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Updated: Sep 11, 2025

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
Published on: June 15, 2018
Topographical polarity reveals continuous EEG microstate transitions and electric field direction in healthy aging
Shiho Kashihara1, Tomohisa Asai1, Hiroshi Imamizu1,2
1Department of Cognitive Neuroscience, Cognitive Mechanisms Laboratories, Advanced Telecommunications Research Institute International (ATR), Keihanna Science City, Kyoto 619-0288, Japan.
Abstract:
Electroencephalography (EEG) microstate sequences, representing whole-brain spatial potential distribution patterns of the EEG, help capture spatiotemporally continuous and fluctuating neural dynamics with high temporal resolution through appropriate discretization. Recent studies suggest that EEG microstate transitions are gradual and continuous phenomena, contrary to the classical view of binary transitions. To update conventional microstate analysis to reflect continuous EEG dynamics and examine differences in age-related electrophysiological state transitions, we considered the relative positions of EEG microstates on the neural manifold and their topographical polarity. Transition probability results revealed fewer transitions on the microstate D-C-E axis in older adults but increased transitions among microstates A, D, B, and E that were mainly observed within polarity and A-B between polarity. Furthermore, the 100 microstate transitions, which are variations of the shortest transitions between 10 microstates, could be reduced to 8 principal components based on each transition co-occurrence, including hubs C and E, planar transitions through msA/B and D, and unidirectional transition components. Several transition components were potentially significant predictors of age group, independent of age-related alpha activity reductions. These patterns remained stable across longer continuous transitions over time and were nearly replicated in independent data, indicating their robustness in characterizing age-related electrophysiological spatiotemporal dynamics.

