in hea...

Machine learning-based prediction of adverse drug effects: An example of seizure-inducing compounds.

Various biological factors have been implicated in convulsive seizures, involving side effects of drugs. For the preclinical safety assessment of drug...

Exploring temporal information in neonatal seizures using a dynamic time warping based SVM kernel.

Seizure events in newborns change in frequency, morphology, and propagation. This contextual information is explored at the classifier level in the pr...

Automated seizure detection using limited-channel EEG and non-linear dimension reduction.

Electroencephalography (EEG) is an essential component in evaluation of epilepsy. However, full-channel EEG signals recorded from 18 to 23 electrodes ...

Single Trial EEG Patterns for the Prediction of Individual Differences in Fluid Intelligence.

Assessing a person's intelligence level is required in many situations, such as career counseling and clinical applications. EEG evoked potentials in ...

Gaussian Process Regression for Predictive But Interpretable Machine Learning Models: An Example of Predicting Mental Workload across Tasks.

There is increasing interest in real-time brain-computer interfaces (BCIs) for the passive monitoring of human cognitive state, including cognitive wo...

Deep Learning and Insomnia: Assisting Clinicians With Their Diagnosis.

Effective sleep analysis is hampered by the lack of automated tools catering to disordered sleep patterns and cumbersome monitoring hardware. In this ...