Phase Resetting on Scalp EEG, Study on Its Synchrony and Distribution

Ruiz, Yusely; Pockett, Susan; Freeman, Walter; González, Eduardo; Li, Guang

doi:10.1007/978-90-481-9695-1_54

Cited by 1 publication

(3 citation statements)

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“…Phase resetting was also dependent on the reference (Ruiz et al, 2009b) so the frame locations were also slightly different. However the classification rates were similar for the two references using their respective frames located by the optimization process.…”

Section: Resultsmentioning

confidence: 99%

“…Each state transition begins with an abrupt change in phase, followed by synchronization at a new frequency and the stabilization of a new AM pattern. Abrupt phase resetting has also been observed in the scalp EEG (Freeman et al, 2003a;Ruiz et al, 2009b), and although these phase resettings were not simultaneous over large numbers of channels, they were clustered in time, suggesting that the phase discontinuities necessary for the emergence of brain activity patterns related to cognition can also be studied using EEG signals, despite the difference in scale, corruption by electromyographic noise, distortions by gyrification, distance, etc. The phase resettings are independent of the central frequency of the temporal filter, but dependent on the bandwidth of the filter in a proportion close to 0.641 as predicted by Rice (1944).…”

Section: Discussionmentioning

confidence: 99%

“…The phase resetting in ECoG and EEG signals had been studied by the use of the Hilbert Transform (Freeman et al, 2003a(Freeman et al, , 2006aRuiz et al, 2009b) showing that the time lapse between phase resetting showed properties similar to a "Rice distribution" (Rice, 1944;Freeman, 2009).…”

Section: Experimental Design and Signal Pre-processingmentioning

confidence: 99%

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A method to study global spatial patterns related to sensory perception in scalp EEG

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Journal of Neuroscience Methods

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a b s t r a c tPrior studies of multichannel ECoG from animals showed that beta and gamma oscillations carried perceptual information in both local and global spatial patterns of amplitude modulation, when the subjects were trained to discriminate conditioned stimuli (CS). Here the hypothesis was tested that similar patterns could be found in the scalp EEG human subjects trained to discriminate simultaneous visual-auditory CS. Signals were continuously recorded from 64 equispaced scalp electrodes and band-pass filtered. The Hilbert transform gave the analytic phase, which segmented the EEG into temporal frames, and the analytic amplitude, which expressed the pattern in each frame as a feature vector. Methods applied to the ECoG were adapted to the EEG for systematic search of the beta-gamma spectrum, the time period after CS onset, and the scalp surface to locate patterns that could be classified with respect to type of CS. Spatial patterns of EEG amplitude modulation were found from all subjects that could be classified with respect to stimulus combination type significantly above chance levels. The patterns were found in the beta range (15-22 Hz) but not in the gamma range. They occurred in three short bursts following CS onset. They were non-local, occupying the entire array. Our results suggest that the scalp EEG can yield information about the timing of episodically synchronized brain activity in higher cognitive function, so that future studies in brain-computer interfacing can be better focused. Our methods may be most valuable for analyzing data from dense arrays with very high spatial and temporal sampling rates.

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Section: Resultsmentioning

confidence: 99%