Kashihara, S. | bioRxiv Science

bioRxiv2024

Topographical polarity reveals continuous EEG microstate transitions and electric field direction in healthy aging

EEG microstate sequences, representing whole-brain spatial potential distribution patterns of the EEG, offer valuable insights for capturing 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. This study aimed 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 showed fewer transitions on the microstate D-C-E axis in older adults. In contrast, transitions among microstates A, D, and B increased in the older group and were mainly observed within 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 the co-occurrence of each transition, 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. These features were nearly replicated in independent data, indicating their robustness in characterizing age-related electrophysiological spatiotemporal dynamics.

neuroscience↗

bioRxiv2023

Spatio-temporal "global" neurodynamics in both continuous and discrete pictures for human brains

The neural manifold in state space represents the mass neural dynamics of a biological system. A challenging modern approach treats the brain as a whole in terms of the interaction between the agent and the world. Therefore, we need to develop a method for this global neural workspace. The current study aimed to visualize spontaneous neural trajectories regardless of their measuring modalities (electroencephalography [EEG], functional magnetic resonance imaging [fMRI], and magnetoencephalography [MEG]). First, we examined the possible visualization of EEG manifolds. These results suggest that a spherical surface can be clearly observed within the spatial similarity space where canonical microstates are on-manifold. Once valid (e.g., differentiable) and useful (e.g., low-dimensional) manifolds are obtained, the nature of the sphere, such as shape and size, becomes a possible target of interest. Because these should be practically useful, we suggest advantages of the EEG manifold (essentially continuous) or the state transition matrix (coarse-grained discrete). Finally, because our basic procedure is modality-independent, MEG and fMRI manifolds were also compared. These results strongly suggest the need to update our understanding of neural mass representations to include robust "global" dynamics.

neuroscience↗