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2 result(s) for "EEG phase slips"
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Phase slips extracted from derivatives of EEG data provide a deeper insight into the formation of cortical phase transitions
The phase slips are generally extracted from the EEG using Hilbert transforms but could also be extracted from the derivatives of EEG, providing additional information about the formation of cortical phase transitions. We examined this from the 30 s long, 256-channel resting state, eyes open EEG data of a 30-year-old male subject. The phase slip rates, PSR1 from EEG, PSR2 from the first-order derivative of EEG, and PSR3 from the second-order derivative of EEG, respectively, were extracted. The study was performed in the alpha (7–12 Hz) band only. The spatiotemporal plots of the EEG and phase slip rates over a 3.0 s period with a 0.5 s resolution were made with a montage layout of the 256 electrode positions. The spatiotemporal patterns of EEG and its derivatives exhibited shifting activity from posterior visual areas to the central and frontal regions over the 3.0 s period. The PSR1, PSR2, and PSR3 activity areas were different from the EEG and were distributed in larger areas as compared with the EEG and its derivatives. Also, the PSR2 and PSR3 activity areas and magnitudes were significantly different as compared with the PSR1 alone. This was also confirmed ( p  < 0.01) by the one-way ANOVA analysis of the means of PSR1, PSR2, and PSR3. These results show that PSR2 and PSR3 carry additional information that could potentially be biomarkers for studying the rate of formation of phase slips and the related cortical activity from the derivatives of EEG data.
Spatiotemporal phase slip patterns for visual evoked potentials, covert object naming tasks, and insight moments extracted from 256 channel EEG recordings
Phase slips arise from state transitions of the coordinated activity of cortical neurons which can be extracted from the EEG data. The phase slip rates (PSRs) were studied from the high-density (256 channel) EEG data, sampled at 16.384 kHz, of five adult subjects during covert visual object naming tasks. Artifact-free data from 29 trials were averaged for each subject. The analysis was performed to look for phase slips in the theta (4–7 Hz), alpha (7–12 Hz), beta (12–30 Hz), and low gamma (30–49 Hz) bands. The phase was calculated with the Hilbert transform, then unwrapped and detrended to look for phase slip rates in a 1.0 ms wide stepping window with a step size of 0.06 ms. The spatiotemporal plots of the PSRs were made by using a montage layout of 256 equidistant electrode positions. The spatiotemporal profiles of EEG and PSRs during the stimulus and the first second of the post-stimulus period were examined in detail to study the visual evoked potentials and different stages of visual object recognition in the visual, language, and memory areas. It was found that the activity areas of PSRs were different as compared with EEG activity areas during the stimulus and post-stimulus periods. Different stages of the insight moments during the covert object naming tasks were examined from PSRs and it was found to be about 512 ± 21 ms for the ‘Eureka’ moment. Overall, these results indicate that information about the cortical phase transitions can be derived from the measured EEG data and can be used in a complementary fashion to study the cognitive behavior of the brain.