The metastable brain

E Tognoli, JAS Kelso - Neuron, 2014 - cell.com
Neural ensembles oscillate across a broad range of frequencies and are transiently coupled
or" bound" together when people attend to a stimulus, perceive, think, and act. This is a …

Deep convolutional neural networks for mental load classification based on EEG data

Z Jiao, X Gao, Y Wang, J Li, H Xu - Pattern Recognition, 2018 - Elsevier
Electroencephalograph (EEG), the representation of the brain's electrical activity, is a widely
used measure of brain activities such as working memory during cognitive tasks. Varying in …

Modeling epileptic brain states using EEG spectral analysis and topographic mapping

B Direito, C Teixeira, B Ribeiro… - Journal of neuroscience …, 2012 - Elsevier
Changes in the spatio-temporal behavior of the brain electrical activity are believed to be
associated to epileptic brain states. We propose a novel methodology to identify the different …

[PDF][PDF] The neuropsychological measure (EEG) of flow under conditions of peak performance

FG De Kock - 2014 - core.ac.uk
Flow is a mental state characterised by a feeling of energised focus, complete involvement
and success when fully immersed in an activity. The dimensions of and the conditions …

Visualization of epilepsy patient's brain condition based on spectral analysis of EEG signals using topographic mapping

DP Wulandari, YK Suprapto, AI Juniani… - 2018 International …, 2018 - ieeexplore.ieee.org
In analyzing the epilepsy patient data it is necessary for a doctor to know where the epileptic
focus are located. This information is related to the determination of the type of drug delivery …

Classification of real and imaginary hand movements for a BCI design

NG Ozmen, L Gumusel - 2013 36th International Conference on …, 2013 - ieeexplore.ieee.org
This paper searches the discrimination ability of a feature extraction method for EEG
analysis. The method is tested on the classification of imagined and real right/left hand …

A new signal segmentation approach based on singular value decomposition and Intelligent savitzky-golay filter

H Azami, M Saraf, K Mohammadi - … AISP 2013, Tehran, Iran, December 25 …, 2014 - Springer
Signal segmentation, dividing non-stationary signals into semi-stationary parts that each has
rather equal statistical characteristics is necessary in many signal analysis approaches. In …

An improved automatic eeg signal segmentation method based on generalized likelihood ratio

H Azami, H Hassanpour, M Anisheh - International Journal of Engineering, 2014 - ije.ir
It is often needed to label electroencephalogram (EEG) signals by segments of similar
characteristics that are particularly meaningful to clinicians and for assessment by …

[PDF][PDF] Epileptic Seizures Detection Using DCT-II and KNN Classifier in Long-Term EEG Signals

MA Jumaah, AI Shihab, AA Farhan - Iraqi Journal of Science, 2020 - iasj.net
Epilepsy is one of the most common diseases of the nervous system around the world,
affecting all age groups and causing seizures leading to loss of control for a period of time …

Neural dynamics of synchronous imitative interaction

G Dumas - 2011 - hal.science
Since 2002, a new neuroimaging technique called hyperscanning allows to record several
participants simultaneously and thus to study social interaction in a reciprocal and …