TYPE Original Research PUBLISHED 13 June 2023 DOI 10.3389/fnint.2023.1087976 OPEN ACCESS EDITED BY Christopher Buneo, Arizona State University, United States REVIEWED BY Seppo P. Ahlfors, Massachusetts General Hospital and Harvard Medical School, United States K. Jeffrey Eriksen, Legacy Research Institute, United States *CORRESPONDENCE Ceon Ramon ceon@uw.edu RECEIVED 02 November 2022 ACCEPTED 19 May 2023 PUBLISHED 13 June 2023 CITATION Ramon C, Graichen U, Gargiulo P, Zanow F, Knösche TR and Haueisen J (2023) Spatiotemporal phase slip patterns for visual evoked potentials, covert object naming tasks, and insight moments extracted from 256 channel EEG recordings. Front. Integr. Neurosci. 17:1087976. doi: 10.3389/fnint.2023.1087976 COPYRIGHT © 2023 Ramon, Graichen, Gargiulo, Zanow, Knösche and Haueisen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Spatiotemporal phase slip patterns for visual evoked potentials, covert object naming tasks, and insight moments extracted from 256 channel EEG recordings Ceon Ramon 1,2 *, Uwe Graichen 3 , Paolo Gargiulo 4,5 , Frank Zanow 6 , Thomas R. Knösche 7 and Jens Haueisen 8 1 Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, United States, 2 Regional Epilepsy Center, Harborview Medical Center, University of Washington, Seattle, WA, United States, 3 Department of Biostatistics and Data Science, Karl Landsteiner University of Health Sciences, Krems an der Donau, Austria, 4 Institute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland, 5 Department of Science, Landspitali University Hospital, Reykjavik, Iceland, 6 ANT Neuro, Hengelo, Netherlands, 7 Max Planck Institute for Human Cognitive and Neurosciences, Leipzig, Germany, 8 Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany 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. KEYWORDS EEG phase slips, phase jumps, cortical neurodynamics, VEP, cortical phase transitions, insight moments, eureka effects, visual object naming Abbreviations: PSR, phase slip rate; PSRs, phase slip rates; VEP, visual evoked potentials. Frontiers in Integrative Neuroscience 01 frontiersin.org