Abstract

The coordinated activity of cortical neurons is generally in a metastable state at or near the state of criticality. Any slight input, internal, e.g., a thought, or external, e.g., visual stimuli, could cause a phase state transition, producing a small perturbation in the measured EEG or ECoG data. These give rise to sharp phase slips in the phase of EEG data, which can be used as a biomarker to study the behavior of the brain. In this talk I will present a brief theory of corticalphase transitions, Hilbert transform techniques to extract spatiotemporal patterns of phase slipsand phase cones from the EEG data, and their applications to human cognition and epilepsylocalizations. The phase slip rates (PSRs) were studied from the high-density (256 channel) EEG data of five adult subjects during covert visual object naming tasks [Ramon et al., 2023]. The spatiotemporalprofiles of EEG and PSRs during the stimulus and the first second of the poststimulus periodwere examined in detail to study the visual evoked potentials and different stages of visual objectrecognition in the visual, language, and memory areas. It was found that the activity areas of PSRs differed from EEG activity areas during the stimulus and poststimulus periods. Different stages of the insight moments during the covert object naming tasks were examined from PSRs and found to be about 512±21 ms for the ‘Eureka' moment.

Similarly, the phase cone activities in the low gamma band (30–50 Hz) and the ripple band(80–150 Hz) were extracted from the 256-channel high-density data of adult patients. Stablephase cone patterns were selected based on the criteria that the sign of the spatial gradient did notchange for at least three consecutive time samples and the frame velocity was within the range ofpropagation velocities of cortical axons. The spatiotemporal plots exhibited dynamical formationof phase cones which were higher in the seizure area than in the nearby surrounding brain areas. Overall, these results indicate that information about the cortical phase transitionscan be derived from the measured EEG data and can be used as a biomarker to study thecognitive behavior and epileptogenic activity of the brain.