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Phase slips extracted from derivatives of EEG data provide a deeper insight into the formation of cortical phase transitions
Phase slips extracted from derivatives of EEG data provide a deeper insight into the formation of cortical phase transitions
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Phase slips extracted from derivatives of EEG data provide a deeper insight into the formation of cortical phase transitions
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Phase slips extracted from derivatives of EEG data provide a deeper insight into the formation of cortical phase transitions
Phase slips extracted from derivatives of EEG data provide a deeper insight into the formation of cortical phase transitions

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Phase slips extracted from derivatives of EEG data provide a deeper insight into the formation of cortical phase transitions
Phase slips extracted from derivatives of EEG data provide a deeper insight into the formation of cortical phase transitions
Journal Article

Phase slips extracted from derivatives of EEG data provide a deeper insight into the formation of cortical phase transitions

2025
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Overview
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.
Publisher
Frontiers Research Foundation,Frontiers Media S.A