Studies on electroencephalography have revealed pointers for repetitive phase transitions in neocortex atframe rates in the theta and alpha bands. Phase transitions are the first step for frame emergence. Within the frame, brain activity is synchronized and amplitude and phase modulation pattern materialize. The phase patterns have radial symmetry resembling a cone. Cone fitting has been used to detect andstudyframes in different brain states, including task, awake, sleep and transition into epileptic seizure, revealing signs of disorganization before the seizure episode started. In this paper anew methodology todetectframes is presented. It is faster than the cone fitting previously used to studyframes. The results are compared with frames obtained from cone fitting in awake, task, sleep and seizure states. The framesdetected by cone fitting and the new method showed high levels of coincidence in time. The disorganization signs observed between pre-ictal period and normal brain state were also observed in the frames detected with the new method. Finally amplitude modulation patterns related to the different behavioral states were clearly distinguishable using the new method frames as time markers for pattern extraction.

Prior studies of multichannel ECoG from animals showed that beta and gamma oscillations carried percep- tual 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 ana- lytic 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.