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Common Spatial Pattern (CSP) is one of the popular and effective methods for discriminating two class electroencephalogram (EEG) measurements. Its probabilistic counterpart by resolving the problem of overfitting as the main limitation of CSP attracted much attention, especially in the motor imaginary based brain computer interface (BCI) applications. Since the computational efficiency is a paramount...
Detecting causal relationships between time series data has been widely studied in many areas, including biology, neuroscience, economics, and climatology. One of the most popular causality inference methods is Granger causality approach that is a linear regression based model for determining whether one time series is useful in forecasting another; however, this approach cannot detect nonlinear relations...
Recently, Motor Imagery (MI) based on Brain Computer Interface (BCI) systems have been noticed for neuro-rehabilitation methods. The challenging key is to correct detection of MI tasks. Probabilistic Common Spatial Pattern (P-CSP) is the most recent and efficient method for discriminating two classes of electroencephalogram (EEG) from Motor Imagery (MI) Task. P-CSP resolves the overfitting which is...
Autism is a neurodevelopmental disorder that changes the normal brain function. Several studies have reported that the patterns of brain connectivity in autistic and healthy individuals are different. In this paper the effective connectivities of autistic and healthy children were measured through Granger Causality and then applied as discriminant features to separate the two groups. To estimate the...
Independent component analysis is one of the most useful procedures in processing EEG signal, assuming to be independent, estimates the brain or non-brain sources which have reached to the electroencephalogram’s electrodes by volume conductance. In spite of the abilities of this procedure, because of some reasons like insufficient data, algorithm shortcomings and noise, it is required that the reliability...
The present study investigates the EEG source differences between adults with ADHD and aged match controls. The processing method is based on sparse representation of electrode signals and complex-valued independent component analysis with a robust measure of sparseness. Combination of scalp topography, estimated dipole source location and spectral patterns of resulted ICs were used to k-means clustering...
In recent years, the number of Internet users amazingly has grown. As a result, number of Internet-related problems like Internet addiction has increased too. Many studies have been done in the past ten years and this issue has attracted attention of many researchers. It has reported some psychiatric disorders are associated with Internet addiction but mechanism of this relation has been not discovered...
In this study, an improved method of iterative independent component analysis (/ICA) on single-trial brain responses was employed to investigate neural mechanisms underlying inhibitory control deficits in adults with attention deficit / hyperactivity disorder (ADHD). Specially recorded data during a continuous performance task from 10 ADHD and 11 healthy control subjects were analyzed. Behavioral...
This study investigates the Event Related Potentials (ERP) obtained from Independent Components of EEG (ERPIC) while participants performed a sustained attention task. EEG signals were recorded from 50 adult participants including ADHD and normal subjects while performing Continuous Performance Test (CPT). Signals were recorded from 21 Ag/AgCl electrodes according to the international 10-20 standard...
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