Introduction: It has been shown that intelligence as a general mental ability is related to the structure and function of the brain regions. However, the specificity of these regional dependencies to the intelligence scores in the typical and atypical developed individuals needs to be well understood. In this study, we hypothesized that neural correlates of IQ should not have a fixed pattern ra...

Background: Muscle fatigue has been known to influence brain activity, but very little is known about how cortical centers respond to muscle fatigue.Objective: This study was conducted to investigate the effects of muscle contraction and fatigue induced by two different percents of maximal voluntary contraction (MVC) on Electroencephalography (EEG) signals.Material and Methods: In t...

Introduction: Brain visual evoked potential (VEP) signals are commonly known to be accompanied by high levels of background noise typically from the spontaneous background brain activity of electroencephalography (EEG) signals. Material and Methods: A model based on dyadic filter bank, discrete wavelet transform (DWT), and singular value decomposition (SVD) was developed to analyze the raw data...

Here we reviewed the last evidence on application of electroencephalography (EEG) as a non-invasive and portable neuroimaging method useful to extract hallmarks neuroplasticity induced by virtual reality (VR) rehabilitation approaches in stroke patients. In neurorehabilitation context, VR training has been used extensively hamper effects motor treatments stroke’s brain. The concept underlying t...

This article presents a hybrid wavelet-based algorithm to suppress the ocular artifacts from electroencephalography (EEG) signals. The wavelet transform (HWT) method is designed by combination of discrete decomposition and packet transform. artifact suppression performed selection sub-bands obtained HWT. Fractional Gaussian noise (fGn) used as reference signal select containing artifacts. multi...

Electroencephalography is a measure of brain activity by wave analysis; it consist number of electrodes. Finding most non-dominant electrode positions in Eye state classification is important task for classification. The proposed work is identifying which electrodes are less responsible for classification. This is a feature selection step required for optimal EEG channel selection. Feature sele...

Electroencephalography (EEG) is a tool that allows us to analyze brain activity with high temporal resolution. These measures, combined deep learning and digital signal processing, are widely used in neurological disorder detection emotion mental recognition. In this paper, new method for recognition presented: instantaneous frequency, spectral entropy Mel-frequency cepstral coefficients (MFCC)...

We report the use of repeat electroencephalography (EEG) in the management of 69 patients with childhood-onset absence epilepsy (CAE). Electro-clinical absences were demonstrated in seven children who were felt clinically to have persisting absences. In three of the remaining 62 patients who were thought to be seizure-free, repeat EEG showed electro-clinical absences; revision of AEDs in these ...

We report two cases of status epilepticus who showed crossed cerebellar diaschisis (CCD) with or without pulvinar high signal intensity (HSI) on brain magnetic resonance imaging (MRI). The first patient had CCD with pulvinar HSI on MRI and periodic lateralized epileptiform discharges (PLEDs) on electroencephalography. MRI of the second patient revealed CCD without pulvinar HSI. And electroencep...