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Brain Waves

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Automated detection of electroencephalography artifacts in human, rodent and canine subjects using machine learning.

Journal of neuroscience methods
BACKGROUND: Electroencephalography (EEG) invariably contains extra-cranial artifacts that are commonly dealt with based on qualitative and subjective criteria. Failure to account for EEG artifacts compromises data interpretation.

Machine learning detects EEG microstate alterations in patients living with temporal lobe epilepsy.

Seizure
PURPOSE: Quasi-stable electrical distribution in EEG called microstates could carry useful information on the dynamics of large scale brain networks. Using machine learning techniques we explored if abnormalities in microstates can identify patients ...

Slow wave detection in sleeping mice: Comparison of traditional and machine learning methods.

Journal of neuroscience methods
BACKGROUND: During slow-wave sleep the electroencephalographic (EEG) and local field potential (LFP) recordings reveal the presence of large amplitude slow waves. Systematic extraction of individual slow waves is not trivial.

Application of identity vectors for EEG classification.

Journal of neuroscience methods
BACKGROUND: Finding an optimal EEG subject verification algorithm is a long standing goal within the EEG community. For every advancement made, another feature set, classifier, or dataset is often introduced; tracking improvements in classification w...

Rhythmic modulation of thalamic oscillations depends on intrinsic cellular dynamics.

Journal of neural engineering
OBJECTIVE: Rhythmic brain stimulation has emerged as a powerful tool to modulate cognition and to target pathological oscillations related to neurological and psychiatric disorders. However, we lack a systematic understanding of how periodic stimulat...

Accuracy of robot-assisted versus optical frameless navigated stereoelectroencephalography electrode placement in children.

Journal of neurosurgery. Pediatrics
OBJECTIVE The aim of this study was to compare the accuracy of optical frameless neuronavigation (ON) and robot-assisted (RA) stereoelectroencephalography (SEEG) electrode placement in children, and to identify factors that might increase the risk of...

Design and Implementation of a Novel Subject-Specific Neurofeedback Evaluation and Treatment System.

Annals of biomedical engineering
Electroencephalography (EEG)-based neurofeedback (NF) is a safe, non-invasive, non-painful method for treating various conditions. Current NF systems enable the selection of only one NF parameter, so that two parameters cannot be feedback simultaneou...

EEG characteristics of children with attention-deficit/hyperactivity disorder.

Neuroscience
The electroencephalogram (EEG) is an informative neuroimaging tool for studying attention-deficit/hyperactivity disorder (ADHD); one main goal is to characterize the EEG of children with ADHD. In this study, we employed the power spectrum, complexity...

EIQ: EEG based IQ test using wavelet packet transform and hierarchical extreme learning machine.

Journal of neuroscience methods
BACKGROUND: The use of electroencephalography has been perpetually incrementing and has numerous applications such as clinical and psychiatric studies, social interactions, brain computer interface etc. Intelligence has baffled us for centuries, and ...

Learning-based classification of valence emotion from electroencephalography.

The International journal of neuroscience
The neuroimaging research field has been revolutionized with the development of human cognitive functions without the use of brain pathways. To assist such systems, electroencephalography (EEG) based measures play an important role. In this study, th...