EEG signals play significant role in the study of mental disorders. Epilepsy is one major disorders and need technological support treatment. A method proposed here an endorsement technique for epileptic seizures using electroencephalogram (EEG) captured non-invasive method. The uses power spectrum density discrete wavelet transformation (DWT). impact spectral analysis along with usage characte...

Background: Like the brain, muscles also generate electrical signals. These signals are picked up by EEG electrodes and become muscle artifacts in EEG recording. MA is looking like fast oscillations. EEG signals disturbed by MA have larger amplitudes than normal EEG signals. Human beings have a large number of muscles all over their bodies. The muscle movement that happens near electrodes, such...

Electroencephalogram (EEG) recordings are often contaminated with ocular and muscle artifacts. In this paper, the canonical correlation analysis (CCA) is used as blind source separation (BSS) technique (BSS-CCA) to decompose the artifact contaminated EEG into component signals. We combine the BSSCCA technique with wavelet filtering approach for minimizing both ocular and muscle artifacts simult...

Although event-related potentials (ERPs) are widely used to study sensory, perceptual and cognitive processes, it remains unknown whether they are phase-locked signals superimposed upon the ongoing electroencephalogram (EEG) or result from phase-alignment of the EEG. Previous attempts to discriminate between these hypotheses have been unsuccessful but here a new test is presented based on the p...

We have theorized that large neurons in the ventral and medial reticular formation of the medulla are critical for both autonomic and cortical arousal. To test this theory, we anesthetized rats with urethane, lowered concentric bipolar stimulating electrodes into the medullary reticular formation, and implanted electroencephalogram (EEG) and ECG recording electrodes. We stimulated in the medull...

1287 Commentary—Colrain and Baker data showing differences between 15-16 and 17-18 years, with those collected in a similar design but from younger adolescents highlights the fact that later adolescents are still showing dramatic changes in sleep EEG power, reflecting ongoing changes in brain development. Tarokh et al. show smaller changes in the occipital (particularly left occipital) derivati...